Science.gov

Sample records for mixed-integer dynamic optimization

  1. Solving mixed integer nonlinear programming problems using spiral dynamics optimization algorithm

    NASA Astrophysics Data System (ADS)

    Kania, Adhe; Sidarto, Kuntjoro Adji

    2016-02-01

    Many engineering and practical problem can be modeled by mixed integer nonlinear programming. This paper proposes to solve the problem with modified spiral dynamics inspired optimization method of Tamura and Yasuda. Four test cases have been examined, including problem in engineering and sport. This method succeeds in obtaining the optimal result in all test cases.

  2. MISO - Mixed Integer Surrogate Optimization

    SciTech Connect

    Mueller, Juliane

    2016-01-20

    MISO is an optimization framework for solving computationally expensive mixed-integer, black-box, global optimization problems. MISO uses surrogate models to approximate the computationally expensive objective function. Hence, derivative information, which is generally unavailable for black-box simulation objective functions, is not needed. MISO allows the user to choose the initial experimental design strategy, the type of surrogate model, and the sampling strategy.

  3. Identification of regulatory structure and kinetic parameters of biochemical networks via mixed-integer dynamic optimization

    PubMed Central

    2013-01-01

    Background Recovering the network topology and associated kinetic parameter values from time-series data are central topics in systems biology. Nevertheless, methods that simultaneously do both are few and lack generality. Results Here, we present a rigorous approach for simultaneously estimating the parameters and regulatory topology of biochemical networks from time-series data. The parameter estimation task is formulated as a mixed-integer dynamic optimization problem with: (i) binary variables, used to model the existence of regulatory interactions and kinetic effects of metabolites in the network processes; and (ii) continuous variables, denoting metabolites concentrations and kinetic parameters values. The approach simultaneously optimizes the Akaike criterion, which captures the trade-off between complexity (measured by the number of parameters), and accuracy of the fitting. This simultaneous optimization mitigates a possible overfitting that could result from addition of spurious regulatory interactions. Conclusion The capabilities of our approach were tested in one benchmark problem. Our algorithm is able to identify a set of plausible network topologies with their associated parameters. PMID:24176044

  4. Stochastic Dynamic Mixed-Integer Programming (SD-MIP)

    DTIC Science & Technology

    2015-05-05

    door to stochastic optimization models, which are typically dynamic in nature. This project lays the foundation for stochastic dynamic mixed...project lays the foundation for stochastic dynamic mixed-integer and linear programming (SD-MIP). This project has produced several new ideas in...models. Recent research has opened the door to stochastic optimization models, which are typically dynamic in nature. This project lays the foundation for

  5. Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach

    PubMed Central

    Henriques, David; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R.

    2015-01-01

    Motivation: Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a combination of links subject to great uncertainty or no information about the kinetic parameters. Results: In this work, we combine a logic-based formalism, to describe all the possible regulatory structures for a given dynamic model of a pathway, with mixed-integer dynamic optimization (MIDO). This framework aims to simultaneously identify the regulatory structure (represented by binary parameters) and the real-valued parameters that are consistent with the available experimental data, resulting in a logic-based differential equation model. The alternative to this would be to perform real-valued parameter estimation for each possible model structure, which is not tractable for models of the size presented in this work. The performance of the method presented here is illustrated with several case studies: a synthetic pathway problem of signaling regulation, a two-component signal transduction pathway in bacterial homeostasis, and a signaling network in liver cancer cells. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: julio@iim.csic.es or saezrodriguez@ebi.ac.uk PMID:26002881

  6. Mixed integer simulation optimization for optimal hydraulic fracturing and production of shale gas fields

    NASA Astrophysics Data System (ADS)

    Li, J. C.; Gong, B.; Wang, H. G.

    2016-08-01

    Optimal development of shale gas fields involves designing a most productive fracturing network for hydraulic stimulation processes and operating wells appropriately throughout the production time. A hydraulic fracturing network design-determining well placement, number of fracturing stages, and fracture lengths-is defined by specifying a set of integer ordered blocks to drill wells and create fractures in a discrete shale gas reservoir model. The well control variables such as bottom hole pressures or production rates for well operations are real valued. Shale gas development problems, therefore, can be mathematically formulated with mixed-integer optimization models. A shale gas reservoir simulator is used to evaluate the production performance for a hydraulic fracturing and well control plan. To find the optimal fracturing design and well operation is challenging because the problem is a mixed integer optimization problem and entails computationally expensive reservoir simulation. A dynamic simplex interpolation-based alternate subspace (DSIAS) search method is applied for mixed integer optimization problems associated with shale gas development projects. The optimization performance is demonstrated with the example case of the development of the Barnett Shale field. The optimization results of DSIAS are compared with those of a pattern search algorithm.

  7. Optimized Waterspace Management and Scheduling Using Mixed-Integer Linear Programming

    DTIC Science & Technology

    2016-01-01

    TECHNICAL REPORT NSWC PCD TR 2015-003 OPTIMIZED WATERSPACE MANAGEMENT AND SCHEDULING USING MIXED-INTEGER LINEAR PROGRAMMING...effects on optimization quality . 24 3 NSWC PCD TR 2015-003 Optimized Waterspace Mgt 1 Introduction The use of autonomous systems to perform increasingly...constraints required for the mathematical formulation of the MCM scheduling problem pertaining to the survey constraints and logistics management . The

  8. Mixed-Integer Nonconvex Quadratic Optimization Relaxations and Performance Analysis

    DTIC Science & Technology

    2016-10-11

    portfolio deleveraging with market impact,” (Jingnan Chen, Liming Feng, Jiming Peng, Yinyu Ye), Operations Research, 62(1) (2014) 195-206. In this...Stanley 2012 Prize for Excellence in Financial Markets , First runner-up. “Space tensor conic programming,” (L Qi and Y Ye), Computational Optimization...portfolio deleveraging with market impact," (J. Chen, L. Feng, J. Peng, Y. Ye), Operations Research, 62(1) (2014) 195-206. "Simultaneous Beam Sampling

  9. Enhanced index tracking modeling in portfolio optimization with mixed-integer programming z approach

    NASA Astrophysics Data System (ADS)

    Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin

    2014-09-01

    Enhanced index tracking is a popular form of portfolio management in stock market investment. Enhanced index tracking aims to construct an optimal portfolio to generate excess return over the return achieved by the stock market index without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using mixed-integer programming model which adopts regression approach in order to generate higher portfolio mean return than stock market index return. In this study, the data consists of 24 component stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2012. The results of this study show that the optimal portfolio of mixed-integer programming model is able to generate higher mean return than FTSE Bursa Malaysia Kuala Lumpur Composite Index return with only selecting 30% out of the total stock market index components.

  10. Comparison of penalty functions on a penalty approach to mixed-integer optimization

    NASA Astrophysics Data System (ADS)

    Francisco, Rogério B.; Costa, M. Fernanda P.; Rocha, Ana Maria A. C.; Fernandes, Edite M. G. P.

    2016-06-01

    In this paper, we present a comparative study involving several penalty functions that can be used in a penalty approach for globally solving bound mixed-integer nonlinear programming (bMIMLP) problems. The penalty approach relies on a continuous reformulation of the bMINLP problem by adding a particular penalty term to the objective function. A penalty function based on the `erf' function is proposed. The continuous nonlinear optimization problems are sequentially solved by the population-based firefly algorithm. Preliminary numerical experiments are carried out in order to analyze the quality of the produced solutions, when compared with other penalty functions available in the literature.

  11. Optimization of a wood dryer kiln using the mixed integer programming technique: A case study

    SciTech Connect

    Gustafsson, S.I.

    1999-07-01

    When wood is to be utilized as a raw material for furniture, buildings, etc., it must be dried from approximately 100% to 6% moisture content. This is achieved at least partly in a drying kiln. Heat for this purpose is provided by electrical means, or by steam from boilers fired with wood chips or oil. By making a close examination of monitored values from an actual drying kiln it has been possible to optimize the use of steam and electricity using the so called mixed integer programming technique. Owing to the operating schedule for the drying kiln it has been necessary to divide the drying process in very short time intervals, i.e., a number of minutes. Since a drying cycle takes about two or three weeks, a considerable mathematical problem is presented and this has to be solved.

  12. Incorporation of Fixed Installation Costs into Optimization of Groundwater Remediation with a New Efficient Surrogate Nonlinear Mixed Integer Optimization Algorithm

    NASA Astrophysics Data System (ADS)

    Shoemaker, Christine; Wan, Ying

    2016-04-01

    Optimization of nonlinear water resources management issues which have a mixture of fixed (e.g. construction cost for a well) and variable (e.g. cost per gallon of water pumped) costs has been not well addressed because prior algorithms for the resulting nonlinear mixed integer problems have required many groundwater simulations (with different configurations of decision variable), especially when the solution space is multimodal. In particular heuristic methods like genetic algorithms have often been used in the water resources area, but they require so many groundwater simulations that only small systems have been solved. Hence there is a need to have a method that reduces the number of expensive groundwater simulations. A recently published algorithm for nonlinear mixed integer programming using surrogates was shown in this study to greatly reduce the computational effort for obtaining accurate answers to problems involving fixed costs for well construction as well as variable costs for pumping because of a substantial reduction in the number of groundwater simulations required to obtain an accurate answer. Results are presented for a US EPA hazardous waste site. The nonlinear mixed integer surrogate algorithm is general and can be used on other problems arising in hydrology with open source codes in Matlab and python ("pySOT" in Bitbucket).

  13. Designing cost-effective biopharmaceutical facilities using mixed-integer optimization.

    PubMed

    Liu, Songsong; Simaria, Ana S; Farid, Suzanne S; Papageorgiou, Lazaros G

    2013-01-01

    Chromatography operations are identified as critical steps in a monoclonal antibody (mAb) purification process and can represent a significant proportion of the purification material costs. This becomes even more critical with increasing product titers that result in higher mass loads onto chromatography columns, potentially causing capacity bottlenecks. In this work, a mixed-integer nonlinear programming (MINLP) model was created and applied to an industrially relevant case study to optimize the design of a facility by determining the most cost-effective chromatography equipment sizing strategies for the production of mAbs. Furthermore, the model was extended to evaluate the ability of a fixed facility to cope with higher product titers up to 15 g/L. Examination of the characteristics of the optimal chromatography sizing strategies across different titer values enabled the identification of the maximum titer that the facility could handle using a sequence of single column chromatography steps as well as multi-column steps. The critical titer levels for different ratios of upstream to dowstream trains where multiple parallel columns per step resulted in the removal of facility bottlenecks were identified. Different facility configurations in terms of number of upstream trains were considered and the trade-off between their cost and ability to handle higher titers was analyzed. The case study insights demonstrate that the proposed modeling approach, combining MINLP models with visualization tools, is a valuable decision-support tool for the design of cost-effective facility configurations and to aid facility fit decisions. 2013.

  14. Mixed integer programming model for optimizing the layout of an ICU vehicle

    PubMed Central

    2009-01-01

    Background This paper presents a Mixed Integer Programming (MIP) model for designing the layout of the Intensive Care Units' (ICUs) patient care space. In particular, this MIP model was developed for optimizing the layout for materials to be used in interventions. This work was developed within the framework of a joint project between the Madrid Technical Unverstity and the Medical Emergency Services of the Madrid Regional Government (SUMMA 112). Methods The first task was to identify the relevant information to define the characteristics of the new vehicles and, in particular, to obtain a satisfactory interior layout to locate all the necessary materials. This information was gathered from health workers related to ICUs. With that information an optimization model was developed in order to obtain a solution. From the MIP model, a first solution was obtained, consisting of a grid to locate the different materials needed for the ICUs. The outcome from the MIP model was discussed with health workers to tune the solution, and after slightly altering that solution to meet some requirements that had not been included in the mathematical model, the eventual solution was approved by the persons responsible for specifying the characteristics of the new vehicles. According to the opinion stated by the SUMMA 112's medical group responsible for improving the ambulances (the so-called "coaching group"), the outcome was highly satisfactory. Indeed, the final design served as a basis to draw up the requirements of a public tender. Results As a result from solving the Optimization model, a grid was obtained to locate the different necessary materials for the ICUs. This grid had to be slightly altered to meet some requirements that had not been included in the mathematical model. The results were discussed with the persons responsible for specifying the characteristics of the new vehicles. Conclusion The outcome was highly satisfactory. Indeed, the final design served as a basis

  15. Footstep Planning on Uneven Terrain with Mixed-Integer Convex Optimization

    DTIC Science & Technology

    2014-08-01

    infocenter/cosinfoc/v12r2/topic/com.ibm. common.doc/doc/banner.htm [18] “ GNU linear programming kit.” [Online]. Available: http://www.gnu. org/software...planning footstep placements for a robot walking on uneven terrain with obsta- cles, using a mixed-integer quadratically-constrained quadratic program ...CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING

  16. Mixed Integer Programming Model and Incremental Optimization for Delivery and Storage Planning Using Truck Terminals

    NASA Astrophysics Data System (ADS)

    Sakakibara, Kazutoshi; Tian, Yajie; Nishikawa, Ikuko

    We discuss the planning of transportation by trucks over a multi-day period. Each truck collects loads from suppliers and delivers them to assembly plants or a truck terminal. By exploiting the truck terminal as a temporal storage, we aim to increase the load ratio of each truck and to minimize the lead time for transportation. In this paper, we show a mixed integer programming model which represents each product explicitly, and discuss the decomposition of the problem into a problem of delivery and storage, and a problem of vehicle routing. Based on this model, we propose a relax-and-fix type heuristic in which decision variables are fixed one by one by mathematical programming techniques such as branch-and-bound methods.

  17. Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

    NASA Technical Reports Server (NTRS)

    Cheung, Kar-Ming; Lee, Charles H.

    2012-01-01

    We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.

  18. Optimal planning of co-firing alternative fuels with coal in a power plant by grey nonlinear mixed integer programming model.

    PubMed

    Ko, Andi Setiady; Chang, Ni-Bin

    2008-07-01

    Energy supply and use is of fundamental importance to society. Although the interactions between energy and environment were originally local in character, they have now widened to cover regional and global issues, such as acid rain and the greenhouse effect. It is for this reason that there is a need for covering the direct and indirect economic and environmental impacts of energy acquisition, transport, production and use. In this paper, particular attention is directed to ways of resolving conflict between economic and environmental goals by encouraging a power plant to consider co-firing biomass and refuse-derived fuel (RDF) with coal simultaneously. It aims at reducing the emission level of sulfur dioxide (SO(2)) in an uncertain environment, using the power plant in Michigan City, Indiana as an example. To assess the uncertainty by a comparative way both deterministic and grey nonlinear mixed integer programming (MIP) models were developed to minimize the net operating cost with respect to possible fuel combinations. It aims at generating the optimal portfolio of alternative fuels while maintaining the same electricity generation simultaneously. To ease the solution procedure stepwise relaxation algorithm was developed for solving the grey nonlinear MIP model. Breakeven alternative fuel value can be identified in the post-optimization stage for decision-making. Research findings show that the inclusion of RDF does not exhibit comparative advantage in terms of the net cost, albeit relatively lower air pollution impact. Yet it can be sustained by a charge system, subsidy program, or emission credit as the price of coal increases over time.

  19. Mixed Integer Programming and Heuristic Scheduling for Space Communication

    NASA Technical Reports Server (NTRS)

    Lee, Charles H.; Cheung, Kar-Ming

    2013-01-01

    Optimal planning and scheduling for a communication network was created where the nodes within the network are communicating at the highest possible rates while meeting the mission requirements and operational constraints. The planning and scheduling problem was formulated in the framework of Mixed Integer Programming (MIP) to introduce a special penalty function to convert the MIP problem into a continuous optimization problem, and to solve the constrained optimization problem using heuristic optimization. The communication network consists of space and ground assets with the link dynamics between any two assets varying with respect to time, distance, and telecom configurations. One asset could be communicating with another at very high data rates at one time, and at other times, communication is impossible, as the asset could be inaccessible from the network due to planetary occultation. Based on the network's geometric dynamics and link capabilities, the start time, end time, and link configuration of each view period are selected to maximize the communication efficiency within the network. Mathematical formulations for the constrained mixed integer optimization problem were derived, and efficient analytical and numerical techniques were developed to find the optimal solution. By setting up the problem using MIP, the search space for the optimization problem is reduced significantly, thereby speeding up the solution process. The ratio of the dimension of the traditional method over the proposed formulation is approximately an order N (single) to 2*N (arraying), where N is the number of receiving antennas of a node. By introducing a special penalty function, the MIP problem with non-differentiable cost function and nonlinear constraints can be converted into a continuous variable problem, whose solution is possible.

  20. Constrained spacecraft reorientation using mixed integer convex programming

    NASA Astrophysics Data System (ADS)

    Tam, Margaret; Glenn Lightsey, E.

    2016-10-01

    A constrained attitude guidance (CAG) system is developed using convex optimization to autonomously achieve spacecraft pointing objectives while meeting the constraints imposed by on-board hardware. These constraints include bounds on the control input and slew rate, as well as pointing constraints imposed by the sensors. The pointing constraints consist of inclusion and exclusion cones that dictate permissible orientations of the spacecraft in order to keep objects in or out of the field of view of the sensors. The optimization scheme drives a body vector towards a target inertial vector along a trajectory that consists solely of permissible orientations in order to achieve the desired attitude for a given mission mode. The non-convex rotational kinematics are handled by discretization, which also ensures that the quaternion stays unity norm. In order to guarantee an admissible path, the pointing constraints are relaxed. Depending on how strict the pointing constraints are, the degree of relaxation is tuneable. The use of binary variables permits the inclusion of logical expressions in the pointing constraints in the case that a set of sensors has redundancies. The resulting mixed integer convex programming (MICP) formulation generates a steering law that can be easily integrated into an attitude determination and control (ADC) system. A sample simulation of the system is performed for the Bevo-2 satellite, including disturbance torques and actuator dynamics which are not modeled by the controller. Simulation results demonstrate the robustness of the system to disturbances while meeting the mission requirements with desirable performance characteristics.

  1. Mixed-Integer Formulations for Constellation Scheduling

    NASA Astrophysics Data System (ADS)

    Valicka, C.; Hart, W.; Rintoul, M.

    Remote sensing systems have expanded the set of capabilities available for and critical to national security. Cooperating, high-fidelity sensing systems and growing mission applications have exponentially increased the set of potential schedules. A definitive lack of advanced tools places an increased burden on operators, as planning and scheduling remain largely manual tasks. This is particularly true in time-critical planning activities where operators aim to accomplish a large number of missions through optimal utilization of single or multiple sensor systems. Automated scheduling through identification and comparison of alternative schedules remains a challenging problem applicable across all remote sensing systems. Previous approaches focused on a subset of sensor missions and do not consider ad-hoc tasking. We have begun development of a robust framework that leverages the Pyomo optimization modeling language for the design of a tool to assist sensor operators planning under the constraints of multiple concurrent missions and uncertainty. Our scheduling models have been formulated to address the stochastic nature of ad-hoc tasks inserted under a variety of scenarios. Operator experience is being leveraged to select appropriate model objectives. Successful development of the framework will include iterative development of high-fidelity mission models that consider and expose various schedule performance metrics. Creating this tool will aid time-critical scheduling by increasing planning efficiency, clarifying the value of alternative modalities uniquely provided by multi-sensor systems, and by presenting both sets of organized information to operators. Such a tool will help operators more quickly and fully utilize sensing systems, a high interest objective within the current remote sensing operations community. Preliminary results for mixed-integer programming formulations of a sensor scheduling problem will be presented. Assumptions regarding sensor geometry

  2. Optimized oral cholera vaccine distribution strategies to minimize disease incidence: A mixed integer programming model and analysis of a Bangladesh scenario.

    PubMed

    Smalley, Hannah K; Keskinocak, Pinar; Swann, Julie; Hinman, Alan

    2015-11-17

    In addition to improved sanitation, hygiene, and better access to safe water, oral cholera vaccines can help to control the spread of cholera in the short term. However, there is currently no systematic method for determining the best allocation of oral cholera vaccines to minimize disease incidence in a population where the disease is endemic and resources are limited. We present a mathematical model for optimally allocating vaccines in a region under varying levels of demographic and incidence data availability. The model addresses the questions of where, when, and how many doses of vaccines to send. Considering vaccine efficacies (which may vary based on age and the number of years since vaccination), we analyze distribution strategies which allocate vaccines over multiple years. Results indicate that, given appropriate surveillance data, targeting age groups and regions with the highest disease incidence should be the first priority, followed by other groups primarily in order of disease incidence, as this approach is the most life-saving and cost-effective. A lack of detailed incidence data results in distribution strategies which are not cost-effective and can lead to thousands more deaths from the disease. The mathematical model allows for what-if analysis for various vaccine distribution strategies by providing the ability to easily vary parameters such as numbers and sizes of regions and age groups, risk levels, vaccine price, vaccine efficacy, production capacity and budget.

  3. Finding community structures in complex networks using mixed integer optimisation

    NASA Astrophysics Data System (ADS)

    Xu, G.; Tsoka, S.; Papageorgiou, L. G.

    2007-11-01

    The detection of community structure has been used to reveal the relationships between individual objects and their groupings in networks. This paper presents a mathematical programming approach to identify the optimal community structures in complex networks based on the maximisation of a network modularity metric for partitioning a network into modules. The overall problem is formulated as a mixed integer quadratic programming (MIQP) model, which can then be solved to global optimality using standard optimisation software. The solution procedure is further enhanced by developing special symmetry-breaking constraints to eliminate equivalent solutions. It is shown that additional features such as minimum/maximum module size and balancing among modules can easily be incorporated in the model. The applicability of the proposed optimisation-based approach is demonstrated by four examples. Comparative results with other approaches from the literature show that the proposed methodology has superior performance while global optimum is guaranteed.

  4. Flexible interval mixed-integer bi-infinite programming for environmental systems management under uncertainty.

    PubMed

    He, L; Huang, G H; Lu, H W

    2009-04-01

    A number of inexact programming methods have been developed for municipal solid waste management under uncertainty. However, most of them do not allow the parameters in the objective and constraints of a programming problem to be functional intervals (i.e., the lower and upper bounds of the intervals are functions of impact factors). In this study, a flexible interval mixed-integer bi-infinite programming (FIMIBIP) method is developed in response to the above concern. A case study is also conducted; the solutions are then compared with those obtained from interval mixed-integer bi-infinite programming (IMIBIP) and fuzzy interval mixed-integer programming (FIMIP) methods. It is indicated that the solutions through FIMIBIP can provide decision support for cost-effectively diverting municipal solid waste, and for sizing, timing and siting the facilities' expansion during the entire planning horizon. These schemes are more flexible than those identified through IMIBIP since the tolerance intervals are introduced to measure the level of constraints satisfaction. The FIMIBIP schemes may also be robust since the solutions are "globally-optimal" under all scenarios caused by the fluctuation of gas/energy prices, while the conventional ones are merely "locally-optimal" under a certain scenario.

  5. Models and Algorithms Involving Very Large Scale Stochastic Mixed-Integer Programs

    DTIC Science & Technology

    2011-02-28

    give rise to a non - convex and discontinuous recourse function that may be difficult to optimize . As a result of this project, there have been... convex , the master problem in (3.1.6)-(3.1.9) is a non - convex mixed-integer program, and as indicated in [C.1], this approach is not scalable without...the first stage would result in a Benders’ master program which is non - convex , leading to a problem that is not any easier than (3.1.5). Nevertheless

  6. Inexact fuzzy-stochastic mixed-integer programming approach for long-term planning of waste management--Part A: methodology.

    PubMed

    Guo, P; Huang, G H

    2009-01-01

    In this study, an inexact fuzzy chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is proposed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing inexact two-stage programming and mixed-integer linear programming techniques by incorporating uncertainties expressed as multiple uncertainties of intervals and dual probability distributions within a general optimization framework. The developed method can provide an effective linkage between the predefined environmental policies and the associated economic implications. Four special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it provides a linkage to predefined policies that have to be respected when a modeling effort is undertaken; secondly, it is useful for tackling uncertainties presented as intervals, probabilities, fuzzy sets and their incorporation; thirdly, it facilitates dynamic analysis for decisions of facility-expansion planning and waste-flow allocation within a multi-facility, multi-period, multi-level, and multi-option context; fourthly, the penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised solid waste-generation rates are violated. In a companion paper, the developed method is applied to a real case for the long-term planning of waste management in the City of Regina, Canada.

  7. PySP : modeling and solving stochastic mixed-integer programs in Python.

    SciTech Connect

    Woodruff, David L.; Watson, Jean-Paul

    2010-08-01

    Although stochastic programming is a powerful tool for modeling decision-making under uncertainty, various impediments have historically prevented its widespread use. One key factor involves the ability of non-specialists to easily express stochastic programming problems as extensions of deterministic models, which are often formulated first. A second key factor relates to the difficulty of solving stochastic programming models, particularly the general mixed-integer, multi-stage case. Intricate, configurable, and parallel decomposition strategies are frequently required to achieve tractable run-times. We simultaneously address both of these factors in our PySP software package, which is part of the COIN-OR Coopr open-source Python project for optimization. To formulate a stochastic program in PySP, the user specifies both the deterministic base model and the scenario tree with associated uncertain parameters in the Pyomo open-source algebraic modeling language. Given these two models, PySP provides two paths for solution of the corresponding stochastic program. The first alternative involves writing the extensive form and invoking a standard deterministic (mixed-integer) solver. For more complex stochastic programs, we provide an implementation of Rockafellar and Wets Progressive Hedging algorithm. Our particular focus is on the use of Progressive Hedging as an effective heuristic for approximating general multi-stage, mixed-integer stochastic programs. By leveraging the combination of a high-level programming language (Python) and the embedding of the base deterministic model in that language (Pyomo), we are able to provide completely generic and highly configurable solver implementations. PySP has been used by a number of research groups, including our own, to rapidly prototype and solve difficult stochastic programming problems.

  8. PIPS-SBB: A Parallel Distributed-Memory Branch-and-Bound Algorithm for Stochastic Mixed-Integer Programs

    SciTech Connect

    Munguia, Lluis-Miquel; Oxberry, Geoffrey; Rajan, Deepak

    2016-05-01

    Stochastic mixed-integer programs (SMIPs) deal with optimization under uncertainty at many levels of the decision-making process. When solved as extensive formulation mixed- integer programs, problem instances can exceed available memory on a single workstation. In order to overcome this limitation, we present PIPS-SBB: a distributed-memory parallel stochastic MIP solver that takes advantage of parallelism at multiple levels of the optimization process. We also show promising results on the SIPLIB benchmark by combining methods known for accelerating Branch and Bound (B&B) methods with new ideas that leverage the structure of SMIPs. Finally, we expect the performance of PIPS-SBB to improve further as more functionality is added in the future.

  9. PIPS-SBB: A Parallel Distributed-Memory Branch-and-Bound Algorithm for Stochastic Mixed-Integer Programs

    DOE PAGES

    Munguia, Lluis-Miquel; Oxberry, Geoffrey; Rajan, Deepak

    2016-05-01

    Stochastic mixed-integer programs (SMIPs) deal with optimization under uncertainty at many levels of the decision-making process. When solved as extensive formulation mixed- integer programs, problem instances can exceed available memory on a single workstation. In order to overcome this limitation, we present PIPS-SBB: a distributed-memory parallel stochastic MIP solver that takes advantage of parallelism at multiple levels of the optimization process. We also show promising results on the SIPLIB benchmark by combining methods known for accelerating Branch and Bound (B&B) methods with new ideas that leverage the structure of SMIPs. Finally, we expect the performance of PIPS-SBB to improve furthermore » as more functionality is added in the future.« less

  10. Item Pool Construction Using Mixed Integer Quadratic Programming (MIQP). GMAC® Research Report RR-14-01

    ERIC Educational Resources Information Center

    Han, Kyung T.; Rudner, Lawrence M.

    2014-01-01

    This study uses mixed integer quadratic programming (MIQP) to construct multiple highly equivalent item pools simultaneously, and compares the results from mixed integer programming (MIP). Three different MIP/MIQP models were implemented and evaluated using real CAT item pool data with 23 different content areas and a goal of equal information…

  11. A Composite Algorithm for Mixed Integer Constrained Nonlinear Optimization.

    DTIC Science & Technology

    1980-01-01

    nature of the problem, auxiliary techniques including Lagrange multipliers, penalty functions, linearization, and rounding have all been used to aid in...result is a series of problems Pn with solutions Sn. If the sequence of problems is appropriately selected, two useful properties result. First...knowledge of 19 the solution to the (n)th problem aids in the solution of the (n+l)st problem. Second, the sequence of solutions Sn tends to the solution

  12. Final Report---Next-Generation Solvers for Mixed-Integer Nonlinear Programs: Structure, Search, and Implementation

    SciTech Connect

    Linderoth, Jeff T.; Luedtke, James R.

    2013-05-30

    The mathematical modeling of systems often requires the use of both nonlinear and discrete components. Problems involving both discrete and nonlinear components are known as mixed-integer nonlinear programs (MINLPs) and are among the most challenging computational optimization problems. This research project added to the understanding of this area by making a number of fundamental advances. First, the work demonstrated many novel, strong, tractable relaxations designed to deal with non-convexities arising in mathematical formulation. Second, the research implemented the ideas in software that is available to the public. Finally, the work demonstrated the importance of these ideas on practical applications and disseminated the work through scholarly journals, survey publications, and conference presentations.

  13. Learning oncogenetic networks by reducing to mixed integer linear programming.

    PubMed

    Shahrabi Farahani, Hossein; Lagergren, Jens

    2013-01-01

    Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

  14. Automatic Design of Synthetic Gene Circuits through Mixed Integer Non-linear Programming

    PubMed Central

    Huynh, Linh; Kececioglu, John; Köppe, Matthias; Tagkopoulos, Ilias

    2012-01-01

    Automatic design of synthetic gene circuits poses a significant challenge to synthetic biology, primarily due to the complexity of biological systems, and the lack of rigorous optimization methods that can cope with the combinatorial explosion as the number of biological parts increases. Current optimization methods for synthetic gene design rely on heuristic algorithms that are usually not deterministic, deliver sub-optimal solutions, and provide no guaranties on convergence or error bounds. Here, we introduce an optimization framework for the problem of part selection in synthetic gene circuits that is based on mixed integer non-linear programming (MINLP), which is a deterministic method that finds the globally optimal solution and guarantees convergence in finite time. Given a synthetic gene circuit, a library of characterized parts, and user-defined constraints, our method can find the optimal selection of parts that satisfy the constraints and best approximates the objective function given by the user. We evaluated the proposed method in the design of three synthetic circuits (a toggle switch, a transcriptional cascade, and a band detector), with both experimentally constructed and synthetic promoter libraries. Scalability and robustness analysis shows that the proposed framework scales well with the library size and the solution space. The work described here is a step towards a unifying, realistic framework for the automated design of biological circuits. PMID:22536398

  15. Automatic design of synthetic gene circuits through mixed integer non-linear programming.

    PubMed

    Huynh, Linh; Kececioglu, John; Köppe, Matthias; Tagkopoulos, Ilias

    2012-01-01

    Automatic design of synthetic gene circuits poses a significant challenge to synthetic biology, primarily due to the complexity of biological systems, and the lack of rigorous optimization methods that can cope with the combinatorial explosion as the number of biological parts increases. Current optimization methods for synthetic gene design rely on heuristic algorithms that are usually not deterministic, deliver sub-optimal solutions, and provide no guaranties on convergence or error bounds. Here, we introduce an optimization framework for the problem of part selection in synthetic gene circuits that is based on mixed integer non-linear programming (MINLP), which is a deterministic method that finds the globally optimal solution and guarantees convergence in finite time. Given a synthetic gene circuit, a library of characterized parts, and user-defined constraints, our method can find the optimal selection of parts that satisfy the constraints and best approximates the objective function given by the user. We evaluated the proposed method in the design of three synthetic circuits (a toggle switch, a transcriptional cascade, and a band detector), with both experimentally constructed and synthetic promoter libraries. Scalability and robustness analysis shows that the proposed framework scales well with the library size and the solution space. The work described here is a step towards a unifying, realistic framework for the automated design of biological circuits.

  16. BBPH: Using progressive hedging within branch and bound to solve multi-stage stochastic mixed integer programs

    SciTech Connect

    Barnett, Jason; Watson, Jean -Paul; Woodruff, David L.

    2016-11-27

    Progressive hedging, though an effective heuristic for solving stochastic mixed integer programs (SMIPs), is not guaranteed to converge in this case. Here, we describe BBPH, a branch and bound algorithm that uses PH at each node in the search tree such that, given sufficient time, it will always converge to a globally optimal solution. Additionally, to providing a theoretically convergent “wrapper” for PH applied to SMIPs, computational results demonstrate that for some difficult problem instances branch and bound can find improved solutions after exploring only a few nodes.

  17. High-Speed Planning Method for Cooperative Logistics Networks using Mixed Integer Programming Model and Dummy Load

    NASA Astrophysics Data System (ADS)

    Onoyama, Takashi; Kubota, Sen; Maekawa, Takuya; Komoda, Norihisa

    Adequate response performance is required for the planning of a cooperative logistic network covering multiple enterprises, because this process needs a human expert's evaluation from many aspects. To satisfy this requirement, we propose an accurate model based on mixed integer programming for optimizing cooperative logistics networks where “round transportation” exists together with “depot transportation” including lower limit constraints of loading ratio for round transportation vehicles. Furthermore, to achieve interactive response performance, a dummy load is introduced into the model instead of integer variables. The experimental result shows the proposed method obtains an accurate solution within interactive response time.

  18. A Mixed Integer Linear Program for Solving a Multiple Route Taxi Scheduling Problem

    NASA Technical Reports Server (NTRS)

    Montoya, Justin Vincent; Wood, Zachary Paul; Rathinam, Sivakumar; Malik, Waqar Ahmad

    2010-01-01

    Aircraft movements on taxiways at busy airports often create bottlenecks. This paper introduces a mixed integer linear program to solve a Multiple Route Aircraft Taxi Scheduling Problem. The outputs of the model are in the form of optimal taxi schedules, which include routing decisions for taxiing aircraft. The model extends an existing single route formulation to include routing decisions. An efficient comparison framework compares the multi-route formulation and the single route formulation. The multi-route model is exercised for east side airport surface traffic at Dallas/Fort Worth International Airport to determine if any arrival taxi time savings can be achieved by allowing arrivals to have two taxi routes: a route that crosses an active departure runway and a perimeter route that avoids the crossing. Results indicate that the multi-route formulation yields reduced arrival taxi times over the single route formulation only when a perimeter taxiway is used. In conditions where the departure aircraft are given an optimal and fixed takeoff sequence, accumulative arrival taxi time savings in the multi-route formulation can be as high as 3.6 hours more than the single route formulation. If the departure sequence is not optimal, the multi-route formulation results in less taxi time savings made over the single route formulation, but the average arrival taxi time is significantly decreased.

  19. Robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming.

    PubMed

    Baran, Richard; Northen, Trent R

    2013-10-15

    Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.

  20. Estimating Tree-Structured Covariance Matrices via Mixed-Integer Programming.

    PubMed

    Bravo, Héctor Corrada; Wright, Stephen; Eng, Kevin H; Keles, Sündüz; Wahba, Grace

    2009-01-01

    We present a novel method for estimating tree-structured covariance matrices directly from observed continuous data. Specifically, we estimate a covariance matrix from observations of p continuous random variables encoding a stochastic process over a tree with p leaves. A representation of these classes of matrices as linear combinations of rank-one matrices indicating object partitions is used to formulate estimation as instances of well-studied numerical optimization problems.In particular, our estimates are based on projection, where the covariance estimate is the nearest tree-structured covariance matrix to an observed sample covariance matrix. The problem is posed as a linear or quadratic mixed-integer program (MIP) where a setting of the integer variables in the MIP specifies a set of tree topologies of the structured covariance matrix. We solve these problems to optimality using efficient and robust existing MIP solvers.We present a case study in phylogenetic analysis of gene expression and a simulation study comparing our method to distance-based tree estimating procedures.

  1. Distributed mixed-integer fuzzy hierarchical programming for municipal solid waste management. Part I: System identification and methodology development.

    PubMed

    Cheng, Guanhui; Huang, Guohe; Dong, Cong; Xu, Ye; Chen, Xiujuan; Chen, Jiapei

    2017-03-01

    Due to the existence of complexities of heterogeneities, hierarchy, discreteness, and interactions in municipal solid waste management (MSWM) systems such as Beijing, China, a series of socio-economic and eco-environmental problems may emerge or worsen and result in irredeemable damages in the following decades. Meanwhile, existing studies, especially ones focusing on MSWM in Beijing, could hardly reflect these complexities in system simulations and provide reliable decision support for management practices. Thus, a framework of distributed mixed-integer fuzzy hierarchical programming (DMIFHP) is developed in this study for MSWM under these complexities. Beijing is selected as a representative case. The Beijing MSWM system is comprehensively analyzed in many aspects such as socio-economic conditions, natural conditions, spatial heterogeneities, treatment facilities, and system complexities, building a solid foundation for system simulation and optimization. Correspondingly, the MSWM system in Beijing is discretized as 235 grids to reflect spatial heterogeneity. A DMIFHP model which is a nonlinear programming problem is constructed to parameterize the Beijing MSWM system. To enable scientific solving of it, a solution algorithm is proposed based on coupling of fuzzy programming and mixed-integer linear programming. Innovations and advantages of the DMIFHP framework are discussed. The optimal MSWM schemes and mechanism revelations will be discussed in another companion paper due to length limitation.

  2. An inexact two-stage mixed integer linear programming method for solid waste management in the City of Regina.

    PubMed

    Li, Y P; Huang, G H

    2006-11-01

    In this study, an interval-parameter two-stage mixed integer linear programming (ITMILP) model is developed for supporting long-term planning of waste management activities in the City of Regina. In the ITMILP, both two-stage stochastic programming and interval linear programming are introduced into a general mixed integer linear programming framework. Uncertainties expressed as not only probability density functions but also discrete intervals can be reflected. The model can help tackle the dynamic, interactive and uncertain characteristics of the solid waste management system in the City, and can address issues concerning plans for cost-effective waste diversion and landfill prolongation. Three scenarios are considered based on different waste management policies. The results indicate that reasonable solutions have been generated. They are valuable for supporting the adjustment or justification of the existing waste flow allocation patterns, the long-term capacity planning of the City's waste management system, and the formulation of local policies and regulations regarding waste generation and management.

  3. Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

    NASA Technical Reports Server (NTRS)

    Lee, Charles H.; Cheung, Kar-Ming

    2012-01-01

    In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.

  4. Solution of Mixed-Integer Programming Problems on the XT5

    SciTech Connect

    Hartman-Baker, Rebecca J; Busch, Ingrid Karin; Hilliard, Michael R; Middleton, Richard S; Schultze, Michael

    2009-01-01

    In this paper, we describe our experience with solving difficult mixed-integer linear programming problems (MILPs) on the petaflop Cray XT5 system at the National Center for Computational Sciences at Oak Ridge National Laboratory. We describe the algorithmic, software, and hardware needs for solving MILPs and present the results of using PICO, an open-source, parallel, mixed-integer linear programming solver developed at Sandia National Laboratories, to solve canonical MILPs as well as problems of interest arising from the logistics and supply chain management field.

  5. Interval-parameter semi-infinite fuzzy-stochastic mixed-integer programming approach for environmental management under multiple uncertainties

    SciTech Connect

    Guo, P.; Huang, G.H.

    2010-03-15

    In this study, an interval-parameter semi-infinite fuzzy-chance-constrained mixed-integer linear programming (ISIFCIP) approach is developed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing interval-parameter semi-infinite programming (ISIP) and fuzzy-chance-constrained programming (FCCP) by incorporating uncertainties expressed as dual uncertainties of functional intervals and multiple uncertainties of distributions with fuzzy-interval admissible probability of violating constraint within a general optimization framework. The binary-variable solutions represent the decisions of waste-management-facility expansion, and the continuous ones are related to decisions of waste-flow allocation. The interval solutions can help decision-makers to obtain multiple decision alternatives, as well as provide bases for further analyses of tradeoffs between waste-management cost and system-failure risk. In the application to the City of Regina, Canada, two scenarios are considered. In Scenario 1, the City's waste-management practices would be based on the existing policy over the next 25 years. The total diversion rate for the residential waste would be approximately 14%. Scenario 2 is associated with a policy for waste minimization and diversion, where 35% diversion of residential waste should be achieved within 15 years, and 50% diversion over 25 years. In this scenario, not only landfill would be expanded, but also CF and MRF would be expanded. Through the scenario analyses, useful decision support for the City's solid-waste managers and decision-makers has been generated. Three special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it is useful for tackling multiple uncertainties expressed as intervals, functional intervals, probability distributions, fuzzy sets, and their

  6. Large-scale bi-level strain design approaches and mixed-integer programming solution techniques.

    PubMed

    Kim, Joonhoon; Reed, Jennifer L; Maravelias, Christos T

    2011-01-01

    The use of computational models in metabolic engineering has been increasing as more genome-scale metabolic models and computational approaches become available. Various computational approaches have been developed to predict how genetic perturbations affect metabolic behavior at a systems level, and have been successfully used to engineer microbial strains with improved primary or secondary metabolite production. However, identification of metabolic engineering strategies involving a large number of perturbations is currently limited by computational resources due to the size of genome-scale models and the combinatorial nature of the problem. In this study, we present (i) two new bi-level strain design approaches using mixed-integer programming (MIP), and (ii) general solution techniques that improve the performance of MIP-based bi-level approaches. The first approach (SimOptStrain) simultaneously considers gene deletion and non-native reaction addition, while the second approach (BiMOMA) uses minimization of metabolic adjustment to predict knockout behavior in a MIP-based bi-level problem for the first time. Our general MIP solution techniques significantly reduced the CPU times needed to find optimal strategies when applied to an existing strain design approach (OptORF) (e.g., from ∼10 days to ∼5 minutes for metabolic engineering strategies with 4 gene deletions), and identified strategies for producing compounds where previous studies could not (e.g., malate and serine). Additionally, we found novel strategies using SimOptStrain with higher predicted production levels (for succinate and glycerol) than could have been found using an existing approach that considers network additions and deletions in sequential steps rather than simultaneously. Finally, using BiMOMA we found novel strategies involving large numbers of modifications (for pyruvate and glutamate), which sequential search and genetic algorithms were unable to find. The approaches and solution

  7. Mixed integer linear programming for maximum-parsimony phylogeny inference.

    PubMed

    Sridhar, Srinath; Lam, Fumei; Blelloch, Guy E; Ravi, R; Schwartz, Russell

    2008-01-01

    Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new advances in phylogeny inference will be required if we are to be able to continue to make effective use of the rapidly growing stores of variation data now being gathered. In this paper, we present two integer linear programming (ILP) formulations to find the most parsimonious phylogenetic tree from a set of binary variation data. One method uses a flow-based formulation that can produce exponential numbers of variables and constraints in the worst case. The method has, however, proven extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods, solving several large mtDNA and Y-chromosome instances within a few seconds and giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality. An alternative formulation establishes that the problem can be solved with a polynomial-sized ILP. We further present a web server developed based on the exponential-sized ILP that performs fast maximum parsimony inferences and serves as a front end to a database of precomputed phylogenies spanning the human genome.

  8. Obtaining lower bounds from the progressive hedging algorithm for stochastic mixed-integer programs

    DOE PAGES

    Gade, Dinakar; Hackebeil, Gabriel; Ryan, Sarah M.; ...

    2016-04-02

    We present a method for computing lower bounds in the progressive hedging algorithm (PHA) for two-stage and multi-stage stochastic mixed-integer programs. Computing lower bounds in the PHA allows one to assess the quality of the solutions generated by the algorithm contemporaneously. The lower bounds can be computed in any iteration of the algorithm by using dual prices that are calculated during execution of the standard PHA. In conclusion, we report computational results on stochastic unit commitment and stochastic server location problem instances, and explore the relationship between key PHA parameters and the quality of the resulting lower bounds.

  9. A two-level approach to large mixed-integer programs with application to cogeneration in energy-efficient buildings

    DOE PAGES

    Lin, Fu; Leyffer, Sven; Munson, Todd

    2016-04-12

    We study a two-stage mixed-integer linear program (MILP) with more than 1 million binary variables in the second stage. We develop a two-level approach by constructing a semi-coarse model that coarsens with respect to variables and a coarse model that coarsens with respect to both variables and constraints. We coarsen binary variables by selecting a small number of prespecified on/off profiles. We aggregate constraints by partitioning them into groups and taking convex combination over each group. With an appropriate choice of coarsened profiles, the semi-coarse model is guaranteed to find a feasible solution of the original problem and hence providesmore » an upper bound on the optimal solution. We show that solving a sequence of coarse models converges to the same upper bound with proven finite steps. This is achieved by adding violated constraints to coarse models until all constraints in the semi-coarse model are satisfied. We demonstrate the effectiveness of our approach in cogeneration for buildings. Here, the coarsened models allow us to obtain good approximate solutions at a fraction of the time required by solving the original problem. Extensive numerical experiments show that the two-level approach scales to large problems that are beyond the capacity of state-of-the-art commercial MILP solvers.« less

  10. A two-level approach to large mixed-integer programs with application to cogeneration in energy-efficient buildings

    SciTech Connect

    Lin, Fu; Leyffer, Sven; Munson, Todd

    2016-04-12

    We study a two-stage mixed-integer linear program (MILP) with more than 1 million binary variables in the second stage. We develop a two-level approach by constructing a semi-coarse model that coarsens with respect to variables and a coarse model that coarsens with respect to both variables and constraints. We coarsen binary variables by selecting a small number of prespecified on/off profiles. We aggregate constraints by partitioning them into groups and taking convex combination over each group. With an appropriate choice of coarsened profiles, the semi-coarse model is guaranteed to find a feasible solution of the original problem and hence provides an upper bound on the optimal solution. We show that solving a sequence of coarse models converges to the same upper bound with proven finite steps. This is achieved by adding violated constraints to coarse models until all constraints in the semi-coarse model are satisfied. We demonstrate the effectiveness of our approach in cogeneration for buildings. Here, the coarsened models allow us to obtain good approximate solutions at a fraction of the time required by solving the original problem. Extensive numerical experiments show that the two-level approach scales to large problems that are beyond the capacity of state-of-the-art commercial MILP solvers.

  11. Distributed mixed-integer fuzzy hierarchical programming for municipal solid waste management. Part II: scheme analysis and mechanism revelation.

    PubMed

    Cheng, Guanhui; Huang, Guohe; Dong, Cong; Xu, Ye; Chen, Jiapei; Chen, Xiujuan; Li, Kailong

    2017-02-16

    As presented in the first companion paper, distributed mixed-integer fuzzy hierarchical programming (DMIFHP) was developed for municipal solid waste management (MSWM) under complexities of heterogeneities, hierarchy, discreteness, and interactions. Beijing was selected as a representative case. This paper focuses on presenting the obtained schemes and the revealed mechanisms of the Beijing MSWM system. The optimal MSWM schemes for Beijing under various solid waste treatment policies and their differences are deliberated. The impacts of facility expansion, hierarchy, and spatial heterogeneities and potential extensions of DMIFHP are also discussed. A few of findings are revealed from the results and a series of comparisons and analyses. For instance, DMIFHP is capable of robustly reflecting these complexities in MSWM systems, especially for Beijing. The optimal MSWM schemes are of fragmented patterns due to the dominant role of the proximity principle in allocating solid waste treatment resources, and they are closely related to regulated ratios of landfilling, incineration, and composting. Communities without significant differences among distances to different types of treatment facilities are more sensitive to these ratios than others. The complexities of hierarchy and heterogeneities pose significant impacts on MSWM practices. Spatial dislocation of MSW generation rates and facility capacities caused by unreasonable planning in the past may result in insufficient utilization of treatment capacities under substantial influences of transportation costs. The problems of unreasonable MSWM planning, e.g., severe imbalance among different technologies and complete vacancy of ten facilities, should be gained deliberation of the public and the municipal or local governments in Beijing. These findings are helpful for gaining insights into MSWM systems under these complexities, mitigating key challenges in the planning of these systems, improving the related management

  12. COMSAT: Residue contact prediction of transmembrane proteins based on support vector machines and mixed integer linear programming.

    PubMed

    Zhang, Huiling; Huang, Qingsheng; Bei, Zhendong; Wei, Yanjie; Floudas, Christodoulos A

    2016-03-01

    In this article, we present COMSAT, a hybrid framework for residue contact prediction of transmembrane (TM) proteins, integrating a support vector machine (SVM) method and a mixed integer linear programming (MILP) method. COMSAT consists of two modules: COMSAT_SVM which is trained mainly on position-specific scoring matrix features, and COMSAT_MILP which is an ab initio method based on optimization models. Contacts predicted by the SVM model are ranked by SVM confidence scores, and a threshold is trained to improve the reliability of the predicted contacts. For TM proteins with no contacts above the threshold, COMSAT_MILP is used. The proposed hybrid contact prediction scheme was tested on two independent TM protein sets based on the contact definition of 14 Å between Cα-Cα atoms. First, using a rigorous leave-one-protein-out cross validation on the training set of 90 TM proteins, an accuracy of 66.8%, a coverage of 12.3%, a specificity of 99.3% and a Matthews' correlation coefficient (MCC) of 0.184 were obtained for residue pairs that are at least six amino acids apart. Second, when tested on a test set of 87 TM proteins, the proposed method showed a prediction accuracy of 64.5%, a coverage of 5.3%, a specificity of 99.4% and a MCC of 0.106. COMSAT shows satisfactory results when compared with 12 other state-of-the-art predictors, and is more robust in terms of prediction accuracy as the length and complexity of TM protein increase. COMSAT is freely accessible at http://hpcc.siat.ac.cn/COMSAT/.

  13. Mixed integer nonlinear programming model of wireless pricing scheme with QoS attribute of bandwidth and end-to-end delay

    NASA Astrophysics Data System (ADS)

    Irmeilyana, Puspita, Fitri Maya; Indrawati

    2016-02-01

    The pricing for wireless networks is developed by considering linearity factors, elasticity price and price factors. Mixed Integer Nonlinear Programming of wireless pricing model is proposed as the nonlinear programming problem that can be solved optimally using LINGO 13.0. The solutions are expected to give some information about the connections between the acceptance factor and the price. Previous model worked on the model that focuses on bandwidth as the QoS attribute. The models attempt to maximize the total price for a connection based on QoS parameter. The QoS attributes used will be the bandwidth and the end to end delay that affect the traffic. The maximum goal to maximum price is achieved when the provider determine the requirement for the increment or decrement of price change due to QoS change and amount of QoS value.

  14. A mixed integer bi-level DEA model for bank branch performance evaluation by Stackelberg approach

    NASA Astrophysics Data System (ADS)

    Shafiee, Morteza; Lotfi, Farhad Hosseinzadeh; Saleh, Hilda; Ghaderi, Mehdi

    2016-11-01

    One of the most complicated decision making problems for managers is the evaluation of bank performance, which involves various criteria. There are many studies about bank efficiency evaluation by network DEA in the literature review. These studies do not focus on multi-level network. Wu (Eur J Oper Res 207:856-864, 2010) proposed a bi-level structure for cost efficiency at the first time. In this model, multi-level programming and cost efficiency were used. He used a nonlinear programming to solve the model. In this paper, we have focused on multi-level structure and proposed a bi-level DEA model. We then used a liner programming to solve our model. In other hand, we significantly improved the way to achieve the optimum solution in comparison with the work by Wu (2010) by converting the NP-hard nonlinear programing into a mixed integer linear programming. This study uses a bi-level programming data envelopment analysis model that embodies internal structure with Stackelberg-game relationships to evaluate the performance of banking chain. The perspective of decentralized decisions is taken in this paper to cope with complex interactions in banking chain. The results derived from bi-level programming DEA can provide valuable insights and detailed information for managers to help them evaluate the performance of the banking chain as a whole using Stackelberg-game relationships. Finally, this model was applied in the Iranian bank to evaluate cost efficiency.

  15. Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

    PubMed

    Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer

    2016-06-02

    Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments.

  16. Mixed-integer programming methods for transportation and power generation problems

    NASA Astrophysics Data System (ADS)

    Damci Kurt, Pelin

    This dissertation conducts theoretical and computational research to solve challenging problems in application areas such as supply chain and power systems. The first part of the dissertation studies a transportation problem with market choice (TPMC) which is a variant of the classical transportation problem in which suppliers with limited capacities have a choice of which demands (markets) to satisfy. We show that TPMC is strongly NP-complete. We consider a version of the problem with a service level constraint on the maximum number of markets that can be rejected and show that if the original problem is polynomial, its cardinality-constrained version is also polynomial. We propose valid inequalities for mixed-integer cover and knapsack sets with variable upper bound constraints, which appear as substructures of TPMC and use them in a branch-and-cut algorithm to solve this problem. The second part of this dissertation studies a unit commitment (UC) problem in which the goal is to minimize the operational cost of power generators over a time period subject to physical constraints while satisfying demand. We provide several exponential classes of multi-period ramping and multi-period variable upper bound inequalities. We prove the strength of these inequalities and describe polynomial-time separation algorithms. Computational results show the effectiveness of the proposed inequalities when used as cuts in a branch-and-cut algorithm to solve the UC problem. The last part of this dissertation investigates the effects of uncertain wind power on the UC problem. A two-stage robust model and a three-stage stochastic program are compared.

  17. Optimally Managing Dynamic Military Server-to-Customer Systems

    DTIC Science & Technology

    2014-08-07

    Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 discrete optimization, Markov decision processes , networks, MEDEVACS...integer programming model for enforcing priority list policies in Markov decision process models, (01 2011) Laura A. McLay, Maria E. Mayorga. A...mixed-integer programming model for enforcing priority list policies in a Markov decision process model, ( ) TOTAL: 3 Received Book TOTAL: Received

  18. Multi-objective Mixed Integer Programming approach for facility layout design by considering closeness ratings, material handling, and re-layout cost

    NASA Astrophysics Data System (ADS)

    Purnomo, Muhammad Ridwan Andi; Satrio Wiwoho, Yoga

    2016-01-01

    Facility layout becomes one of production system factor that should be managed well, as it is designated for the location of production. In managing the layout, designing the layout by considering the optimal layout condition that supports the work condition is essential. One of the method for facility layout optimization is Mixed Integer Programming (MIP). In this study, the MIP is solved using Lingo 9.0 software and considering quantitative and qualitative objectives to be achieved simultaneously: minimizing material handling cost, maximizing closeness rating, and minimizing re-layout cost. The research took place in Rekayasa Wangdi as a make to order company, focusing on the making of concrete brick dough stirring machine with 10 departments involved. The result shows an improvement in the new layout for 333,72 points of objective value compared with the initial layout. As the conclusion, the proposed MIP is proven to be used to model facility layout problem under multi objective consideration for a more realistic look.

  19. Optimal dynamic management of groundwater pollutant sources

    SciTech Connect

    Gorelick, S.M.; Remson, I.

    1982-02-01

    The linear programming-superposition method is presented for managing multiple sources of groundwater pollution over time. The method uses any linear solute transport simulation model to generate a unit source-concentration response matrix that is incorporated into a management model. This series of constraints indicates local solute concentration histories that will result from any series of waste injection schedules. The linear program operates on the matrix to arrive at optimal disposal schedules. An example demonstrates application of the method to maximizing groundwater waste disposal while maintaining water quality of local water supplies within desired limits. Flow field variation associated with waste injection are ignored as an approximation. Parametric programming is shown to be an important tool in evaluating waste disposal trade-offs at various injection sites over time. Mixed-integer programming permits restrictions to be placed upon the number of injection wells which may operate during given management periods.

  20. A novel mixed integer programming for multi-biomarker panel identification by distinguishing malignant from benign colorectal tumors.

    PubMed

    Zou, Meng; Zhang, Peng-Jun; Wen, Xin-Yu; Chen, Luonan; Tian, Ya-Ping; Wang, Yong

    2015-07-15

    Multi-biomarker panels can capture the nonlinear synergy among biomarkers and they are important to aid in the early diagnosis and ultimately battle complex diseases. However, identification of these multi-biomarker panels from case and control data is challenging. For example, the exhaustive search method is computationally infeasible when the data dimension is high. Here, we propose a novel method, MILP_k, to identify serum-based multi-biomarker panel to distinguish colorectal cancers (CRC) from benign colorectal tumors. Specifically, the multi-biomarker panel detection problem is modeled by a mixed integer programming to maximize the classification accuracy. Then we measured the serum profiling data for 101 CRC patients and 95 benign patients. The 61 biomarkers were analyzed individually and further their combinations by our method. We discovered 4 biomarkers as the optimal small multi-biomarker panel, including known CRC biomarkers CEA and IL-10 as well as novel biomarkers IMA and NSE. This multi-biomarker panel obtains leave-one-out cross-validation (LOOCV) accuracy to 0.7857 by nearest centroid classifier. An independent test of this panel by support vector machine (SVM) with threefold cross validation gets an AUC 0.8438. This greatly improves the predictive accuracy by 20% over the single best biomarker. Further extension of this 4-biomarker panel to a larger 13-biomarker panel improves the LOOCV to 0.8673 with independent AUC 0.8437. Comparison with the exhaustive search method shows that our method dramatically reduces the searching time by 1000-fold. Experiments on the early cancer stage samples reveal two panel of biomarkers and show promising accuracy. The proposed method allows us to select the subset of biomarkers with best accuracy to distinguish case and control samples given the number of selected biomarkers. Both receiver operating characteristic curve and precision-recall curve show our method's consistent performance gain in accuracy. Our method

  1. A two-stage mixed-integer fuzzy programming with interval-valued membership functions approach for flood-diversion planning.

    PubMed

    Wang, S; Huang, G H

    2013-03-15

    Flood disasters have been extremely severe in recent decades, and they account for about one third of all natural catastrophes throughout the world. In this study, a two-stage mixed-integer fuzzy programming with interval-valued membership functions (TMFP-IMF) approach is developed for flood-diversion planning under uncertainty. TMFP-IMF integrates the fuzzy flexible programming, two-stage stochastic programming, and integer programming within a general framework. A concept of interval-valued fuzzy membership function is introduced to address complexities of system uncertainties. TMFP-IMF can not only deal with uncertainties expressed as fuzzy sets and probability distributions, but also incorporate pre-regulated water-diversion policies directly into its optimization process. TMFP-IMF is applied to a hypothetical case study of flood-diversion planning for demonstrating its applicability. Results indicate that reasonable solutions can be generated for binary and continuous variables. A variety of flood-diversion and capacity-expansion schemes can be obtained under four scenarios, which enable decision makers (DMs) to identify the most desired one based on their perceptions and attitudes towards the objective-function value and constraints.

  2. Final Report---Optimization Under Nonconvexity and Uncertainty: Algorithms and Software

    SciTech Connect

    Jeff Linderoth

    2011-11-06

    the goal of this work was to develop new algorithmic techniques for solving large-scale numerical optimization problems, focusing on problems classes that have proven to be among the most challenging for practitioners: those involving uncertainty and those involving nonconvexity. This research advanced the state-of-the-art in solving mixed integer linear programs containing symmetry, mixed integer nonlinear programs, and stochastic optimization problems. The focus of the work done in the continuation was on Mixed Integer Nonlinear Programs (MINLP)s and Mixed Integer Linear Programs (MILP)s, especially those containing a great deal of symmetry.

  3. A solution procedure for mixed-integer nonlinear programming formulation of supply chain planning with quantity discounts under demand uncertainty

    NASA Astrophysics Data System (ADS)

    Yin, Sisi; Nishi, Tatsushi

    2014-11-01

    Quantity discount policy is decision-making for trade-off prices between suppliers and manufacturers while production is changeable due to demand fluctuations in a real market. In this paper, quantity discount models which consider selection of contract suppliers, production quantity and inventory simultaneously are addressed. The supply chain planning problem with quantity discounts under demand uncertainty is formulated as a mixed-integer nonlinear programming problem (MINLP) with integral terms. We apply an outer-approximation method to solve MINLP problems. In order to improve the efficiency of the proposed method, the problem is reformulated as a stochastic model replacing the integral terms by using a normalisation technique. We present numerical examples to demonstrate the efficiency of the proposed method.

  4. A Mixed Integer Programming Model for Improving Theater Distribution Force Flow Analysis

    DTIC Science & Technology

    2013-03-01

    the introduction to LINGO in OPER 510. Next, I wish to thank LINDO Systems, particularly Kevin Cunningham, for software assistance with LINGO . I...viii Appendix A. LINGO 13 Settings File Contents .............................................................. 79 Appendix B. Additional Model...optimization software LINGO 13 (Lindo Systems Inc, 2012). A Decision Support System was built in the Excel environment where the user uploads a

  5. Greenhouse gas emissions control in integrated municipal solid waste management through mixed integer bilevel decision-making.

    PubMed

    He, Li; Huang, G H; Lu, Hongwei

    2011-10-15

    Recent studies indicated that municipal solid waste (MSW) is a major contributor to global warming due to extensive emissions of greenhouse gases (GHGs). However, most of them focused on investigating impacts of MSW on GHG emission amounts. This study presents two mixed integer bilevel decision-making models for integrated municipal solid waste management and GHG emissions control: MGU-MCL and MCU-MGL. The MGU-MCL model represents a top-down decision process, with the environmental sectors at the national level dominating the upper-level objective and the waste management sectors at the municipal level providing the lower-level objective. The MCU-MGL model implies a bottom-up decision process where municipality plays a leading role. Results from the models indicate that: the top-down decisions would reduce metric tonne carbon emissions (MTCEs) by about 59% yet increase about 8% of the total management cost; the bottom-up decisions would reduce MTCE emissions by about 13% but increase the total management cost very slightly; on-site monitoring and downscaled laboratory experiments are still required for reducing uncertainty in GHG emission rate from the landfill facility.

  6. Optimization by record dynamics

    NASA Astrophysics Data System (ADS)

    Barettin, Daniele; Sibani, Paolo

    2014-03-01

    Large dynamical changes in thermalizing glassy systems are triggered by trajectories crossing record sized barriers, a behavior revealing the presence of a hierarchical structure in configuration space. The observation is here turned into a novel local search optimization algorithm dubbed record dynamics optimization, or RDO. RDO uses the Metropolis rule to accept or reject candidate solutions depending on the value of a parameter akin to the temperature and minimizes the cost function of the problem at hand through cycles where its ‘temperature’ is raised and subsequently decreased in order to expediently generate record high (and low) values of the cost function. Below, RDO is introduced and then tested by searching for the ground state of the Edwards-Anderson spin-glass model, in two and three spatial dimensions. A popular and highly efficient optimization algorithm, parallel tempering (PT), is applied to the same problem as a benchmark. RDO and PT turn out to produce solutions of similar quality for similar numerical effort, but RDO is simpler to program and additionally yields geometrical information on the system’s configuration space which is of interest in many applications. In particular, the effectiveness of RDO strongly indicates the presence of the above mentioned hierarchically organized configuration space, with metastable regions indexed by the cost (or energy) of the transition states connecting them.

  7. Robust optimization of a mathematical model to design a dynamic cell formation problem considering labor utilization

    NASA Astrophysics Data System (ADS)

    Vafaeinezhad, Moghadaseh; Kia, Reza; Shahnazari-Shahrezaei, Parisa

    2016-11-01

    Cell formation (CF) problem is one of the most important decision problems in designing a cellular manufacturing system includes grouping machines into machine cells and parts into part families. Several factors should be considered in a cell formation problem. In this work, robust optimization of a mathematical model of a dynamic cell formation problem integrating CF, production planning and worker assignment is implemented with uncertain scenario-based data. The robust approach is used to reduce the effects of fluctuations of the uncertain parameters with regards to all possible future scenarios. In this research, miscellaneous cost parameters of the cell formation and demand fluctuations are subject to uncertainty and a mixed-integer nonlinear programming model is developed to formulate the related robust dynamic cell formation problem. The objective function seeks to minimize total costs including machine constant, machine procurement, machine relocation, machine operation, inter-cell and intra-cell movement, overtime, shifting labors between cells and inventory holding. Finally, a case study is carried out to display the robustness and effectiveness of the proposed model. The tradeoff between solution robustness and model robustness is also analyzed in the obtained results.

  8. Optimized dynamic rotation with wedges.

    PubMed

    Rosen, I I; Morrill, S M; Lane, R G

    1992-01-01

    Dynamic rotation is a computer-controlled therapy technique utilizing an automated multileaf collimator in which the radiation beam shape changes dynamically as the treatment machine rotates about the patient so that at each instant the beam shape matches the projected shape of the target volume. In simple dynamic rotation, the dose rate remains constant during rotation. For optimized dynamic rotation, the dose rate is varied as a function of gantry angle. Optimum dose rate at each gantry angle is computed by linear programming. Wedges can be included in the optimized dynamic rotation therapy by using additional rotations. Simple and optimized dynamic rotation treatment plans, with and without wedges, for a pancreatic tumor have been compared using optimization cost function values, normal tissue complication probabilities, and positive difference statistic values. For planning purposes, a continuous rotation is approximated by static beams at a number of gantry angles equally spaced about the patient. In theory, the quality of optimized treatment planning solutions should improve as the number of static beams increases. The addition of wedges should further improve dose distributions. For the case studied, no significant improvements were seen for more than 36 beam angles. Open and wedged optimized dynamic rotations were better than simple dynamic rotation, but wedged optimized dynamic rotation showed no definitive improvement over open beam optimized dynamic rotation.

  9. Deterministic global optimization algorithm based on outer approximation for the parameter estimation of nonlinear dynamic biological systems

    PubMed Central

    2012-01-01

    Background The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved. One major difficulty is the existence of multiple minima in which standard optimization methods may fall during the search. Deterministic global optimization methods overcome this limitation, ensuring convergence to the global optimum within a desired tolerance. Global optimization techniques are usually classified into stochastic and deterministic. The former typically lead to lower CPU times but offer no guarantee of convergence to the global minimum in a finite number of iterations. In contrast, deterministic methods provide solutions of a given quality (i.e., optimality gap), but tend to lead to large computational burdens. Results This work presents a deterministic outer approximation-based algorithm for the global optimization of dynamic problems arising in the parameter estimation of models of biological systems. Our approach, which offers a theoretical guarantee of convergence to global minimum, is based on reformulating the set of ordinary differential equations into an equivalent set of algebraic equations through the use of orthogonal collocation methods, giving rise to a nonconvex nonlinear programming (NLP) problem. This nonconvex NLP is decomposed into two hierarchical levels: a master mixed-integer linear programming problem (MILP) that provides a rigorous lower bound on the optimal solution, and a reduced-space slave NLP that yields an upper bound. The algorithm iterates between these two levels until a termination criterion is satisfied. Conclusion The capabilities of our approach were tested in two benchmark problems, in which the performance of our algorithm was compared with that of the commercial global optimization package BARON. The proposed strategy produced near optimal solutions (i.e., within a desired tolerance) in a fraction of the CPU time required by

  10. An inexact dynamic optimization model for municipal solid waste management in association with greenhouse gas emission control.

    PubMed

    Lu, H W; Huang, G H; He, L; Zeng, G M

    2009-01-01

    Municipal solid waste (MSW) should be properly disposed in order to help protect environmental quality and human health, as well as to preserve natural resources. During MSW disposal processes, a large amount of greenhouse gas (GHG) is emitted, leading to a significant impact on climate change. In this study, an inexact dynamic optimization model (IDOM) is developed for MSW-management systems under uncertainty. It grounds upon conventional mixed-integer linear programming (MILP) approaches, and integrates GHG components into the modeling framework. Compared with the existing models, IDOM can not only deal with the complex tradeoff between system cost minimization and GHG-emission mitigation, but also provide optimal allocation strategies under various emission-control standards. A case study is then provided for demonstrating applicability of the developed model. The results indicate that desired waste-flow patterns with a minimized system cost and GHG-emission amount can be obtained. Of more importance, the IDOM solution is associated with over 5.5 million tonnes of TEC reduction, which is of significant economic implication for real implementations. Therefore, the proposed model could be regarded as a useful tool for realizing comprehensive MSW management with regard to mitigating climate-change impacts.

  11. Optimal Constellation Design for Maximum Continuous Coverage of Targets Against a Space Background

    DTIC Science & Technology

    2012-05-31

    numerical process. To further demonstrate the integration of the numerical coverage calculation with an on-line optimization process, a Mixed Integer ...region itself, a time-invariant solution is optimal , as is demonstrated in this example. The problem is posed as a Mixed- Integer Non-Linear Programming ...operations between the reference surfaces in the constellation. The methodology is integrated with various optimization methods to demonstrate the 2

  12. Comparison of two non-convex mixed-integer nonlinear programming algorithms applied to autoregressive moving average model structure and parameter estimation

    NASA Astrophysics Data System (ADS)

    Uilhoorn, F. E.

    2016-10-01

    In this article, the stochastic modelling approach proposed by Box and Jenkins is treated as a mixed-integer nonlinear programming (MINLP) problem solved with a mesh adaptive direct search and a real-coded genetic class of algorithms. The aim is to estimate the real-valued parameters and non-negative integer, correlated structure of stationary autoregressive moving average (ARMA) processes. The maximum likelihood function of the stationary ARMA process is embedded in Akaike's information criterion and the Bayesian information criterion, whereas the estimation procedure is based on Kalman filter recursions. The constraints imposed on the objective function enforce stability and invertibility. The best ARMA model is regarded as the global minimum of the non-convex MINLP problem. The robustness and computational performance of the MINLP solvers are compared with brute-force enumeration. Numerical experiments are done for existing time series and one new data set.

  13. Optimal dynamic detection of explosives

    SciTech Connect

    Moore, David Steven; Mcgrane, Shawn D; Greenfield, Margo T; Scharff, R J; Rabitz, Herschel A; Roslund, J

    2009-01-01

    The detection of explosives is a notoriously difficult problem, especially at stand-off distances, due to their (generally) low vapor pressure, environmental and matrix interferences, and packaging. We are exploring optimal dynamic detection to exploit the best capabilities of recent advances in laser technology and recent discoveries in optimal shaping of laser pulses for control of molecular processes to significantly enhance the standoff detection of explosives. The core of the ODD-Ex technique is the introduction of optimally shaped laser pulses to simultaneously enhance sensitivity of explosives signatures while reducing the influence of noise and the signals from background interferents in the field (increase selectivity). These goals are being addressed by operating in an optimal nonlinear fashion, typically with a single shaped laser pulse inherently containing within it coherently locked control and probe sub-pulses. With sufficient bandwidth, the technique is capable of intrinsically providing orthogonal broad spectral information for data fusion, all from a single optimal pulse.

  14. New numerical methods for open-loop and feedback solutions to dynamic optimization problems

    NASA Astrophysics Data System (ADS)

    Ghosh, Pradipto

    The topic of the first part of this research is trajectory optimization of dynamical systems via computational swarm intelligence. Particle swarm optimization is a nature-inspired heuristic search method that relies on a group of potential solutions to explore the fitness landscape. Conceptually, each particle in the swarm uses its own memory as well as the knowledge accumulated by the entire swarm to iteratively converge on an optimal or near-optimal solution. It is relatively straightforward to implement and unlike gradient-based solvers, does not require an initial guess or continuity in the problem definition. Although particle swarm optimization has been successfully employed in solving static optimization problems, its application in dynamic optimization, as posed in optimal control theory, is still relatively new. In the first half of this thesis particle swarm optimization is used to generate near-optimal solutions to several nontrivial trajectory optimization problems including thrust programming for minimum fuel, multi-burn spacecraft orbit transfer, and computing minimum-time rest-to-rest trajectories for a robotic manipulator. A distinct feature of the particle swarm optimization implementation in this work is the runtime selection of the optimal solution structure. Optimal trajectories are generated by solving instances of constrained nonlinear mixed-integer programming problems with the swarming technique. For each solved optimal programming problem, the particle swarm optimization result is compared with a nearly exact solution found via a direct method using nonlinear programming. Numerical experiments indicate that swarm search can locate solutions to very great accuracy. The second half of this research develops a new extremal-field approach for synthesizing nearly optimal feedback controllers for optimal control and two-player pursuit-evasion games described by general nonlinear differential equations. A notable revelation from this development

  15. Improving the Performance of a Mixed-Integer Production Scheduling Model for LKAB’s Iron Ore Mine, Kiruna, Sweden

    DTIC Science & Technology

    2006-05-01

    on a Sunblade 1000 computer with 1 GB RAM, while also conducting additional runs calculating lower bounds on a Beowulf Parallel Cluster with 96...problem instances, allowing us to reduce the optimality gap, as shown in third column of the table. We perform these lengthy runs on a Beowulf

  16. Automated Design Framework for Synthetic Biology Exploiting Pareto Optimality.

    PubMed

    Otero-Muras, Irene; Banga, Julio R

    2017-04-12

    In this work we consider Pareto optimality for automated design in synthetic biology. We present a generalized framework based on a mixed-integer dynamic optimization formulation that, given design specifications, allows the computation of Pareto optimal sets of designs, that is, the set of best trade-offs for the metrics of interest. We show how this framework can be used for (i) forward design, that is, finding the Pareto optimal set of synthetic designs for implementation, and (ii) reverse design, that is, analyzing and inferring motifs and/or design principles of gene regulatory networks from the Pareto set of optimal circuits. Finally, we illustrate the capabilities and performance of this framework considering four case studies. In the first problem we consider the forward design of an oscillator. In the remaining problems, we illustrate how to apply the reverse design approach to find motifs for stripe formation, rapid adaption, and fold-change detection, respectively.

  17. A method for nonlinear optimization with discrete design variables

    NASA Technical Reports Server (NTRS)

    Olsen, Gregory R.; Vanderplaats, Garret N.

    1987-01-01

    A numerical method is presented for the solution of nonlinear discrete optimization problems. The applicability of discrete optimization to engineering design is discussed, and several standard structural optimization problems are solved using discrete design variables. The method uses approximation techniques to create subproblems suitable for linear mixed-integer programming methods. The method employs existing software for continuous optimization and integer programming.

  18. Optimal temporal patterns for dynamical cellular signaling

    NASA Astrophysics Data System (ADS)

    Hasegawa, Yoshihiko

    2016-11-01

    Cells use temporal dynamical patterns to transmit information via signaling pathways. As optimality with respect to the environment plays a fundamental role in biological systems, organisms have evolved optimal ways to transmit information. Here, we use optimal control theory to obtain the dynamical signal patterns for the optimal transmission of information, in terms of efficiency (low energy) and reliability (low uncertainty). Adopting an activation-deactivation decoding network, we reproduce several dynamical patterns found in actual signals, such as steep, gradual, and overshooting dynamics. Notably, when minimizing the energy of the input signal, the optimal signals exhibit overshooting, which is a biphasic pattern with transient and steady phases; this pattern is prevalent in actual dynamical patterns. We also identify conditions in which these three patterns (steep, gradual, and overshooting) confer advantages. Our study shows that cellular signal transduction is governed by the principle of minimizing free energy dissipation and uncertainty; these constraints serve as selective pressures when designing dynamical signaling patterns.

  19. PILOT_PROTEIN: Identification of unmodified and modified proteins via high-resolution mass spectrometry and mixed-integer linear optimization

    PubMed Central

    Baliban, Richard C.; DiMaggio, Peter A.; Plazas-Mayorca, Mariana D.; Garcia, Benjamin A.; Floudas, Christodoulos A.

    2012-01-01

    A novel protein identification framework, PILOT_PROTEIN, has been developed to construct a comprehensive list of all unmodified proteins that are present in a living sample. It uses the peptide identification results from the PILOT_SEQUEL algorithm to initially determine all unmodified proteins within the sample. Using a rigorous biclustering approach that groups incorrect peptide sequences with other homologous sequences, the number of false positives reported is minimized. A sequence tag procedure is then incorporated along with the untargeted PTM identification algorithm, PILOT_PTM, to determine a list of all modification types and sites for each protein. The unmodified protein identification algorithm, PILOT_PROTEIN, is compared to the methods SEQUEST, InsPecT, X!Tandem, VEMS, and ProteinProspector using both prepared protein samples and a more complex chromatin digest. The algorithm demonstrates superior protein identification accuracy with a lower false positive rate. All materials are freely available to the scientific community at http://pumpd.princeton.edu. PMID:22788846

  20. TRACKING CODE DEVELOPMENT FOR BEAM DYNAMICS OPTIMIZATION

    SciTech Connect

    Yang, L.

    2011-03-28

    Dynamic aperture (DA) optimization with direct particle tracking is a straight forward approach when the computing power is permitted. It can have various realistic errors included and is more close than theoretical estimations. In this approach, a fast and parallel tracking code could be very helpful. In this presentation, we describe an implementation of storage ring particle tracking code TESLA for beam dynamics optimization. It supports MPI based parallel computing and is robust as DA calculation engine. This code has been used in the NSLS-II dynamics optimizations and obtained promising performance.

  1. Semiclassical guided optimal control of molecular dynamics

    SciTech Connect

    Kondorskiy, A.; Mil'nikov, G.; Nakamura, H.

    2005-10-15

    An efficient semiclassical optimal control theory applicable to multidimensional systems is formulated for controlling wave packet dynamics on a single adiabatic potential energy surface. The approach combines advantages of different formulations of optimal control theory: quantum and classical on one hand and global and local on the other. Numerical applications to the control of HCN-CNH isomerization demonstrate that this theory can provide an efficient tool to manipulate molecular dynamics of many degrees of freedom by laser pulses.

  2. Two Characterizations of Optimality in Dynamic Programming

    SciTech Connect

    Karatzas, Ioannis; Sudderth, William D.

    2010-06-15

    It holds in great generality that a plan is optimal for a dynamic programming problem, if and only if it is 'thrifty' and 'equalizing.' An alternative characterization of an optimal plan, that applies in many economic models, is that the plan must satisfy an appropriate Euler equation and a transversality condition. Here we explore the connections between these two characterizations.

  3. Streak camera dynamic range optimization

    SciTech Connect

    Wiedwald, J.D.; Lerche, R.A.

    1987-09-01

    The LLNL optical streak camera is used by the Laser Fusion Program in a wide range of applications. Many of these applications require a large recorded dynamic range. Recent work has focused on maximizing the dynamic range of the streak camera recording system. For our streak cameras, image intensifier saturation limits the upper end of the dynamic range. We have developed procedures to set the image intensifier gain such that the system dynamic range is maximized. Specifically, the gain is set such that a single streak tube photoelectron is recorded with an exposure of about five times the recording system noise. This ensures detection of single photoelectrons, while not consuming intensifier or recording system dynamic range through excessive intensifier gain. The optimum intensifier gain has been determined for two types of film and for a lens-coupled CCD camera. We have determined that by recording the streak camera image with a CCD camera, the system is shot-noise limited up to the onset of image intensifier nonlinearity. When recording on film, the film determines the noise at high exposure levels. There is discussion of the effects of slit width and image intensifier saturation on dynamic range. 8 refs.

  4. Near-optimal sensor placement for health monitoring of civil structures

    NASA Astrophysics Data System (ADS)

    van der Linden, Gwendolyn W.; Emami-Naeini, Abbas; Kosut, Robert L.; Sederat, Hassan; Lynch, Jerome P.

    2010-04-01

    In this paper we focus on the optimal placement of sensors for state estimation-based continuous health monitoring of structures using three approaches. The first aims to minimize the static estimation error of the structure deflections, using the linear stiffness matrix derived from a finite element model. The second approach aims to maximize the observability of the derived linear state space model. The third approach aims to minimize the dynamic estimation error of the deflections using a Linear Quadratic Estimator. Both nonlinear mixed-integer and relaxed convex optimization formulations are presented. A simple search-based optimization implementation for each of the three approaches is demonstrated on a model of the long-span New Carquinez Bridge in California.

  5. Dynamic optimization and adaptive controller design

    NASA Astrophysics Data System (ADS)

    Inamdar, S. R.

    2010-10-01

    In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

  6. Optimizing Dynamical Network Structure for Pinning Control

    NASA Astrophysics Data System (ADS)

    Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo

    2016-04-01

    Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights.

  7. Efficient dynamic optimization of logic programs

    NASA Technical Reports Server (NTRS)

    Laird, Phil

    1992-01-01

    A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.

  8. Dynamic optimization case studies in DYNOPT tool

    NASA Astrophysics Data System (ADS)

    Ozana, Stepan; Pies, Martin; Docekal, Tomas

    2016-06-01

    Dynamic programming is typically applied to optimization problems. As the analytical solutions are generally very difficult, chosen software tools are used widely. These software packages are often third-party products bound for standard simulation software tools on the market. As typical examples of such tools, TOMLAB and DYNOPT could be effectively applied for solution of problems of dynamic programming. DYNOPT will be presented in this paper due to its licensing policy (free product under GPL) and simplicity of use. DYNOPT is a set of MATLAB functions for determination of optimal control trajectory by given description of the process, the cost to be minimized, subject to equality and inequality constraints, using orthogonal collocation on finite elements method. The actual optimal control problem is solved by complete parameterization both the control and the state profile vector. It is assumed, that the optimized dynamic model may be described by a set of ordinary differential equations (ODEs) or differential-algebraic equations (DAEs). This collection of functions extends the capability of the MATLAB Optimization Tool-box. The paper will introduce use of DYNOPT in the field of dynamic optimization problems by means of case studies regarding chosen laboratory physical educational models.

  9. Managing time-substitutable electricity usage using dynamic controls

    DOEpatents

    Ghosh, Soumyadip; Hosking, Jonathan R.; Natarajan, Ramesh; Subramaniam, Shivaram; Zhang, Xiaoxuan

    2017-02-21

    A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives.

  10. Managing time-substitutable electricity usage using dynamic controls

    DOEpatents

    Ghosh, Soumyadip; Hosking, Jonathan R.; Natarajan, Ramesh; Subramaniam, Shivaram; Zhang, Xiaoxuan

    2017-02-07

    A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives.

  11. Optimization-based Dynamic Human Lifting Prediction

    DTIC Science & Technology

    2008-06-01

    Anith Mathai, Steve Beck,Timothy Marler , Jingzhou Yang, Jasbir S. Arora, Karim Abdel-Malek Virtual Soldier Research Program, Center for Computer Aided...Rahmatalla, S., Kim, J., Marler , T., Beck, S., Yang, J., busek, J., Arora, J.S., and Abdel-Malek, K. Optimization-based dynamic human walking prediction

  12. Optimized dynamical decoupling via genetic algorithms

    NASA Astrophysics Data System (ADS)

    Quiroz, Gregory; Lidar, Daniel A.

    2013-11-01

    We utilize genetic algorithms aided by simulated annealing to find optimal dynamical decoupling (DD) sequences for a single-qubit system subjected to a general decoherence model under a variety of control pulse conditions. We focus on the case of sequences with equal pulse intervals and perform the optimization with respect to pulse type and order. In this manner, we obtain robust DD sequences, first in the limit of ideal pulses, then when including pulse imperfections such as finite-pulse duration and qubit rotation (flip-angle) errors. Although our optimization is numerical, we identify a deterministic structure that underlies the top-performing sequences. We use this structure to devise DD sequences which outperform previously designed concatenated DD (CDD) and quadratic DD (QDD) sequences in the presence of pulse errors. We explain our findings using time-dependent perturbation theory and provide a detailed scaling analysis of the optimal sequences.

  13. Optimal BLS: Optimizing transit-signal detection for Keplerian dynamics

    NASA Astrophysics Data System (ADS)

    Ofir, Aviv

    2015-08-01

    Transit surveys, both ground- and space-based, have already accumulated a large number of light curves that span several years. We optimize the search for transit signals for both detection and computational efficiencies by assuming that the searched systems can be described by Keplerian, and propagating the effects of different system parameters to the detection parameters. Importnantly, we mainly consider the information content of the transit signal and not any specific algorithm - and use BLS (Kovács, Zucker, & Mazeh 2002) just as a specific example.We show that the frequency information content of the light curve is primarily determined by the duty cycle of the transit signal, and thus the optimal frequency sampling is found to be cubic and not linear. Further optimization is achieved by considering duty-cycle dependent binning of the phased light curve. By using the (standard) BLS, one is either fairly insensitive to long-period planets or less sensitive to short-period planets and computationally slower by a significant factor of ~330 (for a 3 yr long dataset). We also show how the physical system parameters, such as the host star's size and mass, directly affect transit detection. This understanding can then be used to optimize the search for every star individually.By considering Keplerian dynamics explicitly rather than implicitly one can optimally search the transit signal parameter space. The presented Optimal BLS enhances the detectability of both very short and very long period planets, while allowing such searches to be done with much reduced resources and time. The Matlab/Octave source code for Optimal BLS is made available.

  14. Common Aero Vehicle Autonomous Reentry Trajectory Optimization Satisfying Waypoint and No-Fly Zone Constraints

    DTIC Science & Technology

    2007-09-01

    used to converge to the optimal solution. This numerical approach is applied to the Common Aero Vehicle (CAV) as the test platform for the full three...6 EAGLE Evolved Acceleration Guidance Logic for Entry . . . . . . 10 POSTII Program To Optimize Simulated Trajectories II...11 LQR linear quadratic regulator . . . . . . . . . . . . . . . . . . 12 MILP Mixed- Integer Linear Programming

  15. Optimizing Motion Planning for Hyper Dynamic Manipulator

    NASA Astrophysics Data System (ADS)

    Aboura, Souhila; Omari, Abdelhafid; Meguenni, Kadda Zemalache

    2012-01-01

    This paper investigates the optimal motion planning for an hyper dynamic manipulator. As case study, we consider a golf swing robot which is consisting with two actuated joint and a mechanical stoppers. Genetic Algorithm (GA) technique is proposed to solve the optimal golf swing motion which is generated by Fourier series approximation. The objective function for GA approach is to minimizing the intermediate and final state, minimizing the robot's energy consummation and maximizing the robot's speed. Obtained simulation results show the effectiveness of the proposed scheme.

  16. Pareto optimization in algebraic dynamic programming.

    PubMed

    Saule, Cédric; Giegerich, Robert

    2015-01-01

    Pareto optimization combines independent objectives by computing the Pareto front of its search space, defined as the set of all solutions for which no other candidate solution scores better under all objectives. This gives, in a precise sense, better information than an artificial amalgamation of different scores into a single objective, but is more costly to compute. Pareto optimization naturally occurs with genetic algorithms, albeit in a heuristic fashion. Non-heuristic Pareto optimization so far has been used only with a few applications in bioinformatics. We study exact Pareto optimization for two objectives in a dynamic programming framework. We define a binary Pareto product operator [Formula: see text] on arbitrary scoring schemes. Independent of a particular algorithm, we prove that for two scoring schemes A and B used in dynamic programming, the scoring scheme [Formula: see text] correctly performs Pareto optimization over the same search space. We study different implementations of the Pareto operator with respect to their asymptotic and empirical efficiency. Without artificial amalgamation of objectives, and with no heuristics involved, Pareto optimization is faster than computing the same number of answers separately for each objective. For RNA structure prediction under the minimum free energy versus the maximum expected accuracy model, we show that the empirical size of the Pareto front remains within reasonable bounds. Pareto optimization lends itself to the comparative investigation of the behavior of two alternative scoring schemes for the same purpose. For the above scoring schemes, we observe that the Pareto front can be seen as a composition of a few macrostates, each consisting of several microstates that differ in the same limited way. We also study the relationship between abstract shape analysis and the Pareto front, and find that they extract information of a different nature from the folding space and can be meaningfully combined.

  17. Application of optimal prediction to molecular dynamics

    SciTech Connect

    Barber, IV, John Letherman

    2004-12-01

    Optimal prediction is a general system reduction technique for large sets of differential equations. In this method, which was devised by Chorin, Hald, Kast, Kupferman, and Levy, a projection operator formalism is used to construct a smaller system of equations governing the dynamics of a subset of the original degrees of freedom. This reduced system consists of an effective Hamiltonian dynamics, augmented by an integral memory term and a random noise term. Molecular dynamics is a method for simulating large systems of interacting fluid particles. In this thesis, I construct a formalism for applying optimal prediction to molecular dynamics, producing reduced systems from which the properties of the original system can be recovered. These reduced systems require significantly less computational time than the original system. I initially consider first-order optimal prediction, in which the memory and noise terms are neglected. I construct a pair approximation to the renormalized potential, and ignore three-particle and higher interactions. This produces a reduced system that correctly reproduces static properties of the original system, such as energy and pressure, at low-to-moderate densities. However, it fails to capture dynamical quantities, such as autocorrelation functions. I next derive a short-memory approximation, in which the memory term is represented as a linear frictional force with configuration-dependent coefficients. This allows the use of a Fokker-Planck equation to show that, in this regime, the noise is δ-correlated in time. This linear friction model reproduces not only the static properties of the original system, but also the autocorrelation functions of dynamical variables.

  18. Rigorous bounds for optimal dynamical decoupling

    SciTech Connect

    Uhrig, Goetz S.; Lidar, Daniel A.

    2010-07-15

    We present rigorous performance bounds for the optimal dynamical decoupling pulse sequence protecting a quantum bit (qubit) against pure dephasing. Our bounds apply under the assumption of instantaneous pulses and of bounded perturbing environment and qubit-environment Hamiltonians such as those realized by baths of nuclear spins in quantum dots. We show that if the total sequence time is fixed the optimal sequence can be used to make the distance between the protected and unperturbed qubit states arbitrarily small in the number of applied pulses. If, on the other hand, the minimum pulse interval is fixed and the total sequence time is allowed to scale with the number of pulses, then longer sequences need not always be advantageous. The rigorous bound may serve as a testbed for approximate treatments of optimal decoupling in bounded models of decoherence.

  19. Direct Optimal Control of Duffing Dynamics

    NASA Technical Reports Server (NTRS)

    Oz, Hayrani; Ramsey, John K.

    2002-01-01

    The "direct control method" is a novel concept that is an attractive alternative and competitor to the differential-equation-based methods. The direct method is equally well applicable to nonlinear, linear, time-varying, and time-invariant systems. For all such systems, the method yields explicit closed-form control laws based on minimization of a quadratic control performance measure. We present an application of the direct method to the dynamics and optimal control of the Duffing system where the control performance measure is not restricted to a quadratic form and hence may include a quartic energy term. The results we present in this report also constitute further generalizations of our earlier work in "direct optimal control methodology." The approach is demonstrated for the optimal control of the Duffing equation with a softening nonlinear stiffness.

  20. An adaptive multi-swarm optimizer for dynamic optimization problems.

    PubMed

    Li, Changhe; Yang, Shengxiang; Yang, Ming

    2014-01-01

    The multipopulation method has been widely used to solve dynamic optimization problems (DOPs) with the aim of maintaining multiple populations on different peaks to locate and track multiple changing optima simultaneously. However, to make this approach effective for solving DOPs, two challenging issues need to be addressed. They are how to adapt the number of populations to changes and how to adaptively maintain the population diversity in a situation where changes are complicated or hard to detect or predict. Tracking the changing global optimum in dynamic environments is difficult because we cannot know when and where changes occur and what the characteristics of changes would be. Therefore, it is necessary to take these challenging issues into account in designing such adaptive algorithms. To address the issues when multipopulation methods are applied for solving DOPs, this paper proposes an adaptive multi-swarm algorithm, where the populations are enabled to be adaptive in dynamic environments without change detection. An experimental study is conducted based on the moving peaks problem to investigate the behavior of the proposed method. The performance of the proposed algorithm is also compared with a set of algorithms that are based on multipopulation methods from different research areas in the literature of evolutionary computation.

  1. Graphical models for optimal power flow

    SciTech Connect

    Dvijotham, Krishnamurthy; Chertkov, Michael; Van Hentenryck, Pascal; Vuffray, Marc; Misra, Sidhant

    2016-09-13

    Optimal power flow (OPF) is the central optimization problem in electric power grids. Although solved routinely in the course of power grid operations, it is known to be strongly NP-hard in general, and weakly NP-hard over tree networks. In this paper, we formulate the optimal power flow problem over tree networks as an inference problem over a tree-structured graphical model where the nodal variables are low-dimensional vectors. We adapt the standard dynamic programming algorithm for inference over a tree-structured graphical model to the OPF problem. Combining this with an interval discretization of the nodal variables, we develop an approximation algorithm for the OPF problem. Further, we use techniques from constraint programming (CP) to perform interval computations and adaptive bound propagation to obtain practically efficient algorithms. Compared to previous algorithms that solve OPF with optimality guarantees using convex relaxations, our approach is able to work for arbitrary tree-structured distribution networks and handle mixed-integer optimization problems. Further, it can be implemented in a distributed message-passing fashion that is scalable and is suitable for “smart grid” applications like control of distributed energy resources. In conclusion, numerical evaluations on several benchmark networks show that practical OPF problems can be solved effectively using this approach.

  2. Graphical models for optimal power flow

    DOE PAGES

    Dvijotham, Krishnamurthy; Chertkov, Michael; Van Hentenryck, Pascal; ...

    2016-09-13

    Optimal power flow (OPF) is the central optimization problem in electric power grids. Although solved routinely in the course of power grid operations, it is known to be strongly NP-hard in general, and weakly NP-hard over tree networks. In this paper, we formulate the optimal power flow problem over tree networks as an inference problem over a tree-structured graphical model where the nodal variables are low-dimensional vectors. We adapt the standard dynamic programming algorithm for inference over a tree-structured graphical model to the OPF problem. Combining this with an interval discretization of the nodal variables, we develop an approximation algorithmmore » for the OPF problem. Further, we use techniques from constraint programming (CP) to perform interval computations and adaptive bound propagation to obtain practically efficient algorithms. Compared to previous algorithms that solve OPF with optimality guarantees using convex relaxations, our approach is able to work for arbitrary tree-structured distribution networks and handle mixed-integer optimization problems. Further, it can be implemented in a distributed message-passing fashion that is scalable and is suitable for “smart grid” applications like control of distributed energy resources. In conclusion, numerical evaluations on several benchmark networks show that practical OPF problems can be solved effectively using this approach.« less

  3. Optimization of dynamic systems using collocation methods

    NASA Astrophysics Data System (ADS)

    Holden, Michael Eric

    The time-based simulation is an important tool for the engineer. Often a time-domain simulation is the most expedient to construct, the most capable of handling complex modeling issues, or the most understandable with an engineer's physical intuition. Aeroelastic systems, for example, are often most easily solved with a nonlinear time-based approach to allow the use of high fidelity models. Simulations of automatic flight control systems can also be easier to model in the time domain, especially when nonlinearities are present. Collocation is an optimization method for systems that incorporate a time-domain simulation. Instead of integrating the equations of motion for each design iteration, the optimizer iteratively solves the simulation as it finds the optimal design. This forms a smooth, well-posed, sparse optimization problem, transforming the numerical integration's sequential calculation into a set of constraints that can be evaluated in any order, or even in parallel. The collocation method used in this thesis has been improved from existing techniques in several ways, in particular with a very simple and computationally inexpensive method of applying dynamic constraints, such as damping, that are more traditionally calculated with linear models in the frequency domain. This thesis applies the collocation method to a range of aircraft design problems, from minimizing the weight of a wing with a flutter constraint, to gain-scheduling the stability augmentation system of a small-scale flight control testbed, to aeroservoelastic design of a large aircraft concept. Collocation methods have not been applied to aeroelastic simulations in the past, although the combination of nonlinear aerodynamic analyses with structural dynamics and stability constraints is well-suited to collocation. The results prove the collocation method's worth as a tool for aircraft design, particularly when applied to the multidisciplinary numerical models used today.

  4. Optimal bolt preload for dynamic loading

    SciTech Connect

    Duffey, T.A.

    1992-08-01

    A simple spring-mass model is developed for closure bolting systems, including the effects of bolt prestress. An analytical solution is developed for the case of an initially peaked, exponentially decaying internal pressure pulse acting on the closure. The dependence of peak bolt stresses and deflections on bolt prestress level is investigated and an optimal prestress that minimizes peak bolt stress is found in certain cases. Vulnerability curves are developed for bolted-closure systems to provide rapid evaluation of the dynamic capacity of designs for a range in bolt prestress.

  5. Optimal bolt preload for dynamic loading

    SciTech Connect

    Duffey, T.A.

    1992-01-01

    A simple spring-mass model is developed for closure bolting systems, including the effects of bolt prestress. An analytical solution is developed for the case of an initially peaked, exponentially decaying internal pressure pulse acting on the closure. The dependence of peak bolt stresses and deflections on bolt prestress level is investigated and an optimal prestress that minimizes peak bolt stress is found in certain cases. Vulnerability curves are developed for bolted-closure systems to provide rapid evaluation of the dynamic capacity of designs for a range in bolt prestress.

  6. Structural optimization for nonlinear dynamic response.

    PubMed

    Dou, Suguang; Strachan, B Scott; Shaw, Steven W; Jensen, Jakob S

    2015-09-28

    Much is known about the nonlinear resonant response of mechanical systems, but methods for the systematic design of structures that optimize aspects of these responses have received little attention. Progress in this area is particularly important in the area of micro-systems, where nonlinear resonant behaviour is being used for a variety of applications in sensing and signal conditioning. In this work, we describe a computational method that provides a systematic means for manipulating and optimizing features of nonlinear resonant responses of mechanical structures that are described by a single vibrating mode, or by a pair of internally resonant modes. The approach combines techniques from nonlinear dynamics, computational mechanics and optimization, and it allows one to relate the geometric and material properties of structural elements to terms in the normal form for a given resonance condition, thereby providing a means for tailoring its nonlinear response. The method is applied to the fundamental nonlinear resonance of a clamped-clamped beam and to the coupled mode response of a frame structure, and the results show that one can modify essential normal form coefficients by an order of magnitude by relatively simple changes in the shape of these elements. We expect the proposed approach, and its extensions, to be useful for the design of systems used for fundamental studies of nonlinear behaviour as well as for the development of commercial devices that exploit nonlinear behaviour.

  7. Optimal dynamic discrimination of similar quantum systems

    NASA Astrophysics Data System (ADS)

    Li, Baiqing

    2005-07-01

    The techniques for identifying and separating similar molecules have always been very important to chemistry and other branches of science and engineering. Similar quantum systems share comparable Hamiltonians, so their eigenenergy levels, transition dipole moments, and therefore their ordinary observable properties are alike. Traditional analytical methods have mostly been restricted by working with the subtle differences in the physical and chemical properties of the similar species. Optimal Dynamic Discrimination (ODD) aims at magnifying the dissimilarity of the agents by actively controlling their quantum evolution, drawing on the extremely rich information embedded in their dynamics. ODD is developed based on the tremendous flexibility of Optimal Control Theory (OCT) and on the practical implementation of closed-loop learning control, which has become a more and more indispensable tool for controlling quantum processes. The ODD experimental paradigm is designed to combat a number of factors that are detrimental to the discrimination of similar molecules: laser pulse noise, signal detection errors, finite time resolution in the signals, and environmental decoherence effects. It utilizes either static signals or time series signal, the latter capable of providing more information. Simulations are performed in this dissertation progressing from the wave function to the density matrix formulation, in order to study the decoherence effects. Analysis of the results reveals the roles of the adverse factors, unravels the underlying mechanisms of ODD, and provides insights on laboratory implementation. ODD emphasizes the incorporation of algorithmic development and laboratory design, and seeks to bridge the gap between theoretical/computational chemistry and experimental chemistry, with the help from applied mathematics and computer science.

  8. Distributed Adaptive Particle Swarm Optimizer in Dynamic Environment

    SciTech Connect

    Cui, Xiaohui; Potok, Thomas E

    2007-01-01

    In the real world, we have to frequently deal with searching and tracking an optimal solution in a dynamical and noisy environment. This demands that the algorithm not only find the optimal solution but also track the trajectory of the changing solution. Particle Swarm Optimization (PSO) is a population-based stochastic optimization technique, which can find an optimal, or near optimal, solution to a numerical and qualitative problem. In PSO algorithm, the problem solution emerges from the interactions between many simple individual agents called particles, which make PSO an inherently distributed algorithm. However, the traditional PSO algorithm lacks the ability to track the optimal solution in a dynamic and noisy environment. In this paper, we present a distributed adaptive PSO (DAPSO) algorithm that can be used for tracking a non-stationary optimal solution in a dynamically changing and noisy environment.

  9. Optimal control of HIV/AIDS dynamic: Education and treatment

    NASA Astrophysics Data System (ADS)

    Sule, Amiru; Abdullah, Farah Aini

    2014-07-01

    A mathematical model which describes the transmission dynamics of HIV/AIDS is developed. The optimal control representing education and treatment for this model is explored. The existence of optimal Control is established analytically by the use of optimal control theory. Numerical simulations suggest that education and treatment for the infected has a positive impact on HIV/AIDS control.

  10. Robustified time-optimal control of uncertain structural dynamic systems

    NASA Technical Reports Server (NTRS)

    Liu, Qiang; Wie, Bong

    1991-01-01

    A new approach for computing open-loop time-optimal control inputs for uncertain linear dynamical systems is developed. In particular, the single-axis, rest-to-rest maneuvering problem of flexible spacecraft in the presence of uncertainty in model parameters is considered. Robustified time-optimal control inputs are obtained by solving a parameter optimization problem subject to robustness constraints. A simple dynamical system with a rigid-body mode and one flexible mode is used to illustrate the concept.

  11. Effects-Based Design of Robust Organizations

    DTIC Science & Technology

    2004-06-01

    turn, are used to synthesize a robust organizational structure. Keywords: Organizational Design, Markov Deci- sion Processes, Reinforcement Learning , and...Markov Decision Processes (MDP), reinforcement learning , Monte Carlo con- trol method, and mixed integer optimization, as in aElectrical and Computer...based on MDP, Monte Carlo control method, reinforcement learning , and mixed integer optimization techniques. In section III, we formulate the dynamic

  12. Dynamic optimization identifies optimal programmes for pathway regulation in prokaryotes.

    PubMed

    Bartl, Martin; Kötzing, Martin; Schuster, Stefan; Li, Pu; Kaleta, Christoph

    2013-01-01

    To survive in fluctuating environmental conditions, microorganisms must be able to quickly react to environmental challenges by upregulating the expression of genes encoding metabolic pathways. Here we show that protein abundance and protein synthesis capacity are key factors that determine the optimal strategy for the activation of a metabolic pathway. If protein abundance relative to protein synthesis capacity increases, the strategies shift from the simultaneous activation of all enzymes to the sequential activation of groups of enzymes and finally to a sequential activation of individual enzymes along the pathway. In the case of pathways with large differences in protein abundance, even more complex pathway activation strategies with a delayed activation of low abundance enzymes and an accelerated activation of high abundance enzymes are optimal. We confirm the existence of these pathway activation strategies as well as their dependence on our proposed constraints for a large number of metabolic pathways in several hundred prokaryotes.

  13. Dynamic systems of regional economy management optimization

    NASA Astrophysics Data System (ADS)

    Trofimov, S.; Kudzh, S.

    directions of an industrial policy of region. The situational-analytical centers (SAC) of regional administration The major component of SAC is dynamic modeling, analysis, forecasting and optimization systems, based on modern intellectual information technologies. Spheres of SAC are not only financial streams management and investments optimization, but also strategic forecasting functions, which provide an optimum choice, "aiming", search of optimum ways of regional development and corresponding investments. It is expedient to consider an opportunity of formation of the uniform organizational-methodical center of an industrial policy of region. This organization can be directly connected to the scheduled-analytical services of the largest economic structures, local authorities, the ministries and departments. Such "direct communication" is capable to provide an effective regional development strategic management. Anyway, the output on foreign markets demands concentration of resources and support of authorities. Offered measures are capable to provide a necessary coordination of efforts of a various level economic structures. For maintenance of a regional industrial policy an attraction of all newest methods of strategic planning and management is necessary. Their activity should be constructed on the basis of modern approaches of economic systems management, cause the essence of an industrial policy is finally reduced to an effective regional and corporate economic activities control centers formation. Opportunities of optimum regional economy planning and management as uniform system Approaches to planning regional economic systems can be different. We will consider some most effective methods of planning and control over a regional facilities condition. All of them are compact and evident, that allows to put them into the group of average complexity technologies. At the decision of problems of a regional resource management is rather perspective the so

  14. Method to describe stochastic dynamics using an optimal coordinate.

    PubMed

    Krivov, Sergei V

    2013-12-01

    A general method to describe the stochastic dynamics of Markov processes is suggested. The method aims to solve three related problems: the determination of an optimal coordinate for the description of stochastic dynamics; the reconstruction of time from an ensemble of stochastic trajectories; and the decomposition of stationary stochastic dynamics into eigenmodes which do not decay exponentially with time. The problems are solved by introducing additive eigenvectors which are transformed by a stochastic matrix in a simple way - every component is translated by a constant distance. Such solutions have peculiar properties. For example, an optimal coordinate for stochastic dynamics with detailed balance is a multivalued function. An optimal coordinate for a random walk on a line corresponds to the conventional eigenvector of the one-dimensional Dirac equation. The equation for the optimal coordinate in a slowly varying potential reduces to the Hamilton-Jacobi equation for the action function.

  15. Optimal birth control of population dynamics.

    PubMed

    Chan, W L; Guo, B Z

    1989-11-01

    The authors studied optimal birth control policies for an age-structured population of McKendrick type which is a distributed parameter system involving 1st order partial differential equations with nonlocal bilinear boundary control. The functional analytic approach of Dubovitskii and Milyutin is adopted in the investigation. Maximum principles for problems with a free end condition and fixed final horizon are developed, and the time optimal control problems, the problem with target sets, and infinite planning horizon case are investigated.

  16. An Optimization Framework for Dynamic, Distributed Real-Time Systems

    NASA Technical Reports Server (NTRS)

    Eckert, Klaus; Juedes, David; Welch, Lonnie; Chelberg, David; Bruggerman, Carl; Drews, Frank; Fleeman, David; Parrott, David; Pfarr, Barbara

    2003-01-01

    Abstract. This paper presents a model that is useful for developing resource allocation algorithms for distributed real-time systems .that operate in dynamic environments. Interesting aspects of the model include dynamic environments, utility and service levels, which provide a means for graceful degradation in resource-constrained situations and support optimization of the allocation of resources. The paper also provides an allocation algorithm that illustrates how to use the model for producing feasible, optimal resource allocations.

  17. Robust Dynamic Multi-objective Vehicle Routing Optimization Method.

    PubMed

    Guo, Yi-Nan; Cheng, Jian; Luo, Sha; Gong, Dun-Wei

    2017-03-21

    For dynamic multi-objective vehicle routing problems, the waiting time of vehicle, the number of serving vehicles, the total distance of routes were normally considered as the optimization objectives. Except for above objectives, fuel consumption that leads to the environmental pollution and energy consumption was focused on in this paper. Considering the vehicles' load and the driving distance, corresponding carbon emission model was built and set as an optimization objective. Dynamic multi-objective vehicle routing problems with hard time windows and randomly appeared dynamic customers, subsequently, were modeled. In existing planning methods, when the new service demand came up, global vehicle routing optimization method was triggered to find the optimal routes for non-served customers, which was time-consuming. Therefore, robust dynamic multi-objective vehicle routing method with two-phase is proposed. Three highlights of the novel method are: (i) After finding optimal robust virtual routes for all customers by adopting multi-objective particle swarm optimization in the first phase, static vehicle routes for static customers are formed by removing all dynamic customers from robust virtual routes in next phase. (ii)The dynamically appeared customers append to be served according to their service time and the vehicles' statues. Global vehicle routing optimization is triggered only when no suitable locations can be found for dynamic customers. (iii)A metric measuring the algorithms' robustness is given. The statistical results indicated that the routes obtained by the proposed method have better stability and robustness, but may be sub-optimum. Moreover, time-consuming global vehicle routing optimization is avoided as dynamic customers appear.

  18. Vehicle dynamics applications of optimal control theory

    NASA Astrophysics Data System (ADS)

    Sharp, R. S.; Peng, Huei

    2011-07-01

    The aim of the paper is to survey the various forms of optimal-control theory which have been applied to automotive problems and to present illustrative examples of applications studies, with assessments of the state of the art and of the contributions made through the use of optimal-control ideas. After a short introduction to the topic mentioning several questions to which optimal-control theory has been addressed, brief reviews of automotive-applicable optimal-control theory are given. There are outlines of the Linear Quadratic Regulator, without and with state reconstruction and then with the addition of disturbance preview, the nonlinear regulator or state-dependent-Riccati equation method, general numerical optimal-control theory including indirect and direct methods, model predictive control and robust control. Applications of the theory to active and semi-active suspension design and performance, worst-case manoeuvring, minimum-time manoeuvring and high-quality driving are then discussed in detail. Application sections describe the problem, the theory that has been used, what has been discovered and what remains to be found. The record of optimal-control theory in aiding the understanding of the various issues, in helping with system designs and knowledge of what is possible, and in guiding future research is assessed. Some ideas about future work are included.

  19. Wind farm turbine type and placement optimization

    SciTech Connect

    Graf, Peter; Dykes, Katherine; Scott, George; Fields, Jason; Lunacek, Monte; Quick, Julian; Rethore, Pierre -Elouan

    2016-10-03

    The layout of turbines in a wind farm is already a challenging nonlinear, nonconvex, nonlinearly constrained continuous global optimization problem. Here we begin to address the next generation of wind farm optimization problems by adding the complexity that there is more than one turbine type to choose from. The optimization becomes a nonlinear constrained mixed integer problem, which is a very difficult class of problems to solve. Furthermore, this document briefly summarizes the algorithm and code we have developed, the code validation steps we have performed, and the initial results for multi-turbine type and placement optimization (TTP_OPT) we have run.

  20. Wind Farm Turbine Type and Placement Optimization

    NASA Astrophysics Data System (ADS)

    Graf, Peter; Dykes, Katherine; Scott, George; Fields, Jason; Lunacek, Monte; Quick, Julian; Rethore, Pierre-Elouan

    2016-09-01

    The layout of turbines in a wind farm is already a challenging nonlinear, nonconvex, nonlinearly constrained continuous global optimization problem. Here we begin to address the next generation of wind farm optimization problems by adding the complexity that there is more than one turbine type to choose from. The optimization becomes a nonlinear constrained mixed integer problem, which is a very difficult class of problems to solve. This document briefly summarizes the algorithm and code we have developed, the code validation steps we have performed, and the initial results for multi-turbine type and placement optimization (TTP_OPT) we have run.

  1. An Optimization Framework for Dynamic Hybrid Energy Systems

    SciTech Connect

    Wenbo Du; Humberto E Garcia; Christiaan J.J. Paredis

    2014-03-01

    A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problem takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.

  2. Dynamics systems vs. optimal control--a unifying view.

    PubMed

    Schaal, Stefan; Mohajerian, Peyman; Ijspeert, Auke

    2007-01-01

    In the past, computational motor control has been approached from at least two major frameworks: the dynamic systems approach and the viewpoint of optimal control. The dynamic system approach emphasizes motor control as a process of self-organization between an animal and its environment. Nonlinear differential equations that can model entrainment and synchronization behavior are among the most favorable tools of dynamic systems modelers. In contrast, optimal control approaches view motor control as the evolutionary or development result of a nervous system that tries to optimize rather general organizational principles, e.g., energy consumption or accurate task achievement. Optimal control theory is usually employed to develop appropriate theories. Interestingly, there is rather little interaction between dynamic systems and optimal control modelers as the two approaches follow rather different philosophies and are often viewed as diametrically opposing. In this paper, we develop a computational approach to motor control that offers a unifying modeling framework for both dynamic systems and optimal control approaches. In discussions of several behavioral experiments and some theoretical and robotics studies, we demonstrate how our computational ideas allow both the representation of self-organizing processes and the optimization of movement based on reward criteria. Our modeling framework is rather simple and general, and opens opportunities to revisit many previous modeling results from this novel unifying view.

  3. Review of dynamic optimization methods in renewable natural resource management

    USGS Publications Warehouse

    Williams, B.K.

    1989-01-01

    In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. The applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.

  4. First principles molecular dynamics without self-consistent field optimization

    SciTech Connect

    Souvatzis, Petros; Niklasson, Anders M. N.

    2014-01-28

    We present a first principles molecular dynamics approach that is based on time-reversible extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] in the limit of vanishing self-consistent field optimization. The optimization-free dynamics keeps the computational cost to a minimum and typically provides molecular trajectories that closely follow the exact Born-Oppenheimer potential energy surface. Only one single diagonalization and Hamiltonian (or Fockian) construction are required in each integration time step. The proposed dynamics is derived for a general free-energy potential surface valid at finite electronic temperatures within hybrid density functional theory. Even in the event of irregular functional behavior that may cause a dynamical instability, the optimization-free limit represents a natural starting guess for force calculations that may require a more elaborate iterative electronic ground state optimization. Our optimization-free dynamics thus represents a flexible theoretical framework for a broad and general class of ab initio molecular dynamics simulations.

  5. First principles molecular dynamics without self-consistent field optimization.

    PubMed

    Souvatzis, Petros; Niklasson, Anders M N

    2014-01-28

    We present a first principles molecular dynamics approach that is based on time-reversible extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] in the limit of vanishing self-consistent field optimization. The optimization-free dynamics keeps the computational cost to a minimum and typically provides molecular trajectories that closely follow the exact Born-Oppenheimer potential energy surface. Only one single diagonalization and Hamiltonian (or Fockian) construction are required in each integration time step. The proposed dynamics is derived for a general free-energy potential surface valid at finite electronic temperatures within hybrid density functional theory. Even in the event of irregular functional behavior that may cause a dynamical instability, the optimization-free limit represents a natural starting guess for force calculations that may require a more elaborate iterative electronic ground state optimization. Our optimization-free dynamics thus represents a flexible theoretical framework for a broad and general class of ab initio molecular dynamics simulations.

  6. Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)

    SciTech Connect

    2012-05-31

    The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.

  7. Dynamic positioning configuration and its first-order optimization

    NASA Astrophysics Data System (ADS)

    Xue, Shuqiang; Yang, Yuanxi; Dang, Yamin; Chen, Wu

    2014-02-01

    Traditional geodetic network optimization deals with static and discrete control points. The modern space geodetic network is, on the other hand, composed of moving control points in space (satellites) and on the Earth (ground stations). The network configuration composed of these facilities is essentially dynamic and continuous. Moreover, besides the position parameter which needs to be estimated, other geophysical information or signals can also be extracted from the continuous observations. The dynamic (continuous) configuration of the space network determines whether a particular frequency of signals can be identified by this system. In this paper, we employ the functional analysis and graph theory to study the dynamic configuration of space geodetic networks, and mainly focus on the optimal estimation of the position and clock-offset parameters. The principle of the D-optimization is introduced in the Hilbert space after the concept of the traditional discrete configuration is generalized from the finite space to the infinite space. It shows that the D-optimization developed in the discrete optimization is still valid in the dynamic configuration optimization, and this is attributed to the natural generalization of least squares from the Euclidean space to the Hilbert space. Then, we introduce the principle of D-optimality invariance under the combination operation and rotation operation, and propose some D-optimal simplex dynamic configurations: (1) (Semi) circular configuration in 2-dimensional space; (2) the D-optimal cone configuration and D-optimal helical configuration which is close to the GPS constellation in 3-dimensional space. The initial design of GPS constellation can be approximately treated as a combination of 24 D-optimal helixes by properly adjusting the ascending node of different satellites to realize a so-called Walker constellation. In the case of estimating the receiver clock-offset parameter, we show that the circular configuration, the

  8. Bridging developmental systems theory and evolutionary psychology using dynamic optimization.

    PubMed

    Frankenhuis, Willem E; Panchanathan, Karthik; Clark Barrett, H

    2013-07-01

    Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic optimization integrates developmental systems theorists' focus on dynamics and contingency with the 'design stance' of evolutionary psychology. It provides a theoretical framework as well as a set of tools for exploring the properties of developmental systems that natural selection might favor, given particular evolutionary ecologies. We also discuss limitations of the approach.

  9. Solving Optimal Control Problems by Exploiting Inherent Dynamical Systems Structures

    NASA Astrophysics Data System (ADS)

    Flaßkamp, Kathrin; Ober-Blöbaum, Sina; Kobilarov, Marin

    2012-08-01

    Computing globally efficient solutions is a major challenge in optimal control of nonlinear dynamical systems. This work proposes a method combining local optimization and motion planning techniques based on exploiting inherent dynamical systems structures, such as symmetries and invariant manifolds. Prior to the optimal control, the dynamical system is analyzed for structural properties that can be used to compute pieces of trajectories that are stored in a motion planning library. In the context of mechanical systems, these motion planning candidates, termed primitives, are given by relative equilibria induced by symmetries and motions on stable or unstable manifolds of e.g. fixed points in the natural dynamics. The existence of controlled relative equilibria is studied through Lagrangian mechanics and symmetry reduction techniques. The proposed framework can be used to solve boundary value problems by performing a search in the space of sequences of motion primitives connected using optimized maneuvers. The optimal sequence can be used as an admissible initial guess for a post-optimization. The approach is illustrated by two numerical examples, the single and the double spherical pendula, which demonstrates its benefit compared to standard local optimization techniques.

  10. On unified modeling, theory, and method for solving multi-scale global optimization problems

    NASA Astrophysics Data System (ADS)

    Gao, David Yang

    2016-10-01

    A unified model is proposed for general optimization problems in multi-scale complex systems. Based on this model and necessary assumptions in physics, the canonical duality theory is presented in a precise way to include traditional duality theories and popular methods as special applications. Two conjectures on NP-hardness are proposed, which should play important roles for correctly understanding and efficiently solving challenging real-world problems. Applications are illustrated for both nonconvex continuous optimization and mixed integer nonlinear programming.

  11. Dynamic optimization of metabolic networks coupled with gene expression.

    PubMed

    Waldherr, Steffen; Oyarzún, Diego A; Bockmayr, Alexander

    2015-01-21

    The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these do not account for temporal changes in biomass composition. Here we present a dynamic optimization framework that integrates the metabolic network with the dynamics of biomass production and composition. An approximation by a timescale separation leads to a coupled model of quasi-steady state constraints on the metabolic reactions, and differential equations for the substrate concentrations and biomass composition. We propose a dynamic optimization approach to determine reaction fluxes for this model, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. Discretization of the optimization problems leads to a linear program that can be efficiently solved. We applied our algorithm in two case studies: a minimal nutrient uptake network, and an abstraction of core metabolic processes in bacteria. In the minimal model, we show that the optimized uptake rates reproduce the empirical Monod growth for bacterial cultures. For the network of core metabolic processes, the dynamic optimization algorithm predicted commonly observed metabolic adaptations, such as a diauxic switch with a preference ranking for different nutrients, re-utilization of waste products after depletion of the original substrate, and metabolic adaptation to an impending nutrient depletion. These examples illustrate how dynamic adaptations of enzyme expression can be predicted solely from an optimization principle.

  12. Integrated aerodynamic/dynamic optimization of helicopter rotor blades

    NASA Technical Reports Server (NTRS)

    Chattopadhyay, Aditi; Walsh, Joanne L.; Riley, Michael F.

    1989-01-01

    An integrated aerodynamic/dynamic optimization procedure is used to minimize blade weight and 4 per rev vertical hub shear for a rotor blade in forward flight. The coupling of aerodynamics and dynamics is accomplished through the inclusion of airloads which vary with the design variables during the optimization process. Both single and multiple objective functions are used in the optimization formulation. The Global Criteria Approach is used to formulate the multiple objective optimization and results are compared with those obtained by using single objective function formulations. Constraints are imposed on natural frequencies, autorotational inertia, and centrifugal stress. The program CAMRAD is used for the blade aerodynamic and dynamic analyses, and the program CONMIN is used for the optimization. Since the spanwise and the azimuthal variations of loading are responsible for most rotor vibration and noise, the vertical airload distributions on the blade, before and after optimization, are compared. The total power required by the rotor to produce the same amount of thrust for a given area is also calculated before and after optimization. Results indicate that integrated optimization can significantly reduce the blade weight, the hub shear and the amplitude of the vertical airload distributions on the blade and the total power required by the rotor.

  13. Practical synchronization on complex dynamical networks via optimal pinning control

    NASA Astrophysics Data System (ADS)

    Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

    2015-07-01

    We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

  14. Practical synchronization on complex dynamical networks via optimal pinning control.

    PubMed

    Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

    2015-07-01

    We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

  15. Optimizing Dynamic Resource Allocation in Teamwork

    DTIC Science & Technology

    2008-02-01

    R. A. & Wagner, A. R. (1972). A theory of Pavlovian conditioning : Variations in the effectiveness of reinforcement and nonreinforcement. In... conditions of uncertainty is certainly one of the most important problems faced by team members performing complex tasks in stochastic environments. We...reinforcement learning algorithms and has been shown to converge to an optimal policy under realistic conditions . Given a particular state, s, a learning

  16. LEO cooperative multi-spacecraft refueling mission optimization considering J2 perturbation and target's surplus propellant constraint

    NASA Astrophysics Data System (ADS)

    Zhao, Zhao; Zhang, Jin; Li, Hai-yang; Zhou, Jian-yong

    2017-01-01

    The optimization of an LEO cooperative multi-spacecraft refueling mission considering the J2 perturbation and target's surplus propellant constraint is studied in the paper. First, a mission scenario is introduced. One service spacecraft and several target spacecraft run on an LEO near-circular orbit, the service spacecraft rendezvouses with some service positions one by one, and target spacecraft transfer to corresponding service positions respectively. Each target spacecraft returns to its original position after obtaining required propellant and the service spacecraft returns to its original position after refueling all target spacecraft. Next, an optimization model of this mission is built. The service sequence, orbital transfer time, and service position are used as deign variables, whereas the propellant cost is used as the design objective. The J2 perturbation, time constraint and the target spacecraft's surplus propellant capability constraint are taken into account. Then, a hybrid two-level optimization approach is presented to solve the formulated mixed integer nonlinear programming (MINLP) problem. A hybrid-encoding genetic algorithm is adopted to seek the near optimal solution in the up-level optimization, while a linear relative dynamic equation considering the J2 perturbation is used to obtain the impulses of orbital transfer in the low-level optimization. Finally, the effectiveness of the proposed model and method is validated by numerical examples.

  17. Global optimal design of ground water monitoring network using embedded kriging.

    PubMed

    Dhar, Anirban; Datta, Bithin

    2009-01-01

    We present a methodology for global optimal design of ground water quality monitoring networks using a linear mixed-integer formulation. The proposed methodology incorporates ordinary kriging (OK) within the decision model formulation for spatial estimation of contaminant concentration values. Different monitoring network design models incorporating concentration estimation error, variance estimation error, mass estimation error, error in locating plume centroid, and spatial coverage of the designed network are developed. A big-M technique is used for reformulating the monitoring network design model to a linear decision model while incorporating different objectives and OK equations. Global optimality of the solutions obtained for the monitoring network design can be ensured due to the linear mixed-integer programming formulations proposed. Performances of the proposed models are evaluated for both field and hypothetical illustrative systems. Evaluation results indicate that the proposed methodology performs satisfactorily. These performance evaluation results demonstrate the potential applicability of the proposed methodology for optimal ground water contaminant monitoring network design.

  18. Optimization Problems in Multisensor and Multitarget Tracking

    DTIC Science & Technology

    2008-02-25

    optimize the the mixed integer nonlinear programming problem Minimize(x,d) cr(d) + E cij(d)xij (i,j)EA Subject To: Y xij 5 1 (i = 1,...,m), (7) jEA(i...Donald Hearn, Program Manager Optimization and Discrete Mathematics Air Force Office of Scientific Research /NL 875 North Randolph Street Suite 325...Number: FA9550-04-1-0222 Recipient: Dr Donald Hearn. Program Manager Recipient*s Address: Optimization and Discrete Mathematics Air Force Office of

  19. Combining optimal control theory and molecular dynamics for protein folding.

    PubMed

    Arkun, Yaman; Gur, Mert

    2012-01-01

    A new method to develop low-energy folding routes for proteins is presented. The novel aspect of the proposed approach is the synergistic use of optimal control theory with Molecular Dynamics (MD). In the first step of the method, optimal control theory is employed to compute the force field and the optimal folding trajectory for the Cα atoms of a Coarse-Grained (CG) protein model. The solution of this CG optimization provides an harmonic approximation of the true potential energy surface around the native state. In the next step CG optimization guides the MD simulation by specifying the optimal target positions for the Cα atoms. In turn, MD simulation provides an all-atom conformation whose Cα positions match closely the reference target positions determined by CG optimization. This is accomplished by Targeted Molecular Dynamics (TMD) which uses a bias potential or harmonic restraint in addition to the usual MD potential. Folding is a dynamical process and as such residues make different contacts during the course of folding. Therefore CG optimization has to be reinitialized and repeated over time to accomodate these important changes. At each sampled folding time, the active contacts among the residues are recalculated based on the all-atom conformation obtained from MD. Using the new set of contacts, the CG potential is updated and the CG optimal trajectory for the Cα atoms is recomputed. This is followed by MD. Implementation of this repetitive CG optimization-MD simulation cycle generates the folding trajectory. Simulations on a model protein Villin demonstrate the utility of the method. Since the method is founded on the general tools of optimal control theory and MD without any restrictions, it is widely applicable to other systems. It can be easily implemented with available MD software packages.

  20. Energy-optimal path planning by stochastic dynamically orthogonal level-set optimization

    NASA Astrophysics Data System (ADS)

    Subramani, Deepak N.; Lermusiaux, Pierre F. J.

    2016-04-01

    A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. Based on partial differential equations, the methodology rigorously leverages the level-set equation that governs time-optimal reachability fronts for a given relative vehicle-speed function. To set up the energy optimization, the relative vehicle-speed and headings are considered to be stochastic and new stochastic Dynamically Orthogonal (DO) level-set equations are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. Numerical schemes to solve the reduced stochastic DO level-set equations are obtained, and accuracy and efficiency considerations are discussed. These reduced equations are first shown to be efficient at solving the governing stochastic level-sets, in part by comparisons with direct Monte Carlo simulations. To validate the methodology and illustrate its accuracy, comparisons with semi-analytical energy-optimal path solutions are then completed. In particular, we consider the energy-optimal crossing of a canonical steady front and set up its semi-analytical solution using a energy-time nested nonlinear double-optimization scheme. We then showcase the inner workings and nuances of the energy-optimal path planning, considering different mission scenarios. Finally, we study and discuss results of energy-optimal missions in a wind-driven barotropic quasi-geostrophic double-gyre ocean circulation.

  1. Optimization-based Dynamic Human Walking Prediction

    DTIC Science & Technology

    2007-01-01

    9(1), 1997, p 10-17. 3. Chevallereau, C. and Aousin, Y. Optimal reference trajectories for walking and running of a biped robot. Robotica , v 19...28, 2001, Arlington, Virginia. 13. Mu, XP. and Wu, Q. Synthesis of a complete sagittal gait cycle for a five-link biped robot. Robotica , v 21...gait cycles of a biped robot. Robotica , v 21(2), 2003, p 199-210. 16. Sardain, P. and Bessonnet, G. Forces acting on a biped robot. Center of

  2. Fully integrated aerodynamic/dynamic optimization of helicopter rotor blades

    NASA Technical Reports Server (NTRS)

    Walsh, Joanne L.; Lamarsh, William J., II; Adelman, Howard M.

    1992-01-01

    A fully integrated aerodynamic/dynamic optimization procedure is described for helicopter rotor blades. The procedure combines performance and dynamic analyses with a general purpose optimizer. The procedure minimizes a linear combination of power required (in hover, forward flight, and maneuver) and vibratory hub shear. The design variables include pretwist, taper initiation, taper ratio, root chord, blade stiffnesses, tuning masses, and tuning mass locations. Aerodynamic constraints consist of limits on power required in hover, forward flight and maneuvers; airfoil section stall; drag divergence Mach number; minimum tip chord; and trim. Dynamic constraints are on frequencies, minimum autorotational inertia, and maximum blade weight. The procedure is demonstrated for two cases. In the first case, the objective function involves power required (in hover, forward flight and maneuver) and dynamics. The second case involves only hover power and dynamics. The designs from the integrated procedure are compared with designs from a sequential optimization approach in which the blade is first optimized for performance and then for dynamics. In both cases, the integrated approach is superior.

  3. Dynamic optimization of district energy grid

    NASA Astrophysics Data System (ADS)

    Salsbery, Scott

    The University of Iowa Power Plant operates utility generation and distribution for campus facilities, including electricity, steam, and chilled water. It is desirable to evaluate the optimal load combination of boilers, engines and chillers to meet the demand at minimal cost, particularly for future demand scenarios. An algorithm has been developed which takes into account the performance of individual units as part of the mix which ultimately supplies the campus and determine the degree that each should be operating to most efficiently meet demand. The algorithm is part of an integrated simulation tool which is specifically designed to apply traditional optimization techniques for a given (both current and possible) circumstance. The second component is to couple the algorithm with accurate estimates and historical data through which expected demand could be predicted. The simulation tool can account for any theoretical circumstance, which will be highly beneficial for strategic planning. As part of the process it is also necessary to determine the unique operating characteristics of the system components. The algorithms rely upon performance curves of individual system components (boiler, chiller, etc.) and those must be developed and refined when possible from experimental testing and commissioning or manufacturer supplied data.

  4. Optimized reduction of uncertainty in bursty human dynamics.

    PubMed

    Jo, Hang-Hyun; Moon, Eunyoung; Kaski, Kimmo

    2012-01-01

    Human dynamics is known to be inhomogeneous and bursty but the detailed understanding of the role of human factors in bursty dynamics is still lacking. In order to investigate their role we devise an agent-based model, where an agent in an uncertain situation tries to reduce the uncertainty by communicating with information providers while having to wait time for responses. Here the waiting time can be considered as cost. We show that the optimal choice of the waiting time under uncertainty gives rise to the bursty dynamics, characterized by the heavy tailed distribution of optimal waiting time. We find that in all cases the efficiency for communication is relevant to the scaling behavior of the optimal waiting time distribution. On the other hand, the cost turns out in some cases to be irrelevant depending on the degree of uncertainty and efficiency.

  5. Multi-objective dynamic aperture optimization for storage rings

    NASA Astrophysics Data System (ADS)

    Li, Yongjun; Yang, Lingyun

    2016-11-01

    We report an efficient dynamic aperture (DA) optimization approach using multi-objective genetic algorithm (MOGA), which is driven by nonlinear driving terms computation. It was found that having small low order driving terms is a necessary but insufficient condition of having a decent DA. Then direct DA tracking simulation is implemented among the last generation candidates to select the best solutions. The approach was demonstrated successfully in optimizing NSLS-II storage ring DA.

  6. Evolutionary Dynamic Multiobjective Optimization Via Kalman Filter Prediction.

    PubMed

    Muruganantham, Arrchana; Tan, Kay Chen; Vadakkepat, Prahlad

    2016-12-01

    Evolutionary algorithms are effective in solving static multiobjective optimization problems resulting in the emergence of a number of state-of-the-art multiobjective evolutionary algorithms (MOEAs). Nevertheless, the interest in applying them to solve dynamic multiobjective optimization problems has only been tepid. Benchmark problems, appropriate performance metrics, as well as efficient algorithms are required to further the research in this field. One or more objectives may change with time in dynamic optimization problems. The optimization algorithm must be able to track the moving optima efficiently. A prediction model can learn the patterns from past experience and predict future changes. In this paper, a new dynamic MOEA using Kalman filter (KF) predictions in decision space is proposed to solve the aforementioned problems. The predictions help to guide the search toward the changed optima, thereby accelerating convergence. A scoring scheme is devised to hybridize the KF prediction with a random reinitialization method. Experimental results and performance comparisons with other state-of-the-art algorithms demonstrate that the proposed algorithm is capable of significantly improving the dynamic optimization performance.

  7. Recursive multibody dynamics and discrete-time optimal control

    NASA Technical Reports Server (NTRS)

    Deleuterio, G. M. T.; Damaren, C. J.

    1989-01-01

    A recursive algorithm is developed for the solution of the simulation dynamics problem for a chain of rigid bodies. Arbitrary joint constraints are permitted, that is, joints may allow translational and/or rotational degrees of freedom. The recursive procedure is shown to be identical to that encountered in a discrete-time optimal control problem. For each relevant quantity in the multibody dynamics problem, there exists an analog in the context of optimal control. The performance index that is minimized in the control problem is identified as Gibbs' function for the chain of bodies.

  8. Experimental Testing of Dynamically Optimized Photoelectron Beams

    SciTech Connect

    Rosenzweig, J. B.; Cook, A. M.; Dunning, M.; England, R. J.; Musumeci, P.; Bellaveglia, M.; Boscolo, M.; Catani, L.; Cianchi, A.; Di Pirro, G.; Ferrario, M.; Fillipetto, D.; Gatti, G.; Palumbo, L.; Vicario, C.; Serafini, L.; Jones, S.

    2006-11-27

    We discuss the design of and initial results from an experiment in space-charge dominated beam dynamics which explores a new regime of high-brightness electron beam generation at the SPARC photoinjector. The scheme under study employs the tendency of intense electron beams to rearrange to produce uniform density, giving a nearly ideal beam from the viewpoint of space charge-induced emittance. The experiments are aimed at testing the marriage of this idea with a related concept, emittance compensation. We show that this new regime of operating photoinjector may be the preferred method of obtaining highest brightness beams with lower energy spread. We discuss the design of the experiment, including developing of a novel time-dependent, aerogel-based imaging system. This system has been installed at SPARC, and first evidence for nearly uniformly filled ellipsoidal charge distributions recorded.

  9. Experimental Testing of Dynamically Optimized Photoelectron Beams

    NASA Astrophysics Data System (ADS)

    Rosenzweig, J. B.; Cook, A. M.; Dunning, M.; England, R. J.; Musumeci, P.; Bellaveglia, M.; Boscolo, M.; Catani, L.; Cianchi, A.; Di Pirro, G.; Ferrario, M.; Fillipetto, D.; Gatti, G.; Palumbo, L.; Serafini, L.; Vicario, C.; Jones, S.

    2006-11-01

    We discuss the design of and initial results from an experiment in space-charge dominated beam dynamics which explores a new regime of high-brightness electron beam generation at the SPARC photoinjector. The scheme under study employs the tendency of intense electron beams to rearrange to produce uniform density, giving a nearly ideal beam from the viewpoint of space charge-induced emittance. The experiments are aimed at testing the marriage of this idea with a related concept, emittance compensation. We show that this new regime of operating photoinjector may be the preferred method of obtaining highest brightness beams with lower energy spread. We discuss the design of the experiment, including developing of a novel time-dependent, aerogel-based imaging system. This system has been installed at SPARC, and first evidence for nearly uniformly filled ellipsoidal charge distributions recorded.

  10. Optimizing Laboratory Experiments for Dynamic Astrophysical Phenomena

    SciTech Connect

    Ryutov, D; Remington, B

    2005-09-13

    To make a laboratory experiment an efficient tool for the studying the dynamical astrophysical phenomena, it is desirable to perform them in such a way as to observe the scaling invariance with respect to the astrophysical system under study. Several examples are presented of such scalings in the area of magnetohydrodynamic phenomena, where a number of scaled experiments have been performed. A difficult issue of the effect of fine-scale dissipative structures on the global scale dissipation-free flow is discussed. The second part of the paper is concerned with much less developed area of the scalings relevant to the interaction of an ultra-intense laser pulse with a pre-formed plasma. The use of the symmetry arguments in such experiments is also considered.

  11. Optimal dynamic bandwidth allocation for complex networks

    NASA Astrophysics Data System (ADS)

    Jiang, Zhong-Yuan; Liang, Man-Gui; Li, Qian; Guo, Dong-Chao

    2013-03-01

    Traffic capacity of one network strongly depends on the link’s bandwidth allocation strategy. In previous bandwidth allocation mechanisms, once one link’s bandwidth is allocated, it will be fixed throughout the overall traffic transmission process. However, the traffic load of every link changes from time to time. In this paper, with finite total bandwidth resource of the network, we propose to dynamically allocate the total bandwidth resource in which each link’s bandwidth is proportional to the queue length of the output buffer of the link per time step. With plenty of data packets in the network, the traffic handling ability of all links of the network achieves full utilization. The theoretical analysis and the extensive simulation results on complex networks are consistent. This work is valuable for network service providers to improve network performance or to do reasonable network design efficiently.

  12. Optimization of Conformational Dynamics in an Epistatic Evolutionary Trajectory.

    PubMed

    González, Mariano M; Abriata, Luciano A; Tomatis, Pablo E; Vila, Alejandro J

    2016-07-01

    The understanding of protein evolution depends on the ability to relate the impact of mutations on molecular traits to organismal fitness. Biological activity and robustness have been regarded as important features in shaping protein evolutionary landscapes. Conformational dynamics, which is essential for protein function, has received little attention in the context of evolutionary analyses. Here we employ NMR spectroscopy, the chief experimental tool to describe protein dynamics at atomic level in solution at room temperature, to study the intrinsic dynamic features of a metallo- Β: -lactamase enzyme and three variants identified during a directed evolution experiment that led to an expanded substrate profile. We show that conformational dynamics in the catalytically relevant microsecond to millisecond timescale is optimized along the favored evolutionary trajectory. In addition, we observe that the effects of mutations on dynamics are epistatic. Mutation Gly262Ser introduces slow dynamics on several residues that surround the active site when introduced in the wild-type enzyme. Mutation Asn70Ser removes the slow dynamics observed for few residues of the wild-type enzyme, but increases the number of residues that undergo slow dynamics when introduced in the Gly262Ser mutant. These effects on dynamics correlate with the epistatic interaction between these two mutations on the bacterial phenotype. These findings indicate that conformational dynamics is an evolvable trait, and that proteins endowed with more dynamic active sites also display a larger potential for promoting evolution.

  13. MULTIOBJECTIVE DYNAMIC APERTURE OPTIMIZATION AT NSLS-II

    SciTech Connect

    Yang, L.; Li, Y.; Guo, W.; Krinsky, S.

    2011-03-28

    In this paper we present a multiobjective approach to the dynamic aperture (DA) optimization. Taking the NSLS-II lattice as an example, we have used both sextupoles and quadrupoles as tuning variables to optimize both on-momentum and off-momentum DA. The geometric and chromatic sextupoles are used for nonlinear properties while the tunes are independently varied by quadrupoles. The dispersion and emittance are fixed during tunes variation. The algorithms, procedures, performances and results of our optimization of DA will be discussed and they are found to be robust, general and easy to apply to similar problems.

  14. Experimental Testing of Dynamically Optimized Photoelectron Beams

    NASA Astrophysics Data System (ADS)

    Rosenzweig, J. B.; Cook, A. M.; Dunning, M.; England, R. J.; Musumeci, P.; Bellaveglia, M.; Boscolo, M.; Catani, L.; Cianchi, A.; Pirro, G. Di; Ferrario, M.; Fillipetto, D.; Gatti, G.; Palumbo, L.; Serafini, L.; Vicario, C.

    2007-09-01

    We discuss the design of and initial results from an experiment in space-charge dominated beam dynamics which explores a new regime of high-brightness electron beam generation at the SPARC (located at INFN-LNF, Frascati) photoinjector. The scheme under study employs the natural tendency in intense electron beams to configure themselves to produce a uniform density, giving a nearly ideal beam from the viewpoint of space charge-induced emittance. The experiments are aimed at testing the marriage of this idea with a related concept, emittance compensation, We show that the existing infrastructure at SPARC is nearly ideal for the proposed tests, and that this new regime of operating photoinjector may be the preferred method of obtaining highest brightness beams with lower energy spread. We discuss the design of the experiment, including developing of a novel time-dependent, aerogel-based imaging system. This system has been installed at SPARC, and first evidence for nearly uniformly filled ellipsoidal charge distributions recorded.

  15. Experimental Testing of Dynamically Optimized Photoelectron Beams

    NASA Astrophysics Data System (ADS)

    Rosenzweig, J. B.; Cook, A. M.; Dunning, M.; England, R. J.; Musumeci, P.; Bellaveglia, M.; Boscolo, M.; Catani, L.; Cianchi, A.; di Pirro, G.; Ferrario, M.; Fillipetto, D.; Gatti, G.; Palumbo, L.; Serafini, L.; Vicario, C.

    We discuss the design of and initial results from an experiment in space-charge dominated beam dynamics which explores a new regime of high-brightness electron beam generation at the SPARC (located at INFN-LNF, Frascati) photoinjector. The scheme under study employs the natural tendency in intense electron beams to configure themselves to produce a uniform density, giving a nearly ideal beam from the viewpoint of space charge-induced emittance. The experiments are aimed at testing the marriage of this idea with a related concept, emittance compensation, We show that the existing infrastructure at SPARC is nearly ideal for the proposed tests, and that this new regime of operating photoinjector may be the preferred method of obtaining highest brightness beams with lower energy spread. We discuss the design of the experiment, including developing of a novel time-dependent, aerogel-based imaging system. This system has been installed at SPARC, and first evidence for nearly uniformly filled ellipsoidal charge distributions recorded.

  16. Bridging Developmental Systems Theory and Evolutionary Psychology Using Dynamic Optimization

    ERIC Educational Resources Information Center

    Frankenhuis, Willem E.; Panchanathan, Karthik; Clark Barrett, H.

    2013-01-01

    Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic…

  17. Can Structural Optimization Explain Slow Dynamics of Rocks?

    NASA Astrophysics Data System (ADS)

    Kim, H.; Vistisen, O.; Tencate, J. A.

    2009-12-01

    Slow dynamics is a recovery process that describes the return to an equilibrium state after some external energy input is applied and then removed. Experimental studies on many rocks have shown that a modest acoustic energy input results in slow dynamics. The recovery process of the stiffness has consistently been found to be linear to log(time) for a wide range of geomaterials and the time constants appear to be unique to the material [TenCate JA, Shankland TJ (1996), Geophys Res Lett 23, 3019-3022]. Measurements of this nonequilibrium effect in rocks (e.g. sandstones and limestones) have been linked directly to the cement holding the individual grains together [Darling TW, TenCate JA, Brown DW, Clausen B, Vogel SC (2004), Geophys Res Lett 31, L16604], also suggesting a potential link to porosity and permeability. Noting that slow dynamics consistently returns the overall stiffness of rocks to its maximum (original) state, it is hypothesized that the original state represents the global minimum strain energy state. Consequently the slow dynamics process represents the global minimization or optimization process. Structural optimization, which has been developed for engineering design, minimises the total strain energy by rearranging the material distribution [Kim H, Querin OM, Steven GP, Xie YM (2002), Struct Multidiscip Optim 24, 441-448]. The optimization process effectively rearranges the way the material is cemented. One of the established global optimization methods is simulated annealing (SA). Derived from cooling of metal to a thermal equilibrium, SA finds an optimum solution by iteratively moving the system towards the minimum energy state with a probability of 'uphill' moves. It has been established that the global optimum can be guaranteed by applying a log(time) linear cooling schedule [Hajek B (1988, Math Ops Res, 15, 311-329]. This work presents the original study of applying SA to the maximum stiffness optimization problem. Preliminary results

  18. A dynamic optimization model for solid waste recycling.

    PubMed

    Anghinolfi, Davide; Paolucci, Massimo; Robba, Michela; Taramasso, Angela Celeste

    2013-02-01

    Recycling is an important part of waste management (that includes different kinds of issues: environmental, technological, economic, legislative, social, etc.). Differently from many works in literature, this paper is focused on recycling management and on the dynamic optimization of materials collection. The developed dynamic decision model is characterized by state variables, corresponding to the quantity of waste in each bin per each day, and control variables determining the quantity of material that is collected in the area each day and the routes for collecting vehicles. The objective function minimizes the sum of costs minus benefits. The developed decision model is integrated in a GIS-based Decision Support System (DSS). A case study related to the Cogoleto municipality is presented to show the effectiveness of the proposed model. From optimal results, it has been found that the net benefits of the optimized collection are about 2.5 times greater than the estimated current policy.

  19. Voronoi Diagram Based Optimization of Dynamic Reactive Power Sources

    SciTech Connect

    Huang, Weihong; Sun, Kai; Qi, Junjian; Xu, Yan

    2015-01-01

    Dynamic var sources can effectively mitigate fault-induced delayed voltage recovery (FIDVR) issues or even voltage collapse. This paper proposes a new approach to optimization of the sizes of dynamic var sources at candidate locations by a Voronoi diagram based algorithm. It first disperses sample points of potential solutions in a searching space, evaluates a cost function at each point by barycentric interpolation for the subspaces around the point, and then constructs a Voronoi diagram about cost function values over the entire space. Accordingly, the final optimal solution can be obtained. Case studies on the WSCC 9-bus system and NPCC 140-bus system have validated that the new approach can quickly identify the boundary of feasible solutions in searching space and converge to the global optimal solution.

  20. Multiobjective Optimization of Low-Energy Trajectories Using Optimal Control on Dynamical Channels

    NASA Technical Reports Server (NTRS)

    Coffee, Thomas M.; Anderson, Rodney L.; Lo, Martin W.

    2011-01-01

    We introduce a computational method to design efficient low-energy trajectories by extracting initial solutions from dynamical channels formed by invariant manifolds, and improving these solutions through variational optimal control. We consider trajectories connecting two unstable periodic orbits in the circular restricted 3-body problem (CR3BP). Our method leverages dynamical channels to generate a range of solutions, and approximates the areto front for impulse and time of flight through a multiobjective optimization of these solutions based on primer vector theory. We demonstrate the application of our method to a libration orbit transfer in the Earth-Moon system.

  1. Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

    NASA Astrophysics Data System (ADS)

    Chen, Wei

    2015-07-01

    In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

  2. Dynamic characterization of bolted joints using FRF decoupling and optimization

    NASA Astrophysics Data System (ADS)

    Tol, Şerife; O¨zgu¨ven, H. Nevzat

    2015-03-01

    Mechanical connections play a significant role in predicting dynamic characteristics of assembled structures. Therefore, equivalent dynamic models for joints are needed. Due to the complexity of joints, it is difficult to describe joint dynamics with analytical models. Reliable models are generally obtained using experimental measurements. In this paper an experimental identification method based on FRF decoupling and optimization algorithm is proposed for modeling joints. In the method the FRFs of two substructures connected with a joint are measured, while the FRFs of the substructures are obtained numerically or experimentally. Then the joint properties are calculated in terms of translational, rotational and cross-coupling stiffness and damping values by using FRF decoupling. In order to eliminate the numerical errors associated with matrix inversion an optimization algorithm is used to update the joint values obtained from FRF decoupling. The validity of the proposed method is demonstrated with experimental studies with bolted joints.

  3. Optimal filtering correction for marine dynamical positioning control system

    NASA Astrophysics Data System (ADS)

    Veremey, Evgeny; Sotnikova, Margarita

    2016-12-01

    The paper focuses on the problem of control law optimization for marine vessels working in a dynamical positioning (DP) regime. The approach proposed here is based on the use of a special unified multipurpose control law structure constructed on the basis of nonlinear asymptotic observers, that allows the decoupling of a synthesis into simpler particular optimization problems. The primary reason for the observers is to restore deficient information concerning the unmeasured velocities of the vessel. Using a number of separate items in addition to the observers, it is possible to achieve desirable dynamical features of the closed loop connection. The most important feature is the so-called dynamical corrector, and this paper is therefore devoted to solving its optimal synthesis in marine vessels controlled by DP systems under the action of sea wave disturbances. The problem involves the need for minimal intensity of the control action determined by high frequency sea wave components. A specialized approach for designing the dynamical corrector is proposed and the applicability and effectiveness of the approach are illustrated using a practical example of underwater DP system synthesis.

  4. Optimizing legacy molecular dynamics software with directive-based offload

    SciTech Connect

    Michael Brown, W.; Carrillo, Jan-Michael Y.; Gavhane, Nitin; Thakkar, Foram M.; Plimpton, Steven J.

    2015-05-14

    The directive-based programming models are one solution for exploiting many-core coprocessors to increase simulation rates in molecular dynamics. They offer the potential to reduce code complexity with offload models that can selectively target computations to run on the CPU, the coprocessor, or both. In our paper, we describe modifications to the LAMMPS molecular dynamics code to enable concurrent calculations on a CPU and coprocessor. We also demonstrate that standard molecular dynamics algorithms can run efficiently on both the CPU and an x86-based coprocessor using the same subroutines. As a consequence, we demonstrate that code optimizations for the coprocessor also result in speedups on the CPU; in extreme cases up to 4.7X. We provide results for LAMMAS benchmarks and for production molecular dynamics simulations using the Stampede hybrid supercomputer with both Intel (R) Xeon Phi (TM) coprocessors and NVIDIA GPUs: The optimizations presented have increased simulation rates by over 2X for organic molecules and over 7X for liquid crystals on Stampede. The optimizations are available as part of the "Intel package" supplied with LAMMPS. (C) 2015 Elsevier B.V. All rights reserved.

  5. Optimizing legacy molecular dynamics software with directive-based offload

    DOE PAGES

    Michael Brown, W.; Carrillo, Jan-Michael Y.; Gavhane, Nitin; ...

    2015-05-14

    The directive-based programming models are one solution for exploiting many-core coprocessors to increase simulation rates in molecular dynamics. They offer the potential to reduce code complexity with offload models that can selectively target computations to run on the CPU, the coprocessor, or both. In our paper, we describe modifications to the LAMMPS molecular dynamics code to enable concurrent calculations on a CPU and coprocessor. We also demonstrate that standard molecular dynamics algorithms can run efficiently on both the CPU and an x86-based coprocessor using the same subroutines. As a consequence, we demonstrate that code optimizations for the coprocessor also resultmore » in speedups on the CPU; in extreme cases up to 4.7X. We provide results for LAMMAS benchmarks and for production molecular dynamics simulations using the Stampede hybrid supercomputer with both Intel (R) Xeon Phi (TM) coprocessors and NVIDIA GPUs: The optimizations presented have increased simulation rates by over 2X for organic molecules and over 7X for liquid crystals on Stampede. The optimizations are available as part of the "Intel package" supplied with LAMMPS. (C) 2015 Elsevier B.V. All rights reserved.« less

  6. Adaptive optimal spectral range for dynamically changing scene

    NASA Astrophysics Data System (ADS)

    Pinsky, Ephi; Siman-tov, Avihay; Peles, David

    2012-06-01

    A novel multispectral video system that continuously optimizes both its spectral range channels and the exposure time of each channel autonomously, under dynamic scenes, varying from short range-clear scene to long range-poor visibility, is currently being developed. Transparency and contrast of high scattering medium of channels with spectral ranges in the near infrared is superior to the visible channels, particularly to the blue range. Longer wavelength spectral ranges that induce higher contrast are therefore favored. Images of 3 spectral channels are fused and displayed for (pseudo) color visualization, as an integrated high contrast video stream. In addition to the dynamic optimization of the spectral channels, optimal real-time exposure time is adjusted simultaneously and autonomously for each channel. A criterion of maximum average signal, derived dynamically from previous frames of the video stream is used (Patent Application - International Publication Number: WO2009/093110 A2, 30.07.2009). This configuration enables dynamic compatibility with the optimal exposure time of a dynamically changing scene. It also maximizes the signal to noise ratio and compensates each channel for the specified value of daylight reflections and sensors response for each spectral range. A possible implementation is a color video camera based on 4 synchronized, highly responsive, CCD imaging detectors, attached to a 4CCD dichroic prism and combined with a common, color corrected, lens. Principal Components Analysis (PCA) technique is then applied for real time "dimensional collapse" in color space, in order to select and fuse, for clear color visualization, the 3 most significant principal channels out of at least 4 characterized by high contrast and rich details in the image data.

  7. Optimization of industrial microorganisms: recent advances in synthetic dynamic regulators.

    PubMed

    Min, Byung Eun; Hwang, Hyun Gyu; Lim, Hyun Gyu; Jung, Gyoo Yeol

    2017-01-01

    Production of biochemicals by industrial fermentation using microorganisms requires maintaining cellular production capacity, because maximal productivity is economically important. High-productivity microbial strains can be developed using static engineering, but these may not maintain maximal productivity throughout the culture period as culture conditions and cell states change dynamically. Additionally, economic reasons limit heterologous protein expression using inducible promoters to prevent metabolic burden for commodity chemical and biofuel production. Recently, synthetic and systems biology has been used to design genetic circuits, precisely controlling gene expression or influencing genetic behavior toward a desired phenotype. Development of dynamic regulators can maintain cellular phenotype in a maximum production state in response to factors including cell concentration, oxygen, temperature, pH, and metabolites. Herein, we introduce dynamic regulators of industrial microorganism optimization and discuss metabolic flux fine control by dynamic regulators in response to metabolites or extracellular stimuli, robust production systems, and auto-induction systems using quorum sensing.

  8. Aerodynamic design optimization using sensitivity analysis and computational fluid dynamics

    NASA Technical Reports Server (NTRS)

    Baysal, Oktay; Eleshaky, Mohamed E.

    1991-01-01

    A new and efficient method is presented for aerodynamic design optimization, which is based on a computational fluid dynamics (CFD)-sensitivity analysis algorithm. The method is applied to design a scramjet-afterbody configuration for an optimized axial thrust. The Euler equations are solved for the inviscid analysis of the flow, which in turn provides the objective function and the constraints. The CFD analysis is then coupled with the optimization procedure that uses a constrained minimization method. The sensitivity coefficients, i.e. gradients of the objective function and the constraints, needed for the optimization are obtained using a quasi-analytical method rather than the traditional brute force method of finite difference approximations. During the one-dimensional search of the optimization procedure, an approximate flow analysis (predicted flow) based on a first-order Taylor series expansion is used to reduce the computational cost. Finally, the sensitivity of the optimum objective function to various design parameters, which are kept constant during the optimization, is computed to predict new optimum solutions. The flow analysis of the demonstrative example are compared with the experimental data. It is shown that the method is more efficient than the traditional methods.

  9. SPOT: an optimization software for dynamic observation programming

    NASA Astrophysics Data System (ADS)

    Lagrange, Anne-Marie; Rubini, Pascal; Brauner-Vettier, Nadia; Cambazard, Hadrien; Catusse, Nicolas; Lemaire, Pierre; Baude, Laurence

    2016-07-01

    The surveys dedicated to the search for extrasolar planets with the recently installed extreme-AO, high contrast Planet Imagers generally include hundreds of targets, to be observed sometimes repeatedly, generally in Angular Differential Imaging Mode. Each observation has to fulfill several time-dependent constraints, which makes a manual elaboration of an optimized planning impossible. We have developed a software (SPOT), an easy to use tool with graphical interface that allows both long term (months, years) and dynamic (nights) optimized scheduling of such surveys, taking into account all relevant constraints. Tests show that excellent schedules and high filling efficiencies can be obtained with execution times compatible with real-time scheduling, making possible to take in account complex constraints and to dynamically adapt planning to unexpected circumstances even during their execution. Moreover, such a tool is very valuable during survey preparations to build target lists and calendars. SPOT could be easily adapted for scheduling observations other instruments or telescopes.

  10. Rethinking design parameters in the search for optimal dynamic seating.

    PubMed

    Pynt, Jennifer

    2015-04-01

    Dynamic seating design purports to lessen damage incurred during sedentary occupations by increasing sitter movement while modifying muscle activity. Dynamic sitting is currently defined by O'Sullivan et al. ( 2013a) as relating to 'the increased motion in sitting which is facilitated by the use of specific chairs or equipment' (p. 628). Yet the evidence is conflicting that dynamic seating creates variation in the sitter's lumbar posture or muscle activity with the overall consensus being that current dynamic seating design fails to fulfill its goals. Research is needed to determine if a new generation of chairs requiring active sitter involvement fulfills the goals of dynamic seating and aids cardio/metabolic health. This paper summarises the pursuit of knowledge regarding optimal seated spinal posture and seating design. Four new forms of dynamic seating encouraging active sitting are discussed. These are 1) The Core-flex with a split seatpan to facilitate a walking action while seated 2) the Duo balans requiring body action to create rocking 3) the Back App and 4) Locus pedestal stools both using the sitter's legs to drive movement. Unsubstantiated claims made by the designers of these new forms of dynamic seating are outlined. Avenues of research are suggested to validate designer claims and investigate whether these designs fulfill the goals of dynamic seating and assist cardio/metabolic health. Should these claims be efficacious then a new definition of dynamic sitting is suggested; 'Sitting in which the action is provided by the sitter, while the dynamic mechanism of the chair accommodates that action'.

  11. Neighboring extremals of dynamic optimization problems with path equality constraints

    NASA Technical Reports Server (NTRS)

    Lee, A. Y.

    1988-01-01

    Neighboring extremals of dynamic optimization problems with path equality constraints and with an unknown parameter vector are considered in this paper. With some simplifications, the problem is reduced to solving a linear, time-varying two-point boundary-value problem with integral path equality constraints. A modified backward sweep method is used to solve this problem. Two example problems are solved to illustrate the validity and usefulness of the solution technique.

  12. Optimally combining dynamical decoupling and quantum error correction.

    PubMed

    Paz-Silva, Gerardo A; Lidar, D A

    2013-01-01

    Quantum control and fault-tolerant quantum computing (FTQC) are two of the cornerstones on which the hope of realizing a large-scale quantum computer is pinned, yet only preliminary steps have been taken towards formalizing the interplay between them. Here we explore this interplay using the powerful strategy of dynamical decoupling (DD), and show how it can be seamlessly and optimally integrated with FTQC. To this end we show how to find the optimal decoupling generator set (DGS) for various subspaces relevant to FTQC, and how to simultaneously decouple them. We focus on stabilizer codes, which represent the largest contribution to the size of the DGS, showing that the intuitive choice comprising the stabilizers and logical operators of the code is in fact optimal, i.e., minimizes a natural cost function associated with the length of DD sequences. Our work brings hybrid DD-FTQC schemes, and their potentially considerable advantages, closer to realization.

  13. Confronting dynamics and uncertainty in optimal decision making for conservation

    NASA Astrophysics Data System (ADS)

    Williams, Byron K.; Johnson, Fred A.

    2013-06-01

    The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a

  14. Confronting dynamics and uncertainty in optimal decision making for conservation

    USGS Publications Warehouse

    Williams, Byron K.; Johnson, Fred A.

    2013-01-01

    The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a

  15. Coarse-graining two-dimensional turbulence via dynamical optimization

    NASA Astrophysics Data System (ADS)

    Turkington, Bruce; Chen, Qian-Yong; Thalabard, Simon

    2016-10-01

    A model reduction technique based on an optimization principle is employed to coarse-grain inviscid, incompressible fluid dynamics in two dimensions. In this reduction the spectrally-truncated vorticity equation defines the microdynamics, while the macroscopic state space consists of quasi-equilibrium trial probability densities on the microscopic phase space, which are parameterized by the means and variances of the low modes of the vorticity. A macroscopic path therefore represents a coarse-grained approximation to the evolution of a nonequilibrium ensemble of microscopic solutions. Closure in terms of the vector of resolved variables, namely, the means and variances of the low modes, is achieved by minimizing over all feasible paths the time integral of their mean-squared residual with respect to the Liouville equation. The equations governing the optimal path are deduced from Hamilton-Jacobi theory. The coarse-grained dynamics derived by this optimization technique contains a scale-dependent eddy viscosity, modified nonlinear interactions between the low mode means, and a nonlinear coupling between the mean and variance of each low mode. The predictive skill of this optimal closure is validated quantitatively by comparing it against direct numerical simulations. These tests show that good agreement is achieved without adjusting any closure parameters.

  16. Designing Area Optimized Application-Specific Network-On-Chip Architectures while Providing Hard QoS Guarantees

    PubMed Central

    Khawaja, Sajid Gul; Mushtaq, Mian Hamza; Khan, Shoab A.; Akram, M. Usman; Jamal, Habib ullah

    2015-01-01

    With the increase of transistors' density, popularity of System on Chip (SoC) has increased exponentially. As a communication module for SoC, Network on Chip (NoC) framework has been adapted as its backbone. In this paper, we propose a methodology for designing area-optimized application specific NoC while providing hard Quality of Service (QoS) guarantees for real time flows. The novelty of the proposed system lies in derivation of a Mixed Integer Linear Programming model which is then used to generate a resource optimal Network on Chip (NoC) topology and architecture while considering traffic and QoS requirements. We also present the micro-architectural design features used for enabling traffic and latency guarantees and discuss how the solution adapts for dynamic variations in the application traffic. The paper highlights the effectiveness of proposed method by generating resource efficient NoC solutions for both industrial and benchmark applications. The area-optimized results are generated in few seconds by proposed technique, without resorting to heuristics, even for an application with 48 traffic flows. PMID:25898016

  17. Optimization of Dynamic Aperture of PEP-X Baseline Design

    SciTech Connect

    Wang, Min-Huey; Cai, Yunhai; Nosochkov, Yuri; /SLAC

    2010-08-23

    SLAC is developing a long-range plan to transfer the evolving scientific programs at SSRL from the SPEAR3 light source to a much higher performing photon source. Storage ring design is one of the possibilities that would be housed in the 2.2-km PEP-II tunnel. The design goal of PEPX storage ring is to approach an optimal light source design with horizontal emittance less than 100 pm and vertical emittance of 8 pm to reach the diffraction limit of 1-{angstrom} x-ray. The low emittance design requires a lattice with strong focusing leading to high natural chromaticity and therefore to strong sextupoles. The latter caused reduction of dynamic aperture. The dynamic aperture requirement for horizontal injection at injection point is about 10 mm. In order to achieve the desired dynamic aperture the transverse non-linearity of PEP-X is studied. The program LEGO is used to simulate the particle motion. The technique of frequency map is used to analyze the nonlinear behavior. The effect of the non-linearity is tried to minimize at the given constrains of limited space. The details and results of dynamic aperture optimization are discussed in this paper.

  18. Human opinion dynamics: An inspiration to solve complex optimization problems

    PubMed Central

    Kaur, Rishemjit; Kumar, Ritesh; Bhondekar, Amol P.; Kapur, Pawan

    2013-01-01

    Human interactions give rise to the formation of different kinds of opinions in a society. The study of formations and dynamics of opinions has been one of the most important areas in social physics. The opinion dynamics and associated social structure leads to decision making or so called opinion consensus. Opinion formation is a process of collective intelligence evolving from the integrative tendencies of social influence with the disintegrative effects of individualisation, and therefore could be exploited for developing search strategies. Here, we demonstrate that human opinion dynamics can be utilised to solve complex mathematical optimization problems. The results have been compared with a standard algorithm inspired from bird flocking behaviour and the comparison proves the efficacy of the proposed approach in general. Our investigation may open new avenues towards understanding the collective decision making. PMID:24141795

  19. Optimal forwarding ratio on dynamical networks with heterogeneous mobility

    NASA Astrophysics Data System (ADS)

    Gan, Yu; Tang, Ming; Yang, Hanxin

    2013-05-01

    Since the discovery of non-Poisson statistics of human mobility trajectories, more attention has been paid to understand the role of these patterns in different dynamics. In this study, we first introduce the heterogeneous mobility of mobile agents into dynamical networks, and then investigate packet forwarding strategy on the heterogeneous dynamical networks. We find that the faster speed and the higher proportion of high-speed agents can enhance the network throughput and reduce the mean traveling time in random forwarding. A hierarchical structure in the dependence of high-speed is observed: the network throughput remains unchanged at small and large high-speed value. It is also interesting to find that a slightly preferential forwarding to high-speed agents can maximize the network capacity. Through theoretical analysis and numerical simulations, we show that the optimal forwarding ratio stems from the local structural heterogeneity of low-speed agents.

  20. Optimized Uncertainty Quantification Algorithm Within a Dynamic Event Tree Framework

    SciTech Connect

    J. W. Nielsen; Akira Tokuhiro; Robert Hiromoto

    2014-06-01

    Methods for developing Phenomenological Identification and Ranking Tables (PIRT) for nuclear power plants have been a useful tool in providing insight into modelling aspects that are important to safety. These methods have involved expert knowledge with regards to reactor plant transients and thermal-hydraulic codes to identify are of highest importance. Quantified PIRT provides for rigorous method for quantifying the phenomena that can have the greatest impact. The transients that are evaluated and the timing of those events are typically developed in collaboration with the Probabilistic Risk Analysis. Though quite effective in evaluating risk, traditional PRA methods lack the capability to evaluate complex dynamic systems where end states may vary as a function of transition time from physical state to physical state . Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. A limitation of DPRA is its potential for state or combinatorial explosion that grows as a function of the number of components; as well as, the sampling of transition times from state-to-state of the entire system. This paper presents a method for performing QPIRT within a dynamic event tree framework such that timing events which result in the highest probabilities of failure are captured and a QPIRT is performed simultaneously while performing a discrete dynamic event tree evaluation. The resulting simulation results in a formal QPIRT for each end state. The use of dynamic event trees results in state explosion as the number of possible component states increases. This paper utilizes a branch and bound algorithm to optimize the solution of the dynamic event trees. The paper summarizes the methods used to implement the branch-and-bound algorithm in solving the discrete dynamic event trees.

  1. Fluid-dynamic design optimization of hydraulic proportional directional valves

    NASA Astrophysics Data System (ADS)

    Amirante, Riccardo; Catalano, Luciano Andrea; Poloni, Carlo; Tamburrano, Paolo

    2014-10-01

    This article proposes an effective methodology for the fluid-dynamic design optimization of the sliding spool of a hydraulic proportional directional valve: the goal is the minimization of the flow force at a prescribed flow rate, so as to reduce the required opening force while keeping the operation features unchanged. A full three-dimensional model of the flow field within the valve is employed to accurately predict the flow force acting on the spool. A theoretical analysis, based on both the axial momentum equation and flow simulations, is conducted to define the design parameters, which need to be properly selected in order to reduce the flow force without significantly affecting the flow rate. A genetic algorithm, coupled with a computational fluid dynamics flow solver, is employed to minimize the flow force acting on the valve spool at the maximum opening. A comparison with a typical single-objective optimization algorithm is performed to evaluate performance and effectiveness of the employed genetic algorithm. The optimized spool develops a maximum flow force which is smaller than that produced by the commercially available valve, mainly due to some major modifications occurring in the discharge section. Reducing the flow force and thus the electromagnetic force exerted by the solenoid actuators allows the operational range of direct (single-stage) driven valves to be enlarged.

  2. Optimizing spread dynamics on graphs by message passing

    NASA Astrophysics Data System (ADS)

    Altarelli, F.; Braunstein, A.; Dall'Asta, L.; Zecchina, R.

    2013-09-01

    Cascade processes are responsible for many important phenomena in natural and social sciences. Simple models of irreversible dynamics on graphs, in which nodes activate depending on the state of their neighbors, have been successfully applied to describe cascades in a large variety of contexts. Over the past decades, much effort has been devoted to understanding the typical behavior of the cascades arising from initial conditions extracted at random from some given ensemble. However, the problem of optimizing the trajectory of the system, i.e. of identifying appropriate initial conditions to maximize (or minimize) the final number of active nodes, is still considered to be practically intractable, with the only exception being models that satisfy a sort of diminishing returns property called submodularity. Submodular models can be approximately solved by means of greedy strategies, but by definition they lack cooperative characteristics which are fundamental in many real systems. Here we introduce an efficient algorithm based on statistical physics for the optimization of trajectories in cascade processes on graphs. We show that for a wide class of irreversible dynamics, even in the absence of submodularity, the spread optimization problem can be solved efficiently on large networks. Analytic and algorithmic results on random graphs are complemented by the solution of the spread maximization problem on a real-world network (the Epinions consumer reviews network).

  3. Exposure time optimization for highly dynamic star trackers.

    PubMed

    Wei, Xinguo; Tan, Wei; Li, Jian; Zhang, Guangjun

    2014-03-11

    Under highly dynamic conditions, the star-spots on the image sensor of a star tracker move across many pixels during the exposure time, which will reduce star detection sensitivity and increase star location errors. However, this kind of effect can be compensated well by setting an appropriate exposure time. This paper focuses on how exposure time affects the star tracker under highly dynamic conditions and how to determine the most appropriate exposure time for this case. Firstly, the effect of exposure time on star detection sensitivity is analyzed by establishing the dynamic star-spot imaging model. Then the star location error is deduced based on the error analysis of the sub-pixel centroiding algorithm. Combining these analyses, the effect of exposure time on attitude accuracy is finally determined. Some simulations are carried out to validate these effects, and the results show that there are different optimal exposure times for different angular velocities of a star tracker with a given configuration. In addition, the results of night sky experiments using a real star tracker agree with the simulation results. The summarized regularities in this paper should prove helpful in the system design and dynamic performance evaluation of the highly dynamic star trackers.

  4. Dynamic imaging model and parameter optimization for a star tracker.

    PubMed

    Yan, Jinyun; Jiang, Jie; Zhang, Guangjun

    2016-03-21

    Under dynamic conditions, star spots move across the image plane of a star tracker and form a smeared star image. This smearing effect increases errors in star position estimation and degrades attitude accuracy. First, an analytical energy distribution model of a smeared star spot is established based on a line segment spread function because the dynamic imaging process of a star tracker is equivalent to the static imaging process of linear light sources. The proposed model, which has a clear physical meaning, explicitly reflects the key parameters of the imaging process, including incident flux, exposure time, velocity of a star spot in an image plane, and Gaussian radius. Furthermore, an analytical expression of the centroiding error of the smeared star spot is derived using the proposed model. An accurate and comprehensive evaluation of centroiding accuracy is obtained based on the expression. Moreover, analytical solutions of the optimal parameters are derived to achieve the best performance in centroid estimation. Finally, we perform numerical simulations and a night sky experiment to validate the correctness of the dynamic imaging model, the centroiding error expression, and the optimal parameters.

  5. Accelerated monotonic convergence of optimal control over quantum dynamics.

    PubMed

    Ho, Tak-San; Rabitz, Herschel

    2010-08-01

    The control of quantum dynamics is often concerned with finding time-dependent optimal control fields that can take a system from an initial state to a final state to attain the desired value of an observable. This paper presents a general method for formulating monotonically convergent algorithms to iteratively improve control fields. The formulation is based on a two-point boundary-value quantum control paradigm (TBQCP) expressed as a nonlinear integral equation of the first kind arising from dynamical invariant tracking control. TBQCP is shown to be related to various existing techniques, including local control theory, the Krotov method, and optimal control theory. Several accelerated monotonic convergence schemes for iteratively computing control fields are derived based on TBQCP. Numerical simulations are compared with the Krotov method showing that the new TBQCP schemes are efficient and remain monotonically convergent over a wide range of the iteration step parameters and the control pulse lengths, which is attributable to the trap-free character of the transition probability quantum dynamics control landscape.

  6. Maximum, minimum, and optimal mutation rates in dynamic environments

    NASA Astrophysics Data System (ADS)

    Ancliff, Mark; Park, Jeong-Man

    2009-12-01

    We analyze the dynamics of the parallel mutation-selection quasispecies model with a changing environment. For an environment with the sharp-peak fitness function in which the most fit sequence changes by k spin flips every period T , we find analytical expressions for the minimum and maximum mutation rates for which a quasispecies can survive, valid in the limit of large sequence size. We find an asymptotic solution in which the quasispecies population changes periodically according to the periodic environmental change. In this state we compute the mutation rate that gives the optimal mean fitness over a period. We find that the optimal mutation rate per genome, k/T , is independent of genome size, a relationship which is observed across broad groups of real organisms.

  7. Morphing-Based Shape Optimization in Computational Fluid Dynamics

    NASA Astrophysics Data System (ADS)

    Rousseau, Yannick; Men'Shov, Igor; Nakamura, Yoshiaki

    In this paper, a Morphing-based Shape Optimization (MbSO) technique is presented for solving Optimum-Shape Design (OSD) problems in Computational Fluid Dynamics (CFD). The proposed method couples Free-Form Deformation (FFD) and Evolutionary Computation, and, as its name suggests, relies on the morphing of shape and computational domain, rather than direct shape parameterization. Advantages of the FFD approach compared to traditional parameterization are first discussed. Then, examples of shape and grid deformations by FFD are presented. Finally, the MbSO approach is illustrated and applied through an example: the design of an airfoil for a future Mars exploration airplane.

  8. Dynamic stochastic optimization models for air traffic flow management

    NASA Astrophysics Data System (ADS)

    Mukherjee, Avijit

    This dissertation presents dynamic stochastic optimization models for Air Traffic Flow Management (ATFM) that enables decisions to adapt to new information on evolving capacities of National Airspace System (NAS) resources. Uncertainty is represented by a set of capacity scenarios, each depicting a particular time-varying capacity profile of NAS resources. We use the concept of a scenario tree in which multiple scenarios are possible initially. Scenarios are eliminated as possibilities in a succession of branching points, until the specific scenario that will be realized on a particular day is known. Thus the scenario tree branching provides updated information on evolving scenarios, and allows ATFM decisions to be re-addressed and revised. First, we propose a dynamic stochastic model for a single airport ground holding problem (SAGHP) that can be used for planning Ground Delay Programs (GDPs) when there is uncertainty about future airport arrival capacities. Ground delays of non-departed flights can be revised based on updated information from scenario tree branching. The problem is formulated so that a wide range of objective functions, including non-linear delay cost functions and functions that reflect equity concerns can be optimized. Furthermore, the model improves on existing practice by ensuring efficient use of available capacity without necessarily exempting long-haul flights. Following this, we present a methodology and optimization models that can be used for decentralized decision making by individual airlines in the GDP planning process, using the solutions from the stochastic dynamic SAGHP. Airlines are allowed to perform cancellations, and re-allocate slots to remaining flights by substitutions. We also present an optimization model that can be used by the FAA, after the airlines perform cancellation and substitutions, to re-utilize vacant arrival slots that are created due to cancellations. Finally, we present three stochastic integer programming

  9. Optimized dynamical decoupling for power-law noise spectra

    SciTech Connect

    Pasini, S.; Uhrig, G. S.

    2010-01-15

    We analyze the suppression of decoherence by means of dynamical decoupling in the pure-dephasing spin-boson model for baths with power law spectra. The sequence of ideal pi pulses is optimized according to the power of the bath. We expand the decoherence function and separate the canceling divergences from the relevant terms. The proposed sequence is chosen to be the one minimizing the decoherence function. By construction, it provides the best performance. We analytically derive the conditions that must be satisfied. The resulting equations are solved numerically. The solutions are very close to the Carr-Purcell-Meiboom-Gill sequence for a soft cutoff of the bath while they approach the Uhrig dynamical-decoupling sequence as the cutoff becomes harder.

  10. Dynamic Simulation and Optimization of Nuclear Hydrogen Production Systems

    SciTech Connect

    Paul I. Barton; Mujid S. Kaximi; Georgios Bollas; Patricio Ramirez Munoz

    2009-07-31

    This project is part of a research effort to design a hydrogen plant and its interface with a nuclear reactor. This project developed a dynamic modeling, simulation and optimization environment for nuclear hydrogen production systems. A hybrid discrete/continuous model captures both the continuous dynamics of the nuclear plant, the hydrogen plant, and their interface, along with discrete events such as major upsets. This hybrid model makes us of accurate thermodynamic sub-models for the description of phase and reaction equilibria in the thermochemical reactor. Use of the detailed thermodynamic models will allow researchers to examine the process in detail and have confidence in the accurary of the property package they use.

  11. Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

    PubMed Central

    De Paris, Renata; Quevedo, Christian V.; Ruiz, Duncan D.; Norberto de Souza, Osmar; Barros, Rodrigo C.

    2015-01-01

    Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand. PMID:25873944

  12. Clustering molecular dynamics trajectories for optimizing docking experiments.

    PubMed

    De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C

    2015-01-01

    Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

  13. Optimization of dynamic measurement of receptor kinetics by wavelet denoising.

    PubMed

    Alpert, Nathaniel M; Reilhac, Anthonin; Chio, Tat C; Selesnick, Ivan

    2006-04-01

    The most important technical limitation affecting dynamic measurements with PET is low signal-to-noise ratio (SNR). Several reports have suggested that wavelet processing of receptor kinetic data in the human brain can improve the SNR of parametric images of binding potential (BP). However, it is difficult to fully assess these reports because objective standards have not been developed to measure the tradeoff between accuracy (e.g. degradation of resolution) and precision. This paper employs a realistic simulation method that includes all major elements affecting image formation. The simulation was used to derive an ensemble of dynamic PET ligand (11C-raclopride) experiments that was subjected to wavelet processing. A method for optimizing wavelet denoising is presented and used to analyze the simulated experiments. Using optimized wavelet denoising, SNR of the four-dimensional PET data increased by about a factor of two and SNR of three-dimensional BP maps increased by about a factor of 1.5. Analysis of the difference between the processed and unprocessed means for the 4D concentration data showed that more than 80% of voxels in the ensemble mean of the wavelet processed data deviated by less than 3%. These results show that a 1.5x increase in SNR can be achieved with little degradation of resolution. This corresponds to injecting about twice the radioactivity, a maneuver that is not possible in human studies without saturating the PET camera and/or exposing the subject to more than permitted radioactivity.

  14. Data-driven optimization of dynamic reconfigurable systems of systems.

    SciTech Connect

    Tucker, Conrad S.; Eddy, John P.

    2010-11-01

    This report documents the results of a Strategic Partnership (aka University Collaboration) LDRD program between Sandia National Laboratories and the University of Illinois at Urbana-Champagne. The project is titled 'Data-Driven Optimization of Dynamic Reconfigurable Systems of Systems' and was conducted during FY 2009 and FY 2010. The purpose of this study was to determine and implement ways to incorporate real-time data mining and information discovery into existing Systems of Systems (SoS) modeling capabilities. Current SoS modeling is typically conducted in an iterative manner in which replications are carried out in order to quantify variation in the simulation results. The expense of many replications for large simulations, especially when considering the need for optimization, sensitivity analysis, and uncertainty quantification, can be prohibitive. In addition, extracting useful information from the resulting large datasets is a challenging task. This work demonstrates methods of identifying trends and other forms of information in datasets that can be used on a wide range of applications such as quantifying the strength of various inputs on outputs, identifying the sources of variation in the simulation, and potentially steering an optimization process for improved efficiency.

  15. Optimal control and cold war dynamics between plant and herbivore.

    PubMed

    Low, Candace; Ellner, Stephen P; Holden, Matthew H

    2013-08-01

    Herbivores eat the leaves that a plant needs for photosynthesis. However, the degree of antagonism between plant and herbivore may depend critically on the timing of their interactions and the intrinsic value of a leaf. We present a model that investigates whether and when the timing of plant defense and herbivore feeding activity can be optimized by evolution so that their interactions can move from antagonistic to neutral. We assume that temporal changes in environmental conditions will affect intrinsic leaf value, measured as potential carbon gain. Using optimal-control theory, we model herbivore evolution, first in response to fixed plant strategies and then under coevolutionary dynamics in which the plant also evolves in response to the herbivore. In the latter case, we solve for the evolutionarily stable strategies of plant defense induction and herbivore hatching rate under different ecological conditions. Our results suggest that the optimal strategies for both plant and herbivore are to avoid direct conflict. As long as the plant has the capability for moderately lethal defense, the herbivore will modify its hatching rate to avoid plant defenses, and the plant will never have to use them. Insights from this model offer a possible solution to the paradox of sublethal defenses and provide a mechanism for stable plant-herbivore interactions without the need for natural enemy control.

  16. A Formal Approach to Empirical Dynamic Model Optimization and Validation

    NASA Technical Reports Server (NTRS)

    Crespo, Luis G; Morelli, Eugene A.; Kenny, Sean P.; Giesy, Daniel P.

    2014-01-01

    A framework was developed for the optimization and validation of empirical dynamic models subject to an arbitrary set of validation criteria. The validation requirements imposed upon the model, which may involve several sets of input-output data and arbitrary specifications in time and frequency domains, are used to determine if model predictions are within admissible error limits. The parameters of the empirical model are estimated by finding the parameter realization for which the smallest of the margins of requirement compliance is as large as possible. The uncertainty in the value of this estimate is characterized by studying the set of model parameters yielding predictions that comply with all the requirements. Strategies are presented for bounding this set, studying its dependence on admissible prediction error set by the analyst, and evaluating the sensitivity of the model predictions to parameter variations. This information is instrumental in characterizing uncertainty models used for evaluating the dynamic model at operating conditions differing from those used for its identification and validation. A practical example based on the short period dynamics of the F-16 is used for illustration.

  17. Assessment of optimally filtered recent geodetic mean dynamic topographies

    NASA Astrophysics Data System (ADS)

    Siegismund, F.

    2013-01-01

    AbstractRecent geoids from the Gravity Recovery and Climate Experiment (GRACE) and the Gravity field and steady state Ocean Circulation Explorer satellite mission (GOCE) contain useful short-scale information for the construction of a geodetic ocean mean <span class="hlt">dynamic</span> topography (MDT). The geodetic MDT is obtained from subtracting the geoid from a mean sea surface (MSS) as measured by satellite altimetry. A gainful use of the MDT and an adequate assessment needs an <span class="hlt">optimal</span> filtering. This is accomplished here by defining a cutoff length scale dmax for the geoid and applying a Gaussian filter with half-width radius r on the MDT. A series of MDTs (GRACE, GOCE, and combined satellite-only (GOCO) solutions) is tested, using different sets of filter parameters dmax and r. <span class="hlt">Optimal</span> global and regional dependent filter parameters are estimated. To find <span class="hlt">optimal</span> parameters and to assess the resulting MDTs, the geostrophic surface currents induced by the filtered geodetic MDT are compared to corrected near-surface currents obtained from the Global Drifter Program (GDP). The global <span class="hlt">optimal</span> cutoff degree and order (d/o) dmax (half-width radius r of the spatial Gaussian filter) is 160 (1.1°) for GRACE; 180 (1.1-1.2°) for 1st releases of GOCE (time- and space-wise methods) and GOCO models; and 210 (1.0 degree) for 2nd and 3rd releases of GOCE and GOCO models. The cutoff d/o is generally larger (smaller) and the filter length smaller (larger) for regions with strong, small-scale (slow, broad scale) currents. The smallest deviations from the drifter data are obtained with the GOCO03s geoid model, although deviations of other models are only slightly higher.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014IJC....87.1000Q','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014IJC....87.1000Q"><span>Online <span class="hlt">optimal</span> tracking control of continuous-time linear systems with unknown <span class="hlt">dynamics</span> by using adaptive <span class="hlt">dynamic</span> programming</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Qin, Chunbin; Zhang, Huaguang; Luo, Yanhong</p> <p>2014-05-01</p> <p>In this paper, a novel theoretic formulation based on adaptive <span class="hlt">dynamic</span> programming (ADP) is developed to solve online the <span class="hlt">optimal</span> tracking problem of the continuous-time linear system with unknown <span class="hlt">dynamics</span>. First, the original system <span class="hlt">dynamics</span> and the reference trajectory <span class="hlt">dynamics</span> are transformed into an augmented system. Then, under the same performance index with the original system <span class="hlt">dynamics</span>, an augmented algebraic Riccati equation is derived. Furthermore, the solutions for the <span class="hlt">optimal</span> control problem of the augmented system are proven to be equal to the standard solutions for the <span class="hlt">optimal</span> tracking problem of the original system <span class="hlt">dynamics</span>. Moreover, a new online algorithm based on the ADP technique is presented to solve the <span class="hlt">optimal</span> tracking problem of the linear system with unknown system <span class="hlt">dynamics</span>. Finally, simulation results are given to verify the effectiveness of the theoretic results.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AcAau.123...51H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AcAau.123...51H"><span>Campaign-level <span class="hlt">dynamic</span> network modelling for spaceflight logistics for the flexible path concept</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ho, Koki; de Weck, Olivier L.; Hoffman, Jeffrey A.; Shishko, Robert</p> <p>2016-06-01</p> <p>This paper develops a network <span class="hlt">optimization</span> formulation for <span class="hlt">dynamic</span> campaign-level space mission planning. Although many past space missions have been designed mainly from a mission-level perspective, a campaign-level perspective will be important for future space exploration. In order to find the <span class="hlt">optimal</span> campaign-level space transportation architecture, a <span class="hlt">mixed-integer</span> linear programming (MILP) formulation with a generalized multi-commodity flow and a time-expanded network is developed. Particularly, a new heuristics-based method, a partially static time-expanded network, is developed to provide a solution quickly. The developed method is applied to a case study containing human exploration of a near-Earth object (NEO) and Mars, related to the concept of the Flexible Path. The numerical results show that using the specific combinations of propulsion technologies, in-situ resource utilization (ISRU), and other space infrastructure elements can reduce the initial mass in low-Earth orbit (IMLEO) significantly. In addition, the case study results also show that we can achieve large IMLEO reduction by designing NEO and Mars missions together as a campaign compared with designing them separately owing to their common space infrastructure pre-deployment. This research will be an important step toward efficient and flexible campaign-level space mission planning.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PhDT.......372H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PhDT.......372H"><span>Approximate <span class="hlt">dynamic</span> programming based solutions for fixed-final-time <span class="hlt">optimal</span> control and <span class="hlt">optimal</span> switching</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heydari, Ali</p> <p></p> <p><span class="hlt">Optimal</span> solutions with neural networks (NN) based on an approximate <span class="hlt">dynamic</span> programming (ADP) framework for new classes of engineering and non-engineering problems and associated difficulties and challenges are investigated in this dissertation. In the enclosed eight papers, the ADP framework is utilized for solving fixed-final-time problems (also called terminal control problems) and problems with switching nature. An ADP based algorithm is proposed in Paper 1 for solving fixed-final-time problems with soft terminal constraint, in which, a single neural network with a single set of weights is utilized. Paper 2 investigates fixed-final-time problems with hard terminal constraints. The <span class="hlt">optimality</span> analysis of the ADP based algorithm for fixed-final-time problems is the subject of Paper 3, in which, it is shown that the proposed algorithm leads to the global <span class="hlt">optimal</span> solution providing certain conditions hold. Afterwards, the developments in Papers 1 to 3 are used to tackle a more challenging class of problems, namely, <span class="hlt">optimal</span> control of switching systems. This class of problems is divided into problems with fixed mode sequence (Papers 4 and 5) and problems with free mode sequence (Papers 6 and 7). Each of these two classes is further divided into problems with autonomous subsystems (Papers 4 and 6) and problems with controlled subsystems (Papers 5 and 7). Different ADP-based algorithms are developed and proofs of convergence of the proposed iterative algorithms are presented. Moreover, an extension to the developments is provided for online learning of the <span class="hlt">optimal</span> switching solution for problems with modeling uncertainty in Paper 8. Each of the theoretical developments is numerically analyzed using different real-world or benchmark problems.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015APS..MARJ29009E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015APS..MARJ29009E"><span><span class="hlt">Optimal</span> Control of Magnetization <span class="hlt">Dynamics</span> in Ferromagnetic Materials using TDDFT</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Elliott, Peter; Krieger, Kevin; Gross, E. K. U.</p> <p>2015-03-01</p> <p>Recently intense laser-field induced ultrafast demagnetization was observed in ab-initio simulations using Time-Dependent Density Functional Theory (TDDFT) for various ferromagnetic materials (Fe,Co,Ni). From a practical and technological viewpoint, it is useful if the induced <span class="hlt">dynamics</span> (e.g. of the total magnetic moment) are controllable. In this talk we apply <span class="hlt">optimal</span> control theory together with TDDFT calculations to tailor the intense laser pulses so as to achieve a particular outcome (e.g. maximize the total moment lost) while also including any required constraints (e.g pulse duration, pulse frequencies, maximum fluence, etc). Support from European Communities FP7, through the CRONOS project Grant No. 280879.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/835380','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/835380"><span>Performance Study and <span class="hlt">Dynamic</span> <span class="hlt">Optimization</span> Design for Thread Pool Systems</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Xu, Dongping</p> <p>2004-12-19</p> <p>Thread pools have been widely used by many multithreaded applications. However, the determination of the pool size according to the application behavior still remains problematic. To automate this process, in this thesis we have developed a set of performance metrics for quantitatively analyzing thread pool performance. For our experiments, we built a thread pool system which provides a general framework for thread pool research. Based on this simulation environment, we studied the performance impact brought by the thread pool on different multithreaded applications. Additionally, the correlations between internal characterizations of thread pools and their throughput were also examined. We then proposed and evaluated a heuristic algorithm to <span class="hlt">dynamically</span> determine the <span class="hlt">optimal</span> thread pool size. The simulation results show that this approach is effective in improving overall application performance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24398055','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24398055"><span>A PSO-based <span class="hlt">optimal</span> tuning strategy for constrained multivariable predictive controllers with model uncertainty.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Nery, Gesner A; Martins, Márcio A F; Kalid, Ricardo</p> <p>2014-03-01</p> <p>This paper describes the development of a method to <span class="hlt">optimally</span> tune constrained MPC algorithms with model uncertainty. The proposed method is formulated by using the worst-case control scenario, which is characterized by the Morari resiliency index and the condition number, and a given nonlinear multi-objective performance criterion. The resulting constrained <span class="hlt">mixed-integer</span> nonlinear <span class="hlt">optimization</span> problem is solved on the basis of a modified version of the particle swarm <span class="hlt">optimization</span> technique, because of its effectiveness in dealing with this kind of problem. The performance of this PSO-based tuning method is evaluated through its application to the well-known Shell heavy oil fractionator process.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26117286','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26117286"><span>Fast engineering <span class="hlt">optimization</span>: A novel highly effective control parameterization approach for industrial <span class="hlt">dynamic</span> processes.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Liu, Ping; Li, Guodong; Liu, Xinggao</p> <p>2015-09-01</p> <p>Control vector parameterization (CVP) is an important approach of the engineering <span class="hlt">optimization</span> for the industrial <span class="hlt">dynamic</span> processes. However, its major defect, the low <span class="hlt">optimization</span> efficiency caused by calculating the relevant differential equations in the generated nonlinear programming (NLP) problem repeatedly, limits its wide application in the engineering <span class="hlt">optimization</span> for the industrial <span class="hlt">dynamic</span> processes. A novel highly effective control parameterization approach, fast-CVP, is first proposed to improve the <span class="hlt">optimization</span> efficiency for industrial <span class="hlt">dynamic</span> processes, where the costate gradient formulae is employed and a fast approximate scheme is presented to solve the differential equations in <span class="hlt">dynamic</span> process simulation. Three well-known engineering <span class="hlt">optimization</span> benchmark problems of the industrial <span class="hlt">dynamic</span> processes are demonstrated as illustration. The research results show that the proposed fast approach achieves a fine performance that at least 90% of the computation time can be saved in contrast to the traditional CVP method, which reveals the effectiveness of the proposed fast engineering <span class="hlt">optimization</span> approach for the industrial <span class="hlt">dynamic</span> processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22314284','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22314284"><span>Geometry <span class="hlt">optimization</span> for micro-pressure sensor considering <span class="hlt">dynamic</span> interference</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Yu, Zhongliang; Zhao, Yulong Li, Lili; Tian, Bian; Li, Cun</p> <p>2014-09-15</p> <p>Presented is the geometry <span class="hlt">optimization</span> for piezoresistive absolute micro-pressure sensor. A figure of merit called the performance factor (PF) is defined as a quantitative index to describe the comprehensive performances of a sensor including sensitivity, resonant frequency, and acceleration interference. Three geometries are proposed through introducing islands and sensitive beams into typical flat diaphragm. The stress distributions of sensitive elements are analyzed by finite element method. Multivariate fittings based on ANSYS simulation results are performed to establish the equations about surface stress, deflection, and resonant frequency. <span class="hlt">Optimization</span> by MATLAB is carried out to determine the dimensions of the geometries. Convex corner undercutting is evaluated. Each PF of the three geometries with the determined dimensions is calculated and compared. Silicon bulk micromachining is utilized to fabricate the prototypes of the sensors. The outputs of the sensors under both static and <span class="hlt">dynamic</span> conditions are tested. Experimental results demonstrate the rationality of the defined performance factor and reveal that the geometry with quad islands presents the highest PF of 210.947 Hz{sup 1/4}. The favorable overall performances enable the sensor more suitable for altimetry.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27368775','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27368775"><span>Prediction uncertainty and <span class="hlt">optimal</span> experimental design for learning <span class="hlt">dynamical</span> systems.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Letham, Benjamin; Letham, Portia A; Rudin, Cynthia; Browne, Edward P</p> <p>2016-06-01</p> <p><span class="hlt">Dynamical</span> systems are frequently used to model biological systems. When these models are fit to data, it is necessary to ascertain the uncertainty in the model fit. Here, we present prediction deviation, a metric of uncertainty that determines the extent to which observed data have constrained the model's predictions. This is accomplished by solving an <span class="hlt">optimization</span> problem that searches for a pair of models that each provides a good fit for the observed data, yet has maximally different predictions. We develop a method for estimating a priori the impact that additional experiments would have on the prediction deviation, allowing the experimenter to design a set of experiments that would most reduce uncertainty. We use prediction deviation to assess uncertainty in a model of interferon-alpha inhibition of viral infection, and to select a sequence of experiments that reduces this uncertainty. Finally, we prove a theoretical result which shows that prediction deviation provides bounds on the trajectories of the underlying true model. These results show that prediction deviation is a meaningful metric of uncertainty that can be used for <span class="hlt">optimal</span> experimental design.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016Chaos..26f3110L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016Chaos..26f3110L"><span>Prediction uncertainty and <span class="hlt">optimal</span> experimental design for learning <span class="hlt">dynamical</span> systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Letham, Benjamin; Letham, Portia A.; Rudin, Cynthia; Browne, Edward P.</p> <p>2016-06-01</p> <p><span class="hlt">Dynamical</span> systems are frequently used to model biological systems. When these models are fit to data, it is necessary to ascertain the uncertainty in the model fit. Here, we present prediction deviation, a metric of uncertainty that determines the extent to which observed data have constrained the model's predictions. This is accomplished by solving an <span class="hlt">optimization</span> problem that searches for a pair of models that each provides a good fit for the observed data, yet has maximally different predictions. We develop a method for estimating a priori the impact that additional experiments would have on the prediction deviation, allowing the experimenter to design a set of experiments that would most reduce uncertainty. We use prediction deviation to assess uncertainty in a model of interferon-alpha inhibition of viral infection, and to select a sequence of experiments that reduces this uncertainty. Finally, we prove a theoretical result which shows that prediction deviation provides bounds on the trajectories of the underlying true model. These results show that prediction deviation is a meaningful metric of uncertainty that can be used for <span class="hlt">optimal</span> experimental design.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JSemi..36i4007Q','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JSemi..36i4007Q"><span>4500 V SPT+ IGBT <span class="hlt">optimization</span> on static and <span class="hlt">dynamic</span> losses</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Qingyun, Dai; Xiaoli, Tian; Wenliang, Zhang; Shuojin, Lu; Yangjun, Zhu</p> <p>2015-09-01</p> <p>This paper concerns the need for improving the static and <span class="hlt">dynamic</span> performance of the high voltage insulated gate bipolar transistor (HV IGBTs). A novel structure with a carrier stored layer on the cathode side, known as an enhanced planar IGBT of the 4500 V voltage class is investigated. With the adoption of a soft punch through (SPT) concept as the vertical structure and an enhanced planar concept as the top structure, signed as SPT+ IGBT, the simulation results indicate the turn-off switching waveform of the 4500 V SPT+ IGBT is soft and also realizes an improved trade-off relationship between on-state voltage drop (Von) and turn-off loss (Eoff) in comparison with the SPT IGBT. Attention is also paid to the influences caused by different carrier stored layer doping dose on static and <span class="hlt">dynamic</span> performances, to <span class="hlt">optimize</span> on-state and switching losses of SPT+ IGBT. Project supported by the National Major Science and Technology Special Project of China (No. 2011ZX02504-002).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19920072551&hterms=ascent+guidance&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dascent%2Bguidance','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19920072551&hterms=ascent+guidance&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dascent%2Bguidance"><span>An inverse <span class="hlt">dynamics</span> approach to trajectory <span class="hlt">optimization</span> and guidance for an aerospace plane</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lu, Ping</p> <p>1992-01-01</p> <p>The <span class="hlt">optimal</span> ascent problem for an aerospace planes is formulated as an <span class="hlt">optimal</span> inverse <span class="hlt">dynamic</span> problem. Both minimum-fuel and minimax type of performance indices are considered. Some important features of the <span class="hlt">optimal</span> trajectory and controls are used to construct a nonlinear feedback midcourse controller, which not only greatly simplifies the difficult constrained <span class="hlt">optimization</span> problem and yields improved solutions, but is also suited for onboard implementation. Robust ascent guidance is obtained by using combination of feedback compensation and onboard generation of control through the inverse <span class="hlt">dynamics</span> approach. Accurate orbital insertion can be achieved with near-<span class="hlt">optimal</span> control of the rocket through inverse <span class="hlt">dynamics</span> even in the presence of disturbances.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009LNCS.5745...74S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009LNCS.5745...74S"><span>Cost <span class="hlt">Optimization</span> Model for Business Applications in Virtualized Grid Environments</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Strebel, Jörg</p> <p></p> <p>The advent of Grid computing gives enterprises an ever increasing choice of computing options, yet research has so far hardly addressed the problem of mixing the different computing options in a cost-minimal fashion. The following paper presents a comprehensive cost model and a <span class="hlt">mixed</span> <span class="hlt">integer</span> <span class="hlt">optimization</span> model which can be used to minimize the IT expenditures of an enterprise and help in decision-making when to outsource certain business software applications. A sample scenario is analyzed and promising cost savings are demonstrated. Possible applications of the model to future research questions are outlined.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA513141','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA513141"><span>Route <span class="hlt">Optimization</span> for Multiple Searchers</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2009-09-04</p> <p>observation leads to the first linearization of SP1. Model SP1-L: Indices As in SP1. i number of looks on a target path ( i = 0, 1, ..., JT ). Sets and...ω)Uω (20) s.t. e−iα(1 + i − ie−α) + 1 α e−iα(e−α − 1) ∑ c,t∈T ζc,t(ω)αZc,t ≤ Uω ∀ ω, i (21) 12 (15)− (19) SP1-L is a <span class="hlt">mixed-integer</span> linear program...tolerances δ, δi ≥ 0, i = 0, 1, 2, .... 17 Step 0. Set the lower bound, ξ, on the <span class="hlt">optimal</span> value of SP1 to 0; set the upper bound, ξ, on the <span class="hlt">optimal</span> value of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012PhDT.......221L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012PhDT.......221L"><span><span class="hlt">Optimal</span> spatiotemporal reduced order modeling for nonlinear <span class="hlt">dynamical</span> systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>LaBryer, Allen</p> <p></p> <p>Proposed in this dissertation is a novel reduced order modeling (ROM) framework called <span class="hlt">optimal</span> spatiotemporal reduced order modeling (OPSTROM) for nonlinear <span class="hlt">dynamical</span> systems. The OPSTROM approach is a data-driven methodology for the synthesis of multiscale reduced order models (ROMs) which can be used to enhance the efficiency and reliability of under-resolved simulations for nonlinear <span class="hlt">dynamical</span> systems. In the context of nonlinear continuum <span class="hlt">dynamics</span>, the OPSTROM approach relies on the concept of embedding subgrid-scale models into the governing equations in order to account for the effects due to unresolved spatial and temporal scales. Traditional ROMs neglect these effects, whereas most other multiscale ROMs account for these effects in ways that are inconsistent with the underlying spatiotemporal statistical structure of the nonlinear <span class="hlt">dynamical</span> system. The OPSTROM framework presented in this dissertation begins with a general system of partial differential equations, which are modified for an under-resolved simulation in space and time with an arbitrary discretization scheme. Basic filtering concepts are used to demonstrate the manner in which residual terms, representing subgrid-scale <span class="hlt">dynamics</span>, arise with a coarse computational grid. Models for these residual terms are then developed by accounting for the underlying spatiotemporal statistical structure in a consistent manner. These subgrid-scale models are designed to provide closure by accounting for the <span class="hlt">dynamic</span> interactions between spatiotemporal macroscales and microscales which are otherwise neglected in a ROM. For a given resolution, the predictions obtained with the modified system of equations are <span class="hlt">optimal</span> (in a mean-square sense) as the subgrid-scale models are based upon principles of mean-square error minimization, conditional expectations and stochastic estimation. Methods are suggested for efficient model construction, appraisal, error measure, and implementation with a couple of well-known time</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22386785','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22386785"><span>Metamodeling and the Critic-based approach to multi-level <span class="hlt">optimization</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Werbos, Ludmilla; Kozma, Robert; Silva-Lugo, Rodrigo; Pazienza, Giovanni E; Werbos, Paul J</p> <p>2012-08-01</p> <p>Large-scale networks with hundreds of thousands of variables and constraints are becoming more and more common in logistics, communications, and distribution domains. Traditionally, the utility functions defined on such networks are <span class="hlt">optimized</span> using some variation of Linear Programming, such as <span class="hlt">Mixed</span> <span class="hlt">Integer</span> Programming (MIP). Despite enormous progress both in hardware (multiprocessor systems and specialized processors) and software (Gurobi) we are reaching the limits of what these tools can handle in real time. Modern logistic problems, for example, call for expanding the problem both vertically (from one day up to several days) and horizontally (combining separate solution stages into an integrated model). The complexity of such integrated models calls for alternative methods of solution, such as Approximate <span class="hlt">Dynamic</span> Programming (ADP), which provide a further increase in the performance necessary for the daily operation. In this paper, we present the theoretical basis and related experiments for solving the multistage decision problems based on the results obtained for shorter periods, as building blocks for the models and the solution, via Critic-Model-Action cycles, where various types of neural networks are combined with traditional MIP models in a unified <span class="hlt">optimization</span> system. In this system architecture, fast and simple feed-forward networks are trained to reasonably initialize more complicated recurrent networks, which serve as approximators of the value function (Critic). The combination of interrelated neural networks and <span class="hlt">optimization</span> modules allows for multiple queries for the same system, providing flexibility and <span class="hlt">optimizing</span> performance for large-scale real-life problems. A MATLAB implementation of our solution procedure for a realistic set of data and constraints shows promising results, compared to the iterative MIP approach.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4517946','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4517946"><span>New Statistical Learning Methods for Estimating <span class="hlt">Optimal</span> <span class="hlt">Dynamic</span> Treatment Regimes</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Zhao, Ying-Qi; Zeng, Donglin; Laber, Eric B.; Kosorok, Michael R.</p> <p>2014-01-01</p> <p><span class="hlt">Dynamic</span> treatment regimes (DTRs) are sequential decision rules for individual patients that can adapt over time to an evolving illness. The goal is to accommodate heterogeneity among patients and find the DTR which will produce the best long term outcome if implemented. We introduce two new statistical learning methods for estimating the <span class="hlt">optimal</span> DTR, termed backward outcome weighted learning (BOWL), and simultaneous outcome weighted learning (SOWL). These approaches convert individualized treatment selection into an either sequential or simultaneous classification problem, and can thus be applied by modifying existing machine learning techniques. The proposed methods are based on directly maximizing over all DTRs a nonparametric estimator of the expected long-term outcome; this is fundamentally different than regression-based methods, for example Q-learning, which indirectly attempt such maximization and rely heavily on the correctness of postulated regression models. We prove that the resulting rules are consistent, and provide finite sample bounds for the errors using the estimated rules. Simulation results suggest the proposed methods produce superior DTRs compared with Q-learning especially in small samples. We illustrate the methods using data from a clinical trial for smoking cessation. PMID:26236062</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23625909','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23625909"><span><span class="hlt">Optimization</span> of conventional water treatment plant using <span class="hlt">dynamic</span> programming.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Mostafa, Khezri Seyed; Bahareh, Ghafari; Elahe, Dadvar; Pegah, Dadras</p> <p>2015-12-01</p> <p>In this research, the mathematical models, indicating the capability of various units, such as rapid mixing, coagulation and flocculation, sedimentation, and the rapid sand filtration are used. Moreover, cost functions were used for the formulation of conventional water and wastewater treatment plant by applying Clark's formula (Clark, 1982). Also, by applying <span class="hlt">dynamic</span> programming algorithm, it is easy to design a conventional treatment system with minimal cost. The application of the model for a case reduced the annual cost. This reduction was approximately in the range of 4.5-9.5% considering variable limitations. Sensitivity analysis and prediction of system's feedbacks were performed for different alterations in proportion from parameters <span class="hlt">optimized</span> amounts. The results indicated (1) that the objective function is more sensitive to design flow rate (Q), (2) the variations in the alum dosage (A), and (3) the sand filter head loss (H). Increasing the inflow by 20%, the total annual cost would increase to about 12.6%, while 20% reduction in inflow leads to 15.2% decrease in the total annual cost. Similarly, 20% increase in alum dosage causes 7.1% increase in the total annual cost, while 20% decrease results in 7.9% decrease in the total annual cost. Furthermore, the pressure decrease causes 2.95 and 3.39% increase and decrease in total annual cost of treatment plants.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015APS..MARL34002S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015APS..MARL34002S"><span>Morphological <span class="hlt">Optimization</span> of Perovskite Thin Films via <span class="hlt">Dynamic</span> Zone Annealing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sun, Yan; Wang, Kai; Gong, Xiong; Karim, Alamgir</p> <p>2015-03-01</p> <p>Organolead Halide Perovskites have been proved to be excellent candidates for application in low-cost high-efficient solar cells owing to their superior desired optical and electrical properties, as well as compatibility with low-temperature solution-processed manufacturing. However, most perovskites applications in photovoltaics require high quality perovskite films. Although tremendous works on tuning perovskite film morphology have been reported previously, it is still a challenge to realize high quality perovskite film with controllable film uniformity and surface coverage, neither the mechanisms in the formation of perovskite. To address the issues above, here we demonstrate the effect of <span class="hlt">Dynamic</span> Zone Annealing (DZA) on perovskite morphologies, which is proved as an efficient method to control the structure and morphology in crystalline polymer and block copolymers. Via applying the DZA method, the mechanism in perovskite film formation is studied. Furthermore, by <span class="hlt">optimizing</span> DZA parameter such as maximum temperature, temperature gradient and zone velocity to control dendritic morphology and the grain growth, enhanced device performance was realized eventually. Equal contribution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017MSSP...85..193S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MSSP...85..193S"><span>Analytically <span class="hlt">optimal</span> parameters of <span class="hlt">dynamic</span> vibration absorber with negative stiffness</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shen, Yongjun; Peng, Haibo; Li, Xianghong; Yang, Shaopu</p> <p>2017-02-01</p> <p>In this paper the <span class="hlt">optimal</span> parameters of a <span class="hlt">dynamic</span> vibration absorber (DVA) with negative stiffness is analytically studied. The analytical solution is obtained by Laplace transform method when the primary system is subjected to harmonic excitation. The research shows there are still two fixed points independent of the absorber damping in the amplitude-frequency curve of the primary system when the system contains negative stiffness. Then the optimum frequency ratio and optimum damping ratio are respectively obtained based on the fixed-point theory. A new strategy is proposed to obtain the optimum negative stiffness ratio and make the system remain stable at the same time. At last the control performance of the presented DVA is compared with those of three existing typical DVAs, which were presented by Den Hartog, Ren and Sims respectively. The comparison results in harmonic and random excitation show that the presented DVA in this paper could not only reduce the peak value of the amplitude-frequency curve of the primary system significantly, but also broaden the efficient frequency range of vibration mitigation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1022922','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1022922"><span>Photocathode <span class="hlt">Optimization</span> for a <span class="hlt">Dynamic</span> Transmission Electron Microscope: Final Report</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Ellis, P; Flom, Z; Heinselman, K; Nguyen, T; Tung, S; Haskell, R; Reed, B W; LaGrange, T</p> <p>2011-08-04</p> <p>The <span class="hlt">Dynamic</span> Transmission Electron Microscope (DTEM) team at Harvey Mudd College has been sponsored by LLNL to design and build a test setup for <span class="hlt">optimizing</span> the performance of the DTEM's electron source. Unlike a traditional TEM, the DTEM achieves much faster exposure times by using photoemission from a photocathode to produce electrons for imaging. The DTEM team's work is motivated by the need to improve the coherence and current density of the electron cloud produced by the electron gun in order to increase the image resolution and contrast achievable by DTEM. The photoemission test setup is nearly complete and the team will soon complete baseline tests of electron gun performance. The photoemission laser and high voltage power supply have been repaired; the optics path for relaying the laser to the photocathode has been finalized, assembled, and aligned; the internal setup of the vacuum chamber has been finalized and mostly implemented; and system control, synchronization, and data acquisition has been implemented in LabVIEW. Immediate future work includes determining a consistent alignment procedure to place the laser waist on the photocathode, and taking baseline performance measurements of the tantalum photocathode. Future research will examine the performance of the electron gun as a function of the photoemission laser profile, the photocathode material, and the geometry and voltages of the accelerating and focusing components in the electron gun. This report presents the team's progress and outlines the work that remains.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22763388','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22763388"><span>Function-valued adaptive <span class="hlt">dynamics</span> and <span class="hlt">optimal</span> control theory.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Parvinen, Kalle; Heino, Mikko; Dieckmann, Ulf</p> <p>2013-09-01</p> <p>In this article we further develop the theory of adaptive <span class="hlt">dynamics</span> of function-valued traits. Previous work has concentrated on models for which invasion fitness can be written as an integral in which the integrand for each argument value is a function of the strategy value at that argument value only. For this type of models of direct effect, singular strategies can be found using the calculus of variations, with singular strategies needing to satisfy Euler's equation with environmental feedback. In a broader, more mechanistically oriented class of models, the function-valued strategy affects a process described by differential equations, and fitness can be expressed as an integral in which the integrand for each argument value depends both on the strategy and on process variables at that argument value. In general, the calculus of variations cannot help analyzing this much broader class of models. Here we explain how to find singular strategies in this class of process-mediated models using <span class="hlt">optimal</span> control theory. In particular, we show that singular strategies need to satisfy Pontryagin's maximum principle with environmental feedback. We demonstrate the utility of this approach by studying the evolution of strategies determining seasonal flowering schedules.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21115043','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21115043"><span><span class="hlt">Optimal</span> spectral tracking--adapting to <span class="hlt">dynamic</span> regime change.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Brittain, John-Stuart; Halliday, David M</p> <p>2011-01-30</p> <p>Real world data do not always obey the statistical restraints imposed upon them by sophisticated analysis techniques. In spectral analysis for instance, an ergodic process--the interchangeability of temporal for spatial averaging--is assumed for a repeat-trial design. Many evolutionary scenarios, such as learning and motor consolidation, do not conform to such linear behaviour and should be approached from a more flexible perspective. To this end we previously introduced the method of <span class="hlt">optimal</span> spectral tracking (OST) in the study of trial-varying parameters. In this extension to our work we modify the OST routines to provide an adaptive implementation capable of reacting to <span class="hlt">dynamic</span> transitions in the underlying system state. In so doing, we generalise our approach to characterise both slow-varying and rapid fluctuations in time-series, simultaneously providing a metric of system stability. The approach is first applied to a surrogate dataset and compared to both our original non-adaptive solution and spectrogram approaches. The adaptive OST is seen to display fast convergence and desirable statistical properties. All three approaches are then applied to a neurophysiological recording obtained during a study on anaesthetic monitoring. Local field potentials acquired from the posterior hypothalamic region of a deep brain stimulation patient undergoing anaesthesia were analysed. The characterisation of features such as response delay, time-to-peak and modulation brevity are considered.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1265997','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1265997"><span>A MILP-Based Distribution <span class="hlt">Optimal</span> Power Flow Model for Microgrid Operation</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Liu, Guodong; Starke, Michael R; Zhang, Xiaohu; Tomsovic, Kevin</p> <p>2016-01-01</p> <p>This paper proposes a distribution <span class="hlt">optimal</span> power flow (D-OPF) model for the operation of microgrids. The proposed model minimizes not only the operating cost, including fuel cost, purchasing cost and demand charge, but also several performance indices, including voltage deviation, network power loss and power factor. It co-<span class="hlt">optimizes</span> the real and reactive power form distributed generators (DGs) and batteries considering their capacity and power factor limits. The D-OPF is formulated as a <span class="hlt">mixed-integer</span> linear programming (MILP). Numerical simulation results show the effectiveness of the proposed model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3948477','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3948477"><span>Operational <span class="hlt">Optimization</span> of Large-Scale Parallel-Unit SWRO Desalination Plant Using Differential Evolution Algorithm</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Wang, Xiaolong; Jiang, Aipeng; Jiangzhou, Shu; Li, Ping</p> <p>2014-01-01</p> <p>A large-scale parallel-unit seawater reverse osmosis desalination plant contains many reverse osmosis (RO) units. If the operating conditions change, these RO units will not work at the <span class="hlt">optimal</span> design points which are computed before the plant is built. The operational <span class="hlt">optimization</span> problem (OOP) of the plant is to find out a scheduling of operation to minimize the total running cost when the change happens. In this paper, the OOP is modelled as a <span class="hlt">mixed-integer</span> nonlinear programming problem. A two-stage differential evolution algorithm is proposed to solve this OOP. Experimental results show that the proposed method is satisfactory in solution quality. PMID:24701180</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3765209','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3765209"><span>Simultaneous model discrimination and parameter estimation in <span class="hlt">dynamic</span> models of cellular systems</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2013-01-01</p> <p>Background Model development is a key task in systems biology, which typically starts from an initial model candidate and, involving an iterative cycle of hypotheses-driven model modifications, leads to new experimentation and subsequent model identification steps. The final product of this cycle is a satisfactory refined model of the biological phenomena under study. During such iterative model development, researchers frequently propose a set of model candidates from which the best alternative must be selected. Here we consider this problem of model selection and formulate it as a simultaneous model selection and parameter identification problem. More precisely, we consider a general <span class="hlt">mixed-integer</span> nonlinear programming (MINLP) formulation for model selection and identification, with emphasis on <span class="hlt">dynamic</span> models consisting of sets of either ODEs (ordinary differential equations) or DAEs (differential algebraic equations). Results We solved the MINLP formulation for model selection and identification using an algorithm based on Scatter Search (SS). We illustrate the capabilities and efficiency of the proposed strategy with a case study considering the KdpD/KdpE system regulating potassium homeostasis in Escherichia coli. The proposed approach resulted in a final model that presents a better fit to the in silico generated experimental data. Conclusions The presented MINLP-based <span class="hlt">optimization</span> approach for nested-model selection and identification is a powerful methodology for model development in systems biology. This strategy can be used to perform model selection and parameter estimation in one single step, thus greatly reducing the number of experiments and computations of traditional modeling approaches. PMID:23938131</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009CMMPh..49..748B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009CMMPh..49..748B"><span><span class="hlt">Optimal</span> control and <span class="hlt">optimal</span> trajectories of regional macroeconomic <span class="hlt">dynamics</span> based on the Pontryagin maximum principle</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bulgakov, V. K.; Strigunov, V. V.</p> <p>2009-05-01</p> <p>The Pontryagin maximum principle is used to prove a theorem concerning <span class="hlt">optimal</span> control in regional macroeconomics. A boundary value problem for <span class="hlt">optimal</span> trajectories of the state and adjoint variables is formulated, and <span class="hlt">optimal</span> curves are analyzed. An algorithm is proposed for solving the boundary value problem of <span class="hlt">optimal</span> control. The performance of the algorithm is demonstrated by computing an <span class="hlt">optimal</span> control and the corresponding <span class="hlt">optimal</span> trajectories.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27942416','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27942416"><span>Ckmeans.1d.dp: <span class="hlt">Optimal</span> k-means Clustering in One Dimension by <span class="hlt">Dynamic</span> Programming.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wang, Haizhou; Song, Mingzhou</p> <p>2011-12-01</p> <p>The heuristic k-means algorithm, widely used for cluster analysis, does not guarantee <span class="hlt">optimality</span>. We developed a <span class="hlt">dynamic</span> programming algorithm for <span class="hlt">optimal</span> one-dimensional clustering. The algorithm is implemented as an R package called Ckmeans.1d.dp. We demonstrate its advantage in <span class="hlt">optimality</span> and runtime over the standard iterative k-means algorithm.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20405047','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20405047"><span><span class="hlt">Dynamic</span> regime marginal structural mean models for estimation of <span class="hlt">optimal</span> <span class="hlt">dynamic</span> treatment regimes, Part II: proofs of results.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Orellana, Liliana; Rotnitzky, Andrea; Robins, James M</p> <p>2010-03-03</p> <p>In this companion article to "<span class="hlt">Dynamic</span> Regime Marginal Structural Mean Models for Estimation of <span class="hlt">Optimal</span> <span class="hlt">Dynamic</span> Treatment Regimes, Part I: Main Content" [Orellana, Rotnitzky and Robins (2010), IJB, Vol. 6, Iss. 2, Art. 7] we present (i) proofs of the claims in that paper, (ii) a proposal for the computation of a confidence set for the <span class="hlt">optimal</span> index when this lies in a finite set, and (iii) an example to aid the interpretation of the positivity assumption.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2854089','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2854089"><span><span class="hlt">Dynamic</span> Regime Marginal Structural Mean Models for Estimation of <span class="hlt">Optimal</span> <span class="hlt">Dynamic</span> Treatment Regimes, Part II: Proofs of Results*</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Orellana, Liliana; Rotnitzky, Andrea; Robins, James M.</p> <p>2010-01-01</p> <p>In this companion article to “<span class="hlt">Dynamic</span> Regime Marginal Structural Mean Models for Estimation of <span class="hlt">Optimal</span> <span class="hlt">Dynamic</span> Treatment Regimes, Part I: Main Content” [Orellana, Rotnitzky and Robins (2010), IJB, Vol. 6, Iss. 2, Art. 7] we present (i) proofs of the claims in that paper, (ii) a proposal for the computation of a confidence set for the <span class="hlt">optimal</span> index when this lies in a finite set, and (iii) an example to aid the interpretation of the positivity assumption. PMID:20405047</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JPhCS.725a2008S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JPhCS.725a2008S"><span><span class="hlt">Optimal</span> Strategy for Integrated <span class="hlt">Dynamic</span> Inventory Control and Supplier Selection in Unknown Environment via Stochastic <span class="hlt">Dynamic</span> Programming</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sutrisno; Widowati; Solikhin</p> <p>2016-06-01</p> <p>In this paper, we propose a mathematical model in stochastic <span class="hlt">dynamic</span> <span class="hlt">optimization</span> form to determine the <span class="hlt">optimal</span> strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the <span class="hlt">optimal</span> supplier and calculate the <span class="hlt">optimal</span> product volume purchased from the <span class="hlt">optimal</span> supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic <span class="hlt">dynamic</span> programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the <span class="hlt">optimal</span> supplier and the inventory level was tracked the reference point well.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007PhDT.......134G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007PhDT.......134G"><span><span class="hlt">Optimal</span> GENCO bidding strategy</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gao, Feng</p> <p></p> <p>Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex <span class="hlt">optimization</span> problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: <span class="hlt">Mixed</span> <span class="hlt">Integer</span> Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex <span class="hlt">optimization</span> problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical <span class="hlt">Mixed</span> <span class="hlt">Integer</span> Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build <span class="hlt">optimal</span> bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time <span class="hlt">optimal</span> control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional <span class="hlt">optimization</span> model may not be enough to consider the distributed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1339363-microgrid-optimal-scheduling-chance-constrained-islanding-capability','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1339363-microgrid-optimal-scheduling-chance-constrained-islanding-capability"><span>Microgrid <span class="hlt">Optimal</span> Scheduling With Chance-Constrained Islanding Capability</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Liu, Guodong; Starke, Michael R.; Xiao, B.; ...</p> <p>2017-01-13</p> <p>To facilitate the integration of variable renewable generation and improve the resilience of electricity sup-ply in a microgrid, this paper proposes an <span class="hlt">optimal</span> scheduling strategy for microgrid operation considering constraints of islanding capability. A new concept, probability of successful islanding (PSI), indicating the probability that a microgrid maintains enough spinning reserve (both up and down) to meet local demand and accommodate local renewable generation after instantaneously islanding from the main grid, is developed. The PSI is formulated as <span class="hlt">mixed-integer</span> linear program using multi-interval approximation taking into account the probability distributions of forecast errors of wind, PV and load. With themore » goal of minimizing the total operating cost while preserving user specified PSI, a chance-constrained <span class="hlt">optimization</span> problem is formulated for the <span class="hlt">optimal</span> scheduling of mirogrids and solved by <span class="hlt">mixed</span> <span class="hlt">integer</span> linear programming (MILP). Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator and a battery demonstrate the effectiveness of the proposed scheduling strategy. Lastly, we verify the relationship between PSI and various factors.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19900013716','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19900013716"><span>Application of numerical <span class="hlt">optimization</span> techniques to control system design for nonlinear <span class="hlt">dynamic</span> models of aircraft</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lan, C. Edward; Ge, Fuying</p> <p>1989-01-01</p> <p>Control system design for general nonlinear flight <span class="hlt">dynamic</span> models is considered through numerical simulation. The design is accomplished through a numerical <span class="hlt">optimizer</span> coupled with analysis of flight <span class="hlt">dynamic</span> equations. The general flight <span class="hlt">dynamic</span> equations are numerically integrated and <span class="hlt">dynamic</span> characteristics are then identified from the <span class="hlt">dynamic</span> response. The design variables are determined iteratively by the <span class="hlt">optimizer</span> to <span class="hlt">optimize</span> a prescribed objective function which is related to desired <span class="hlt">dynamic</span> characteristics. Generality of the method allows nonlinear effects to aerodynamics and <span class="hlt">dynamic</span> coupling to be considered in the design process. To demonstrate the method, nonlinear simulation models for an F-5A and an F-16 configurations are used to design dampers to satisfy specifications on flying qualities and control systems to prevent departure. The results indicate that the present method is simple in formulation and effective in satisfying the design objectives.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhyA..416..157L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhyA..416..157L"><span>Evacuation <span class="hlt">dynamic</span> and exit <span class="hlt">optimization</span> of a supermarket based on particle swarm <span class="hlt">optimization</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Lin; Yu, Zhonghai; Chen, Yang</p> <p>2014-12-01</p> <p>A modified particle swarm <span class="hlt">optimization</span> algorithm is proposed in this paper to investigate the <span class="hlt">dynamic</span> of pedestrian evacuation from a fire in a public building-a supermarket with multiple exits and configurations of counters. Two distinctive evacuation behaviours featured by the shortest-path strategy and the following-up strategy are simulated in the model, accounting for different categories of age and sex of the pedestrians along with the impact of the fire, including gases, heat and smoke. To examine the relationship among the progress of the overall evacuation and the layout and configuration of the site, a series of simulations are conducted in various settings: without a fire and with a fire at different locations. Those experiments reveal a general pattern of two-phase evacuation, i.e., a steep section and a flat section, in addition to the impact of the presence of multiple exits on the evacuation along with the geographic locations of the exits. For the study site, our simulations indicated the deficiency of the configuration and the current layout of this site in the process of evacuation and verified the availability of proposed solutions to resolve the deficiency. More specifically, for improvement of the effectiveness of the evacuation from the site, adding an exit between Exit 6 and Exit 7 and expanding the corridor at the right side of Exit 7 would significantly reduce the evacuation time.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PhyA..450..403Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PhyA..450..403Y"><span>The <span class="hlt">optimal</span> <span class="hlt">dynamic</span> immunization under a controlled heterogeneous node-based SIRS model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan</p> <p>2016-05-01</p> <p><span class="hlt">Dynamic</span> immunizations, under which the state of the propagation network of electronic viruses can be changed by adjusting the control measures, are regarded as an alternative to static immunizations. This paper addresses the <span class="hlt">optimal</span> <span class="hlt">dynamical</span> immunization under the widely accepted SIRS assumption. First, based on a controlled heterogeneous node-based SIRS model, an <span class="hlt">optimal</span> control problem capturing the <span class="hlt">optimal</span> <span class="hlt">dynamical</span> immunization is formulated. Second, the existence of an <span class="hlt">optimal</span> <span class="hlt">dynamical</span> immunization scheme is shown, and the corresponding <span class="hlt">optimality</span> system is derived. Next, some numerical examples are given to show that an <span class="hlt">optimal</span> immunization strategy can be worked out by numerically solving the <span class="hlt">optimality</span> system, from which it is found that the network topology has a complex impact on the <span class="hlt">optimal</span> immunization strategy. Finally, the difference between a payoff and the minimum payoff is estimated in terms of the deviation of the corresponding immunization strategy from the <span class="hlt">optimal</span> immunization strategy. The proposed <span class="hlt">optimal</span> immunization scheme is justified, because it can achieve a low level of infections at a low cost.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/6947394','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/6947394"><span><span class="hlt">Optimal</span> control of a <span class="hlt">dynamical</span> system representing a gantry crane</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Karihaloo, B.L.; Parbery, R.D.</p> <p>1982-03-01</p> <p>Problems arising in the <span class="hlt">optimal</span> control of gantry crane installations are considered. Continuous controls to minimize a control squared objective function are obtained. The amplitude of in-plane oscillations of the suspended mass is assumed small. The <span class="hlt">optimal</span> controls are sufficiently simple for practical realization.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AIPC.1410..296K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AIPC.1410..296K"><span><span class="hlt">Optimal</span> <span class="hlt">Dynamic</span> Advertising Strategy Under Age-Specific Market Segmentation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Krastev, Vladimir</p> <p>2011-12-01</p> <p>We consider the model proposed by Faggian and Grosset for determining the advertising efforts and goodwill in the long run of a company under age segmentation of consumers. Reducing this model to <span class="hlt">optimal</span> control sub problems we find the <span class="hlt">optimal</span> advertising strategy and goodwill.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA622426','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA622426"><span>An Approximate <span class="hlt">Dynamic</span> Programming Mode for <span class="hlt">Optimal</span> MEDEVAC Dispatching</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2015-03-26</p> <p>An Approximate <span class="hlt">Dynamic</span> Programming Model For MEDEVAC Dispatching THESIS MARCH 2015 Aaron J. Rettke, Captain, USA AFIT-ENS-MS-15-M-115 DEPARTMENT OF...and is not subject to copyright protection in the United States. AFIT-ENS-MS-15-M-115 AN APPROXIMATE <span class="hlt">DYNAMIC</span> PROGRAMMING MODEL FOR MEDEVAC... APPROXIMATE <span class="hlt">DYNAMIC</span> PROGRAMMING MODEL FOR MEDEVAC DISPATCHING THESIS Aaron J. Rettke, BS, MS Captain, USA Committee Membership: Lt Col Matthew J</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016Chaos..26h3101B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016Chaos..26h3101B"><span>Computing the <span class="hlt">optimal</span> path in stochastic <span class="hlt">dynamical</span> systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bauver, Martha; Forgoston, Eric; Billings, Lora</p> <p>2016-08-01</p> <p>In stochastic systems, one is often interested in finding the <span class="hlt">optimal</span> path that maximizes the probability of escape from a metastable state or of switching between metastable states. Even for simple systems, it may be impossible to find an analytic form of the <span class="hlt">optimal</span> path, and in high-dimensional systems, this is almost always the case. In this article, we formulate a constructive methodology that is used to compute the <span class="hlt">optimal</span> path numerically. The method utilizes finite-time Lyapunov exponents, statistical selection criteria, and a Newton-based iterative minimizing scheme. The method is applied to four examples. The first example is a two-dimensional system that describes a single population with internal noise. This model has an analytical solution for the <span class="hlt">optimal</span> path. The numerical solution found using our computational method agrees well with the analytical result. The second example is a more complicated four-dimensional system where our numerical method must be used to find the <span class="hlt">optimal</span> path. The third example, although a seemingly simple two-dimensional system, demonstrates the success of our method in finding the <span class="hlt">optimal</span> path where other numerical methods are known to fail. In the fourth example, the <span class="hlt">optimal</span> path lies in six-dimensional space and demonstrates the power of our method in computing paths in higher-dimensional spaces.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23400151','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23400151"><span>Performance <span class="hlt">optimization</span> of web-based medical simulation.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Halic, Tansel; Ahn, Woojin; De, Suvranu</p> <p>2013-01-01</p> <p>This paper presents a technique for performance <span class="hlt">optimization</span> of multimodal interactive web-based medical simulation. A web-based simulation framework is promising for easy access and wide dissemination of medical simulation. However, the real-time performance of the simulation highly depends on hardware capability on the client side. Providing consistent simulation in different hardware is critical for reliable medical simulation. This paper proposes a non-linear <span class="hlt">mixed</span> <span class="hlt">integer</span> programming model to <span class="hlt">optimize</span> the performance of visualization and physics computation while considering hardware capability and application specific constraints. The <span class="hlt">optimization</span> model identifies and parameterizes the rendering and computing capabilities of the client hardware using an exploratory proxy code. The parameters are utilized to determine the <span class="hlt">optimized</span> simulation conditions including texture sizes, mesh sizes and canvas resolution. The test results show that the <span class="hlt">optimization</span> model not only achieves a desired frame per second but also resolves visual artifacts due to low performance hardware.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012TRACE..23..145M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012TRACE..23..145M"><span>The <span class="hlt">Optimization</span> of a Cogeneration System for Commercial Buildings by the Particle Swarm <span class="hlt">Optimization</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Miyazaki, Takahiko; Akisawa, Atsushi; Kashiwagi, Takao</p> <p></p> <p>The cogeneration system provides electricity as well as heating and cooling, which consequently leads to a complexity of the design and operation of the system. It requires, therefore, the <span class="hlt">optimization</span> of parameters such as the number of machines and the capacity of equipment. Generally, the problem can be expressed as a <span class="hlt">mixed</span> <span class="hlt">integer</span> nonlinear programming problem, and a lot of efforts would be required to solve it. In this paper, we present a different approach to the <span class="hlt">optimization</span> of cogeneration systems, which facilitates to find a quasi-optimum solution. The particle swarm <span class="hlt">optimization</span> combined with a simulation of the system is applied to the minimization of the primary energy consumption and of the system cost. The results present the optimum system constitutions for medium- and large-sized buildings. The result of the system cost minimization under a constraint of the energy saving rate is also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PMB....58.5783K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PMB....58.5783K"><span><span class="hlt">Optimized</span> <span class="hlt">dynamic</span> framing for PET-based myocardial blood flow estimation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kolthammer, Jeffrey A.; Muzic, Raymond F.</p> <p>2013-08-01</p> <p>An <span class="hlt">optimal</span> experiment design methodology was developed to select the framing schedule to be used in <span class="hlt">dynamic</span> positron emission tomography (PET) for estimation of myocardial blood flow using 82Rb. A compartment model and an arterial input function based on measured data were used to calculate a D-<span class="hlt">optimality</span> criterion for a wide range of candidate framing schedules. To validate the <span class="hlt">optimality</span> calculation, noisy time-activity curves were simulated, from which parameter values were estimated using an efficient and robust decomposition of the estimation problem. D-<span class="hlt">optimized</span> schedules improved estimate precision compared to non-<span class="hlt">optimized</span> schedules, including previously published schedules. To assess robustness, a range of physiologic conditions were simulated. Schedules that were <span class="hlt">optimal</span> for one condition were nearly-<span class="hlt">optimal</span> for others. The effect of infusion duration was investigated. <span class="hlt">Optimality</span> was better for shorter than for longer tracer infusion durations, with the <span class="hlt">optimal</span> schedule for the shortest infusion duration being nearly <span class="hlt">optimal</span> for other durations. Together this suggests that a framing schedule <span class="hlt">optimized</span> for one set of conditions will also work well for others and it is not necessary to use different schedules for different infusion durations or for rest and stress studies. The method for <span class="hlt">optimizing</span> schedules is general and could be applied in other <span class="hlt">dynamic</span> PET imaging studies.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA564449','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA564449"><span><span class="hlt">Optimization</span> Algorithms and Equilibrium Analysis for <span class="hlt">Dynamic</span> Resource Allocation</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2012-01-31</p> <p>to derive necessary and sufficient conditions for many desirable properties of a prediction market mechanism such as proper scoring, truthful...set can be non - convex or non -connected. Our method is based on approximating a quadratic social utility <span class="hlt">optimization</span> problem (QP) and showing that...In [2], we present a convex <span class="hlt">optimization</span> framework that unifies these seemingly unrelated models for centrally organizing contingent claims</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017MPLB...3150084Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MPLB...3150084Z"><span>A new approach of analyzing time-varying <span class="hlt">dynamical</span> equation via an <span class="hlt">optimal</span> principle</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Hui; Li, Lixiang; Peng, Haipeng; Kurths, Jürgen; Xiao, Jinghua; Yang, Yixian; Li, Ang</p> <p>2017-03-01</p> <p>In this paper, an innovative design approach is proposed to solve time-varying <span class="hlt">dynamical</span> equation, including matrix inverse equation and Sylvester equation. Based on the precondition of the existing solution of time-varying <span class="hlt">dynamical</span> equation, different from previous approach to solve unknown matrix, an <span class="hlt">optimal</span> design principle is used to solve the unknown variables. A performance index is introduced based on the inherent properties of the time-varying <span class="hlt">dynamical</span> equation and Euler equation. The solution of time-varying <span class="hlt">dynamical</span> equation is converted to an <span class="hlt">optimal</span> problem of performance index. Furthermore, convergence and sensitivity to additive noise are also analyzed, and simulation results confirm that the method is feasible and effective. Especially, in simulations we design a tunable positive parameter in the <span class="hlt">dynamic</span> <span class="hlt">optimization</span> model. The tunable parameter is not only helpful to accelerate its convergence but also reduce its sensitivity to additive noise. Meanwhile the comparative simulation results are shown for the convergence accuracy and robustness of this method.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1043862','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1043862"><span><span class="hlt">Optimization</span> of the <span class="hlt">Dynamic</span> Aperture for SPEAR3 Low-Emittance Upgrade</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Wang, Lanfa; Huang, Xiaobiao; Nosochkov, Yuri; Safranek, James A.; Borland, Michael; /Argonne</p> <p>2012-05-30</p> <p>A low emittance upgrade is planned for SPEAR3. As the first phase, the emittance is reduced from 10nm to 7nm without additional magnets. A further upgrade with even lower emittance will require a damping wiggler. There is a smaller <span class="hlt">dynamic</span> aperture for the lower emittance optics due to a stronger nonlinearity. Elegant based Multi-Objective Genetic Algorithm (MOGA) is used to maximize the <span class="hlt">dynamic</span> aperture. Both the <span class="hlt">dynamic</span> aperture and beam lifetime are <span class="hlt">optimized</span> simultaneously. Various configurations of the sextupole magnets have been studied in order to find the best configuration. The betatron tune also can be <span class="hlt">optimized</span> to minimize resonance effects. The <span class="hlt">optimized</span> <span class="hlt">dynamic</span> aperture increases more than 15% from the nominal case and the lifetime increases from 14 hours to 17 hours. It is important that the increase of the <span class="hlt">dynamic</span> aperture is mainly in the beam injection direction. Therefore the injection efficiency will benefit from this improvement.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA470638','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA470638"><span><span class="hlt">Optimization</span> of Breast Cancer Treatment by <span class="hlt">Dynamic</span> Intensity Modulated Electron Radiotherapy</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2006-04-01</p> <p>AD_________________ Award Number: DAMD17-01-1-0435 TITLE: <span class="hlt">Optimization</span> of Breast Cancer Treatment by...<span class="hlt">Optimization</span> of Breast Cancer Treatment by <span class="hlt">Dynamic</span> Intensity Modulated Electron Radiotherapy 5b. GRANT NUMBER DAMD17-01-1-0435 5c. PROGRAM ELEMENT</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PhRvA..92f2106G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PhRvA..92f2106G"><span>Time-limited <span class="hlt">optimal</span> <span class="hlt">dynamics</span> beyond the quantum speed limit</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gajdacz, Miroslav; Das, Kunal K.; Arlt, Jan; Sherson, Jacob F.; Opatrný, Tomáš</p> <p>2015-12-01</p> <p>The quantum speed limit sets the minimum time required to transfer a quantum system completely into a given target state. At shorter times the higher operation speed results in a loss of fidelity. Here we quantify the trade-off between the fidelity and the duration in a system driven by a time-varying control. The problem is addressed in the framework of Hilbert space geometry offering an intuitive interpretation of <span class="hlt">optimal</span> control algorithms. This approach leads to a necessary criterion for control <span class="hlt">optimality</span> applicable as a measure of algorithm convergence. The time fidelity trade-off expressed in terms of the direct Hilbert velocity provides a robust prediction of the quantum speed limit and allows one to adapt the control <span class="hlt">optimization</span> such that it yields a predefined fidelity. The results are verified numerically in a multilevel system with a constrained Hamiltonian and a classification scheme for the control sequences is proposed based on their optimizability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJSyS..47.2022X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJSyS..47.2022X"><span><span class="hlt">Optimal</span> <span class="hlt">dynamic</span> pricing for deteriorating items with reference-price effects</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xue, Musen; Tang, Wansheng; Zhang, Jianxiong</p> <p>2016-07-01</p> <p>In this paper, a <span class="hlt">dynamic</span> pricing problem for deteriorating items with the consumers' reference-price effect is studied. An <span class="hlt">optimal</span> control model is established to maximise the total profit, where the demand not only depends on the current price, but also is sensitive to the historical price. The continuous-time <span class="hlt">dynamic</span> <span class="hlt">optimal</span> pricing strategy with reference-price effect is obtained through solving the <span class="hlt">optimal</span> control model on the basis of Pontryagin's maximum principle. In addition, numerical simulations and sensitivity analysis are carried out. Finally, some managerial suggestions that firm may adopt to formulate its pricing policy are proposed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ChPhB..24l8401L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ChPhB..24l8401L"><span><span class="hlt">Optimal</span> satisfaction degree in energy harvesting cognitive radio networks</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Zan; Liu, Bo-Yang; Si, Jiang-Bo; Zhou, Fu-Hui</p> <p>2015-12-01</p> <p>A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree <span class="hlt">optimization</span> problem as a <span class="hlt">mixed</span> <span class="hlt">integer</span> nonlinear programming (MINLP) problem. The satisfaction degree <span class="hlt">optimization</span> problem is solved by using differential evolution (DE) algorithm. The proposed <span class="hlt">optimization</span> problem allows the network to adaptively achieve the <span class="hlt">optimal</span> solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://files.eric.ed.gov/fulltext/ED502608.pdf','ERIC'); return false;" href="http://files.eric.ed.gov/fulltext/ED502608.pdf"><span>Was Your Glass Left Half Full? Family <span class="hlt">Dynamics</span> and <span class="hlt">Optimism</span></span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Buri, John R.; Gunty, Amy</p> <p>2008-01-01</p> <p>Students' levels of a frequently studied adaptive schema (<span class="hlt">optimism</span>) as a function of parenting variables (parental authority, family intrusiveness, parental overprotection, parentification, parental psychological control, and parental nurturance) were investigated. Results revealed that positive parenting styles were positively related to the…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA623473','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA623473"><span>Adaptive and <span class="hlt">Optimal</span> Control of Stochastic <span class="hlt">Dynamical</span> Systems</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2015-09-14</p> <p>control and stochastic differential games . Stochastic linear-quadratic, continuous time, stochastic control problems are solved for systems with noise...control problems for systems with arbitrary correlated n 15. SUBJECT TERMS Adaptive control, <span class="hlt">optimal</span> control, stochastic differential games 16. SECURITY...explicit results have been obtained for problems of stochastic control and stochastic differential games . Stochastic linear- quadratic, continuous time</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19890006570','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19890006570"><span><span class="hlt">Optimal</span> post-experiment estimation of poorly modeled <span class="hlt">dynamic</span> systems</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mook, D. Joseph</p> <p>1988-01-01</p> <p>Recently, a novel strategy for post-experiment state estimation of discretely-measured <span class="hlt">dynamic</span> systems has been developed. The method accounts for errors in the system <span class="hlt">dynamic</span> model equations in a more general and rigorous manner than do filter-smoother algorithms. The <span class="hlt">dynamic</span> model error terms do not require the usual process noise assumptions of zero-mean, symmetrically distributed random disturbances. Instead, the model error terms require no prior assumptions other than piecewise continuity. The resulting state estimates are more accurate than filters for applications in which the <span class="hlt">dynamic</span> model error clearly violates the typical process noise assumptions, and the available measurements are sparse and/or noisy. Estimates of the <span class="hlt">dynamic</span> model error, in addition to the states, are obtained as part of the solution of a two-point boundary value problem, and may be exploited for numerous reasons. In this paper, the basic technique is explained, and several example applications are given. Included among the examples are both state estimation and exploitation of the model error estimates.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1055043','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1055043"><span>INDDGO: Integrated Network Decomposition & <span class="hlt">Dynamic</span> programming for Graph <span class="hlt">Optimization</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Groer, Christopher S; Sullivan, Blair D; Weerapurage, Dinesh P</p> <p>2012-10-01</p> <p>It is well-known that <span class="hlt">dynamic</span> programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such <span class="hlt">dynamic</span> programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient <span class="hlt">dynamic</span> programming implementation for solving maximum weighted independent set. We describe our software and the algorithms we have implemented, focusing on memory saving techniques for the <span class="hlt">dynamic</span> programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our <span class="hlt">dynamic</span> programming code runs several times faster than these other methods.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhyA..470..217P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhyA..470..217P"><span><span class="hlt">Optimizing</span> controllability of edge <span class="hlt">dynamics</span> in complex networks by perturbing network structure</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pang, Shaopeng; Hao, Fei</p> <p>2017-03-01</p> <p>Using the minimum input signals to drive the <span class="hlt">dynamics</span> in complex networks toward some desired state is a fundamental issue in the field of network controllability. For a complex network with the <span class="hlt">dynamical</span> process defined on its edges, the controllability of this network is <span class="hlt">optimal</span> if it can be fully controlled by applying one input signal to an arbitrary non-isolated vertex of it. In this paper, the adding-edge strategy and turning-edge strategy are proposed to <span class="hlt">optimize</span> the controllability by minimum structural perturbations. Simulations and analyses indicate that the minimum number of adding-edges required for the <span class="hlt">optimal</span> controllability is equal to the minimum number of turning-edges, and networks with positively correlated in- and out-degrees are easier to achieve <span class="hlt">optimal</span> controllability. Furthermore, both the strategies have the capacity to reveal the relationship between certain structural properties of a complex network and its controllability of edge <span class="hlt">dynamics</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016E%26ES...39a2042T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016E%26ES...39a2042T"><span>Application of the <span class="hlt">dynamic</span> ant colony algorithm on the <span class="hlt">optimal</span> operation of cascade reservoirs</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tong, X. X.; Xu, W. S.; Wang, Y. F.; Zhang, Y. W.; Zhang, P. C.</p> <p>2016-08-01</p> <p>Due to the lack of <span class="hlt">dynamic</span> adjustments between global searches and local <span class="hlt">optimization</span>, it is difficult to maintain high diversity and overcome local optimum problems for Ant Colony Algorithms (ACA). Therefore, this paper proposes an improved ACA, <span class="hlt">Dynamic</span> Ant Colony Algorithm (DACA). DACA applies <span class="hlt">dynamic</span> adjustments on heuristic factor changes to balance global searches and local <span class="hlt">optimization</span> in ACA, which decreases cosines. At the same time, by utilizing the randomness and ergodicity of the chaotic search, DACA implements the chaos disturbance on the path found in each ACA iteration to improve the algorithm's ability to jump out of the local optimum and avoid premature convergence. We conducted a case study with DACA for <span class="hlt">optimal</span> joint operation of the Dadu River cascade reservoirs. The simulation results were compared with the results of the gradual <span class="hlt">optimization</span> method and the standard ACA, which demonstrated the advantages of DACA in speed and precision.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26236571','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26236571"><span>Targeted Learning of the Mean Outcome under an <span class="hlt">Optimal</span> <span class="hlt">Dynamic</span> Treatment Rule.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>van der Laan, Mark J; Luedtke, Alexander R</p> <p>2015-03-01</p> <p>We consider estimation of and inference for the mean outcome under the <span class="hlt">optimal</span> <span class="hlt">dynamic</span> two time-point treatment rule defined as the rule that maximizes the mean outcome under the <span class="hlt">dynamic</span> treatment, where the candidate rules are restricted to depend only on a user-supplied subset of the baseline and intermediate covariates. This estimation problem is addressed in a statistical model for the data distribution that is nonparametric beyond possible knowledge about the treatment and censoring mechanism. This contrasts from the current literature that relies on parametric assumptions. We establish that the mean of the counterfactual outcome under the <span class="hlt">optimal</span> <span class="hlt">dynamic</span> treatment is a pathwise differentiable parameter under conditions, and develop a targeted minimum loss-based estimator (TMLE) of this target parameter. We establish asymptotic linearity and statistical inference for this estimator under specified conditions. In a sequentially randomized trial the statistical inference relies upon a second-order difference between the estimator of the <span class="hlt">optimal</span> <span class="hlt">dynamic</span> treatment and the <span class="hlt">optimal</span> <span class="hlt">dynamic</span> treatment to be asymptotically negligible, which may be a problematic condition when the rule is based on multivariate time-dependent covariates. To avoid this condition, we also develop TMLEs and statistical inference for data adaptive target parameters that are defined in terms of the mean outcome under the estimate of the <span class="hlt">optimal</span> <span class="hlt">dynamic</span> treatment. In particular, we develop a novel cross-validated TMLE approach that provides asymptotic inference under minimal conditions, avoiding the need for any empirical process conditions. We offer simulation results to support our theoretical findings.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940029394','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940029394"><span>Multilevel decomposition approach to integrated aerodynamic/<span class="hlt">dynamic</span>/structural <span class="hlt">optimization</span> of helicopter rotor blades</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.</p> <p>1994-01-01</p> <p>This paper describes an integrated aerodynamic, <span class="hlt">dynamic</span>, and structural (IADS) <span class="hlt">optimization</span> procedure for helicopter rotor blades. The procedure combines performance, <span class="hlt">dynamics</span>, and structural analyses with a general purpose <span class="hlt">optimizer</span> using multilevel decomposition techniques. At the upper level, the structure is defined in terms of local quantities (stiffnesses, mass, and average strains). At the lower level, the structure is defined in terms of local quantities (detailed dimensions of the blade structure and stresses). The IADS procedure provides an <span class="hlt">optimization</span> technique that is compatible with industrial design practices in which the aerodynamic and <span class="hlt">dynamic</span> design is performed at a global level and the structural design is carried out at a detailed level with considerable dialogue and compromise among the aerodynamic, <span class="hlt">dynamic</span>, and structural groups. The IADS procedure is demonstrated for several cases.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19950016536','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19950016536"><span>Integrated aerodynamic/<span class="hlt">dynamic</span>/structural <span class="hlt">optimization</span> of helicopter rotor blades using multilevel decomposition</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.</p> <p>1995-01-01</p> <p>This paper describes an integrated aerodynamic/<span class="hlt">dynamic</span>/structural (IADS) <span class="hlt">optimization</span> procedure for helicopter rotor blades. The procedure combines performance, <span class="hlt">dynamics</span>, and structural analyses with a general-purpose <span class="hlt">optimizer</span> using multilevel decomposition techniques. At the upper level, the structure is defined in terms of global quantities (stiffness, mass, and average strains). At the lower level, the structure is defined in terms of local quantities (detailed dimensions of the blade structure and stresses). The IADS procedure provides an <span class="hlt">optimization</span> technique that is compatible with industrial design practices in which the aerodynamic and <span class="hlt">dynamic</span> designs are performed at a global level and the structural design is carried out at a detailed level with considerable dialog and compromise among the aerodynamic, <span class="hlt">dynamic</span>, and structural groups. The IADS procedure is demonstrated for several examples.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26526039','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26526039"><span>Computational Fluid <span class="hlt">Dynamics</span>-Based Design <span class="hlt">Optimization</span> Method for Archimedes Screw Blood Pumps.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Yu, Hai; Janiga, Gábor; Thévenin, Dominique</p> <p>2016-04-01</p> <p>An <span class="hlt">optimization</span> method suitable for improving the performance of Archimedes screw axial rotary blood pumps is described in the present article. In order to achieve a more robust design and to save computational resources, this method combines the advantages of the established pump design theory with modern computer-aided, computational fluid <span class="hlt">dynamics</span> (CFD)-based design <span class="hlt">optimization</span> (CFD-O) relying on evolutionary algorithms and computational fluid <span class="hlt">dynamics</span>. The main purposes of this project are to: (i) integrate pump design theory within the already existing CFD-based <span class="hlt">optimization</span>; (ii) demonstrate that the resulting procedure is suitable for <span class="hlt">optimizing</span> an Archimedes screw blood pump in terms of efficiency. Results obtained in this study demonstrate that the developed tool is able to meet both objectives. Finally, the resulting level of hemolysis can be numerically assessed for the <span class="hlt">optimal</span> design, as hemolysis is an issue of overwhelming importance for blood pumps.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1992asdy.conf..395L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1992asdy.conf..395L"><span><span class="hlt">Dynamic</span> modeling and <span class="hlt">optimal</span> control of spacecraft with flexible structures undergoing general attitude maneuvers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lin, Yiing-Yuh; Lin, Gern-Liang</p> <p>1992-08-01</p> <p>In this research, the <span class="hlt">dynamics</span> and control of a rigid spacecraft with flexible structures were studied for the case of <span class="hlt">optimal</span> simultaneous multiaxis reorientation. A model spacecraft consisting of a rigid hub in the middle and two solid bodies symmetrically connected to either side of the hub through uniformly distributed flexible beams is considered for the <span class="hlt">dynamic</span> analysis and control simulation. To <span class="hlt">optimally</span> reorienting the spacecraft, an <span class="hlt">optimal</span> nominal control trajectory is found first through an iterative procedure. Linear flexural deformations are assumed for the beam structures and the assumed modes method is applied to find the vibration control law of the beams. The system overall <span class="hlt">optimal</span> attitude control is achieved by following the open loop <span class="hlt">optimal</span> reference control trajectory with an stabilizing guidance law.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170001473','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170001473"><span>Low-Thrust Many-Revolution Trajectory <span class="hlt">Optimization</span> via Differential <span class="hlt">Dynamic</span> Programming and a Sundman Transformation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Aziz, Jonathan D.; Parker, Jeffrey S.; Scheeres, Daniel J.; Englander, Jacob A.</p> <p>2017-01-01</p> <p>Low-thrust trajectories about planetary bodies characteristically span a high count of orbital revolutions. Directing the thrust vector over many revolutions presents a challenging <span class="hlt">optimization</span> problem for any conventional strategy. This paper demonstrates the tractability of low-thrust trajectory <span class="hlt">optimization</span> about planetary bodies by applying a Sundman transformation to change the independent variable of the spacecraft equations of motion to the eccentric anomaly and performing the <span class="hlt">optimization</span> with differential <span class="hlt">dynamic</span> programming. Fuel-<span class="hlt">optimal</span> geocentric transfers are shown in excess of 1000 revolutions while subject to Earths J2 perturbation and lunar gravity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009SPIE.7382E..38X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009SPIE.7382E..38X"><span><span class="hlt">Dynamic</span> analysis and <span class="hlt">optimal</span> design of exposure device of laser detector based on a virtual prototype</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xu, Da; Zhao, Jian-xun; Hu, Jun-biao; Li, Hua; Wang, Chuan-you; Li, Bing-wei</p> <p>2009-07-01</p> <p>The <span class="hlt">dynamical</span> simulation model of the exposure device of laser detector is built up in ADAMS software. Aiming at <span class="hlt">optimizing</span> the movement law of the pole and minimizing the maximal value of load of key parts, the influences of the spring stiffness coefficient,the damping coefficient, preload of spring and the mass of pole on the <span class="hlt">optimal</span> goal are discussed. The virtual prototype of the exposure device of laser detector has been <span class="hlt">optimized</span> and the <span class="hlt">optimized</span> parameters are obtained. In order to choose the electromotor and material, intensity of key parts is checked based on ANSYS. And the problem of TQC is solved effectively by this way.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JGRD..11813022L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JGRD..11813022L"><span>A new <span class="hlt">dynamic</span> approach for statistical <span class="hlt">optimization</span> of GNSS radio occultation bending angles for <span class="hlt">optimal</span> climate monitoring utility</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Wu, S.; Schwaerz, M.; Fritzer, J.; Zhang, S.; Carter, B. A.; Zhang, K.</p> <p>2013-12-01</p> <p>Navigation Satellite System (GNSS)-based radio occultation (RO) is a satellite remote sensing technique providing accurate profiles of the Earth's atmosphere for weather and climate applications. Above about 30 km altitude, however, statistical <span class="hlt">optimization</span> is a critical process for initializing the RO bending angles in order to <span class="hlt">optimize</span> the climate monitoring utility of the retrieved atmospheric profiles. Here we introduce an advanced <span class="hlt">dynamic</span> statistical <span class="hlt">optimization</span> algorithm, which uses bending angles from multiple days of European Centre for Medium-range Weather Forecasts (ECMWF) short-range forecast and analysis fields, together with averaged-observed bending angles, to obtain background profiles and associated error covariance matrices with geographically varying background uncertainty estimates on a daily updated basis. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.4 (OPSv5.4) algorithm, using several days of simulated MetOp and observed CHAMP and COSMIC data, for January and July conditions. We find the following for the new method's performance compared to OPSv5.4: 1.) it significantly reduces random errors (standard deviations), down to about half their size, and leaves less or about equal residual systematic errors (biases) in the <span class="hlt">optimized</span> bending angles; 2.) the <span class="hlt">dynamic</span> (daily) estimate of the background error correlation matrix alone already improves the <span class="hlt">optimized</span> bending angles; 3.) the subsequently retrieved refractivity profiles and atmospheric (temperature) profiles benefit by improved error characteristics, especially above about 30 km. Based on these encouraging results, we work to employ similar <span class="hlt">dynamic</span> error covariance estimation also for the observed bending angles and to apply the method to full months and subsequently to entire climate data records.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJSyS..47.1480L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJSyS..47.1480L"><span><span class="hlt">Optimal</span> <span class="hlt">dynamic</span> pricing and replenishment policy for perishable items with inventory-level-dependent demand</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lu, Lihao; Zhang, Jianxiong; Tang, Wansheng</p> <p>2016-04-01</p> <p>An inventory system for perishable items with limited replenishment capacity is introduced in this paper. The demand rate depends on the stock quantity displayed in the store as well as the sales price. With the goal to realise profit maximisation, an optimisation problem is addressed to seek for the <span class="hlt">optimal</span> joint <span class="hlt">dynamic</span> pricing and replenishment policy which is obtained by solving the optimisation problem with Pontryagin's maximum principle. A joint mixed policy, in which the sales price is a static decision variable and the replenishment rate remains to be a <span class="hlt">dynamic</span> decision variable, is presented to compare with the joint <span class="hlt">dynamic</span> policy. Numerical results demonstrate the advantages of the joint <span class="hlt">dynamic</span> one, and further show the effects of different system parameters on the <span class="hlt">optimal</span> joint <span class="hlt">dynamic</span> policy and the maximal total profit.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA273871','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA273871"><span><span class="hlt">Optimal</span> and Efficient Path Planning for Unknown and <span class="hlt">Dynamic</span> Environments</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>1993-08-01</p> <p>Figure 1 : Backpointers Based on Initial Propagation from Goal State 10 Figure 2 : Robot Discovers First Unknown Obstacle Cell I 1 Figure 3 : Robot...Moves Up in Search of Path around Obstacle 11 Figure 4 : Robot Moves Down in Search of Path around Obstacle 12 Figure 5 : RAISE States Propagate out of...<span class="hlt">Dynamic</span> Obstacle 25 Figure 14 : Discovering that the Obstacle has Moved 25 Figure 15 : Path Planning with Potential Fields 26 Figure 16 : Path Planning</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012MSSP...28..105P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012MSSP...28..105P"><span>The effect of prediction error correlation on <span class="hlt">optimal</span> sensor placement in structural <span class="hlt">dynamics</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Papadimitriou, Costas; Lombaert, Geert</p> <p>2012-04-01</p> <p>The problem of estimating the <span class="hlt">optimal</span> sensor locations for parameter estimation in structural <span class="hlt">dynamics</span> is re-visited. The effect of spatially correlated prediction errors on the <span class="hlt">optimal</span> sensor placement is investigated. The information entropy is used as a performance measure of the sensor configuration. The <span class="hlt">optimal</span> sensor location is formulated as an <span class="hlt">optimization</span> problem involving discrete-valued variables, which is solved using computationally efficient sequential sensor placement algorithms. Asymptotic estimates for the information entropy are used to develop useful properties that provide insight into the dependence of the information entropy on the number and location of sensors. A theoretical analysis shows that the spatial correlation length of the prediction errors controls the minimum distance between the sensors and should be taken into account when designing <span class="hlt">optimal</span> sensor locations with potential sensor distances up to the order of the characteristic length of the <span class="hlt">dynamic</span> problem considered. Implementation issues for modal identification and structural-related model parameter estimation are addressed. Theoretical and computational developments are illustrated by designing the <span class="hlt">optimal</span> sensor configurations for a continuous beam model, a discrete chain-like stiffness-mass model and a finite element model of a footbridge in Wetteren (Belgium). Results point out the crucial effect the spatial correlation of the prediction errors have on the design of <span class="hlt">optimal</span> sensor locations for structural <span class="hlt">dynamics</span> applications, revealing simultaneously potential inadequacies of spatially uncorrelated prediction errors models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012SPIE.8387E..0CL','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012SPIE.8387E..0CL"><span>Approximate <span class="hlt">dynamic</span> programming recurrence relations for a hybrid <span class="hlt">optimal</span> control problem</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lu, W.; Ferrari, S.; Fierro, R.; Wettergren, T. A.</p> <p>2012-06-01</p> <p>This paper presents a hybrid approximate <span class="hlt">dynamic</span> programming (ADP) method for a hybrid <span class="hlt">dynamic</span> system (HDS) <span class="hlt">optimal</span> control problem, that occurs in many complex unmanned systems which are implemented via a hybrid architecture, regarding robot modes or the complex environment. The HDS considered in this paper is characterized by a well-known three-layer hybrid framework, which includes a discrete event controller layer, a discrete-continuous interface layer, and a continuous state layer. The hybrid <span class="hlt">optimal</span> control problem (HOCP) is to nd the <span class="hlt">optimal</span> discrete event decisions and the <span class="hlt">optimal</span> continuous controls subject to a deterministic minimization of a scalar function regarding the system state and control over time. Due to the uncertainty of environment and complexity of the HOCP, the cost-to-go cannot be evaluated before the HDS explores the entire system state space; as a result, the <span class="hlt">optimal</span> control, neither continuous nor discrete, is not available ahead of time. Therefore, ADP is adopted to learn the <span class="hlt">optimal</span> control while the HDS is exploring the environment, because of the online advantage of ADP method. Furthermore, ADP can break the curses of dimensionality which other <span class="hlt">optimizing</span> methods, such as <span class="hlt">dynamic</span> programming (DP) and Markov decision process (MDP), are facing due to the high dimensions of HOCP.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27274921','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27274921"><span><span class="hlt">Optimization</span> Models for Scheduling of Jobs.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Indika, S H Sathish; Shier, Douglas R</p> <p>2006-01-01</p> <p>This work is motivated by a particular scheduling problem that is faced by logistics centers that perform aircraft maintenance and modification. Here we concentrate on a single facility (hangar) which is equipped with several work stations (bays). Specifically, a number of jobs have already been scheduled for processing at the facility; the starting times, durations, and work station assignments for these jobs are assumed to be known. We are interested in how best to schedule a number of new jobs that the facility will be processing in the near future. We first develop a <span class="hlt">mixed</span> <span class="hlt">integer</span> quadratic programming model (MIQP) for this problem. Since the exact solution of this MIQP formulation is time consuming, we develop a heuristic procedure, based on existing bin packing techniques. This heuristic is further enhanced by application of certain local <span class="hlt">optimality</span> conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4662499','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4662499"><span><span class="hlt">Optimization</span> Models for Scheduling of Jobs</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Indika, S. H. Sathish; Shier, Douglas R.</p> <p>2006-01-01</p> <p>This work is motivated by a particular scheduling problem that is faced by logistics centers that perform aircraft maintenance and modification. Here we concentrate on a single facility (hangar) which is equipped with several work stations (bays). Specifically, a number of jobs have already been scheduled for processing at the facility; the starting times, durations, and work station assignments for these jobs are assumed to be known. We are interested in how best to schedule a number of new jobs that the facility will be processing in the near future. We first develop a <span class="hlt">mixed</span> <span class="hlt">integer</span> quadratic programming model (MIQP) for this problem. Since the exact solution of this MIQP formulation is time consuming, we develop a heuristic procedure, based on existing bin packing techniques. This heuristic is further enhanced by application of certain local <span class="hlt">optimality</span> conditions. PMID:27274921</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4407907','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4407907"><span>Bacterial Temporal <span class="hlt">Dynamics</span> Enable <span class="hlt">Optimal</span> Design of Antibiotic Treatment</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Meredith, Hannah R.; Lopatkin, Allison J.; Anderson, Deverick J.; You, Lingchong</p> <p>2015-01-01</p> <p>There is a critical need to better use existing antibiotics due to the urgent threat of antibiotic resistant bacteria coupled with the reduced effort in developing new antibiotics. β-lactam antibiotics represent one of the most commonly used classes of antibiotics to treat a broad spectrum of Gram-positive and -negative bacterial pathogens. However, the rise of extended spectrum β-lactamase (ESBL) producing bacteria has limited the use of β-lactams. Due to the concern of complex drug responses, many β-lactams are typically ruled out if ESBL-producing pathogens are detected, even if these pathogens test as susceptible to some β-lactams. Using quantitative modeling, we show that β-lactams could still effectively treat pathogens producing low or moderate levels of ESBLs when administered properly. We further develop a metric to guide the design of a dosing protocol to <span class="hlt">optimize</span> treatment efficiency for any antibiotic-pathogen combination. Ultimately, <span class="hlt">optimized</span> dosing protocols could allow reintroduction of a repertoire of first-line antibiotics with improved treatment outcomes and preserve last-resort antibiotics. PMID:25905796</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1313618','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1313618"><span>Stochastic <span class="hlt">Optimal</span> Scheduling of Residential Appliances with Renewable Energy Sources</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Wu, Hongyu; Pratt, Annabelle; Chakraborty, Sudipta</p> <p>2015-07-03</p> <p>This paper proposes a stochastic, multi-objective <span class="hlt">optimization</span> model within a Model Predictive Control (MPC) framework, to determine the <span class="hlt">optimal</span> operational schedules of residential appliances operating in the presence of renewable energy source (RES). The objective function minimizes the weighted sum of discomfort, energy cost, total and peak electricity consumption, and carbon footprint. A heuristic method is developed for combining different objective components. The proposed stochastic model utilizes Monte Carlo simulation (MCS) for representing uncertainties in electricity price, outdoor temperature, RES generation, water usage, and non-controllable loads. The proposed model is solved using a <span class="hlt">mixed</span> <span class="hlt">integer</span> linear programming (MILP) solver and numerical results show the validity of the model. Case studies show the benefit of using the proposed <span class="hlt">optimization</span> model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24508904','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24508904"><span>Integrated strategic and tactical biomass-biofuel supply chain <span class="hlt">optimization</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lin, Tao; Rodríguez, Luis F; Shastri, Yogendra N; Hansen, Alan C; Ting, K C</p> <p>2014-03-01</p> <p>To ensure effective biomass feedstock provision for large-scale biofuel production, an integrated biomass supply chain <span class="hlt">optimization</span> model was developed to minimize annual biomass-ethanol production costs by <span class="hlt">optimizing</span> both strategic and tactical planning decisions simultaneously. The <span class="hlt">mixed</span> <span class="hlt">integer</span> linear programming model <span class="hlt">optimizes</span> the activities range from biomass harvesting, packing, in-field transportation, stacking, transportation, preprocessing, and storage, to ethanol production and distribution. The numbers, locations, and capacities of facilities as well as biomass and ethanol distribution patterns are key strategic decisions; while biomass production, delivery, and operating schedules and inventory monitoring are key tactical decisions. The model was implemented to study Miscanthus-ethanol supply chain in Illinois. The base case results showed unit Miscanthus-ethanol production costs were $0.72L(-1) of ethanol. Biorefinery related costs accounts for 62% of the total costs, followed by biomass procurement costs. Sensitivity analysis showed that a 50% reduction in biomass yield would increase unit production costs by 11%.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/21059054','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/21059054"><span><span class="hlt">Optimal</span> purchasing of raw materials: A data-driven approach</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Muteki, K.; MacGregor, J.F.</p> <p>2008-06-15</p> <p>An approach to the <span class="hlt">optimal</span> purchasing of raw materials that will achieve a desired product quality at a minimum cost is presented. A PLS (Partial Least Squares) approach to formulation modeling is used to combine databases on raw material properties and on past process operations and to relate these to final product quality. These PLS latent variable models are then used in a sequential quadratic programming (SQP) or <span class="hlt">mixed</span> <span class="hlt">integer</span> nonlinear programming (MINLP) <span class="hlt">optimization</span> to select those raw-materials, among all those available on the market, the ratios in which to combine them and the process conditions under which they should be processed. The approach is illustrated for the <span class="hlt">optimal</span> purchasing of metallurgical coals for coke making in the steel industry.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/754319','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/754319"><span>Scaling and <span class="hlt">optimization</span> of the radiation temperature in <span class="hlt">dynamic</span> hohlraums</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>SLUTZ,STEPHEN A.; DOUGLAS,MELISSA R.; LASH,JOEL S.; VESEY,ROGER A.; CHANDLER,GORDON A.; NASH,THOMAS J.; DERZON,MARK S.</p> <p>2000-04-13</p> <p>The authors have constructed a quasi-analytic model of the <span class="hlt">dynamic</span> hohlraum. Solutions only require a numerical root solve, which can be done very quickly. Results of the model are compared to both experiments and full numerical simulations with good agreement. The computational simplicity of the model allows one to find the behavior of the hohlraum temperature as a function the various parameters of the system and thus find optimum parameters as a function of the driving current. The model is used to investigate the benefits of ablative standoff and axial convergence.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AIPC.1738F0004C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AIPC.1738F0004C"><span><span class="hlt">Optimal</span> control methods for controlling bacterial populations with persister <span class="hlt">dynamics</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cogan, N. G.</p> <p>2016-06-01</p> <p>Bacterial tolerance to antibiotics is a well-known phenomena; however, only recent studies of bacterial biofilms have shown how multifaceted tolerance really is. By joining into a structured community and offering shared protection and gene transfer, bacterial populations can protect themselves genotypically, phenotypically and physically. In this study, we collect a line of research that focuses on phenotypic (or plastic) tolerance. The <span class="hlt">dynamics</span> of persister formation are becoming better understood, even though there are major questions that remain. The thrust of our results indicate that even without detailed description of the biological mechanisms, theoretical studies can offer strategies that can eradicate bacterial populations with existing drugs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090025073','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090025073"><span>Discrete Adjoint-Based Design <span class="hlt">Optimization</span> of Unsteady Turbulent Flows on <span class="hlt">Dynamic</span> Unstructured Grids</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nielsen, Eric J.; Diskin, Boris; Yamaleev, Nail K.</p> <p>2009-01-01</p> <p>An adjoint-based methodology for design <span class="hlt">optimization</span> of unsteady turbulent flows on <span class="hlt">dynamic</span> unstructured grids is described. The implementation relies on an existing unsteady three-dimensional unstructured grid solver capable of <span class="hlt">dynamic</span> mesh simulations and discrete adjoint capabilities previously developed for steady flows. The discrete equations for the primal and adjoint systems are presented for the backward-difference family of time-integration schemes on both static and <span class="hlt">dynamic</span> grids. The consistency of sensitivity derivatives is established via comparisons with complex-variable computations. The current work is believed to be the first verified implementation of an adjoint-based <span class="hlt">optimization</span> methodology for the true time-dependent formulation of the Navier-Stokes equations in a practical computational code. Large-scale shape <span class="hlt">optimizations</span> are demonstrated for turbulent flows over a tiltrotor geometry and a simulated aeroelastic motion of a fighter jet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011PhRvL.106s0501D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011PhRvL.106s0501D"><span><span class="hlt">Optimal</span> Control Technique for Many-Body Quantum <span class="hlt">Dynamics</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Doria, Patrick; Calarco, Tommaso; Montangero, Simone</p> <p>2011-05-01</p> <p>We present an efficient strategy for controlling a vast range of nonintegrable quantum many-body one-dimensional systems that can be merged with state-of-the-art tensor network simulation methods such as the density matrix renormalization group. To demonstrate its potential, we employ it to solve a major issue in current optical-lattice physics with ultracold atoms: we show how to reduce by about 2 orders of magnitude the time needed to bring a superfluid gas into a Mott insulator state, while suppressing defects by more than 1 order of magnitude as compared to current experiments [T. Stöferle , Phys. Rev. Lett. 92, 130403 (2004)PRLTAO0031-900710.1103/PhysRevLett.92.130403]. Finally, we show that the <span class="hlt">optimal</span> pulse is robust against atom number fluctuations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD0748206','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD0748206"><span><span class="hlt">Optimal</span> <span class="hlt">Dynamics</span> of the Vidale-Wolfe Advertising Model. Part I. Fixed Terminal Market Share.</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p></p> <p>The <span class="hlt">optimal</span> control problem consist of the Vidale-Wolfe advertising model as its <span class="hlt">dynamics</span>; the <span class="hlt">optimal</span> control being the rate of advertising ...expenditure which must achieve a specified terminal market share in a way which maximizes the present value of net profit streams over a finite horizon. The...problem is completely solved with or without an upper limit on advertising rate. The solution in the later case is obtained by using Green’s theorem</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011NIMPB.269.1568S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011NIMPB.269.1568S"><span><span class="hlt">Optimization</span> of large amorphous silicon and silica structures for molecular <span class="hlt">dynamics</span> simulations of energetic impacts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Samela, Juha; Norris, Scott A.; Nordlund, Kai; Aziz, Michael J.</p> <p>2011-07-01</p> <p>A practical method to create <span class="hlt">optimized</span> amorphous silicon and silica structures for molecular <span class="hlt">dynamics</span> simulations is developed and tested. The method is based on the Wooten, Winer, and Weaire algorithm and combination of small <span class="hlt">optimized</span> blocks to larger structures. The method makes possible to perform simulations of either very large cluster hypervelocity impacts on amorphous targets or small displacements induced by low energy ion impacts in silicon.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19790071257&hterms=Uncertainty+Principle&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DUncertainty%2BPrinciple','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19790071257&hterms=Uncertainty+Principle&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DUncertainty%2BPrinciple"><span>The Uncertainty Threshold Principle: Some Fundamental Limitations of <span class="hlt">Optimal</span> Decision Making Under <span class="hlt">Dynamic</span> Uncertainity</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Athans, M.; Ku, R.; Gershwin, S. B.</p> <p>1977-01-01</p> <p>This note shows that the <span class="hlt">optimal</span> control of <span class="hlt">dynamic</span> systems with uncertain parameters has certain limitations. In particular, by means of a simple scalar linear-quadratic <span class="hlt">optimal</span> control example, it is shown that the infinite horizon solution does not exist if the parameter uncertainty exceeds a certain quantifiable threshold; we call this the uncertainty threshold principle. The philosophical and design implications of this result are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19770055137&hterms=Uncertainty+Principle&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DUncertainty%2BPrinciple','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19770055137&hterms=Uncertainty+Principle&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DUncertainty%2BPrinciple"><span>The uncertainty threshold principle - Some fundamental limitations of <span class="hlt">optimal</span> decision making under <span class="hlt">dynamic</span> uncertainty</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Athans, M.; Ku, R.; Gershwin, S. B.</p> <p>1977-01-01</p> <p>This note shows that the <span class="hlt">optimal</span> control of <span class="hlt">dynamic</span> systems with uncertain parameters has certain limitations. In particular, by means of a simple scalar linear-quadratic <span class="hlt">optimal</span> control example, it is shown that the infinite horizon solution does not exist if the parameter uncertainty exceeds a certain quantifiable threshold; we call this the uncertainty threshold principle. The philosophical and design implications of this result are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008PhDT.......121H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008PhDT.......121H"><span><span class="hlt">Optimization</span> of the <span class="hlt">dynamic</span> behavior of strongly nonlinear heterogeneous materials</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Herbold, Eric B.</p> <p></p> <p>New aspects of strongly nonlinear wave and structural phenomena in granular media are developed numerically, theoretically and experimentally. One-dimensional chains of particles and compressed powder composites are the two main types of materials considered here. Typical granular assemblies consist of linearly elastic spheres or layers of masses and effective nonlinear springs in one-dimensional columns for <span class="hlt">dynamic</span> testing. These materials are highly sensitive to initial and boundary conditions, making them useful for acoustic and shock-mitigating applications. One-dimensional assemblies of spherical particles are examples of strongly nonlinear systems with unique properties. For example, if initially uncompressed, these materials have a sound speed equal to zero (sonic vacuum), supporting strongly nonlinear compression solitary waves with a finite width. Different types of assembled metamaterials will be presented with a discussion of the material's response to static compression. The acoustic diode effect will be presented, which may be useful in shock mitigation applications. Systems with controlled dissipation will also be discussed from an experimental and theoretical standpoint emphasizing the critical viscosity that defines the transition from an oscillatory to monotonous shock profile. The <span class="hlt">dynamic</span> compression of compressed powder composites may lead to self-organizing mesoscale structures in two and three dimensions. A reactive granular material composed of a compressed mixture of polytetrafluoroethylene (PTFE), tungsten (W) and aluminum (Al) fine-grain powders exhibit this behavior. Quasistatic, Hopkinson bar, and drop-weight experiments show that composite materials with a high porosity and fine metallic particles exhibit a higher strength than less porous mixtures with larger particles, given the same mass fraction of constituents. A two-dimensional Eulerian hydrocode is implemented to investigate the mechanical deformation and failure of the compressed</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090004433','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090004433"><span><span class="hlt">Optimal</span> Input Design for Aircraft Parameter Estimation using <span class="hlt">Dynamic</span> Programming Principles</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Morelli, Eugene A.; Klein, Vladislav</p> <p>1990-01-01</p> <p>A new technique was developed for designing <span class="hlt">optimal</span> flight test inputs for aircraft parameter estimation experiments. The principles of <span class="hlt">dynamic</span> programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral <span class="hlt">dynamics</span> of a fighter aircraft. The <span class="hlt">optimal</span> input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900058102&hterms=programming+principles&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dprogramming%2Bprinciples','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900058102&hterms=programming+principles&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dprogramming%2Bprinciples"><span><span class="hlt">Optimal</span> input design for aircraft parameter estimation using <span class="hlt">dynamic</span> programming principles</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Klein, Vladislav; Morelli, Eugene A.</p> <p>1990-01-01</p> <p>A new technique was developed for designing <span class="hlt">optimal</span> flight test inputs for aircraft parameter estimation experiments. The principles of <span class="hlt">dynamic</span> programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral <span class="hlt">dynamics</span> of a fighter aircraft. The <span class="hlt">optimal</span> input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19770046002&hterms=Uncertainty+Principle&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DUncertainty%2BPrinciple','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19770046002&hterms=Uncertainty+Principle&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DUncertainty%2BPrinciple"><span>The uncertainty threshold principle - Fundamental limitations of <span class="hlt">optimal</span> decision making under <span class="hlt">dynamic</span> uncertainty</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Athans, M.; Ku, R.; Gershwin, S. B.</p> <p>1976-01-01</p> <p>The fundamental limitations of the <span class="hlt">optimal</span> control of <span class="hlt">dynamic</span> systems with random parameters are analyzed by studying a scalar linear-quadratic <span class="hlt">optimal</span> control example. It is demonstrated that optimum long-range decision making is possible only if the <span class="hlt">dynamic</span> uncertainty (quantified by the means and covariances of the random parameters) is below a certain threshold. If this threshold is exceeded, there do not exist optimum decision rules. This phenomenon is called the 'uncertainty threshold principle'. The implications of this phenomenon to the field of modelling, identification, and adaptive control are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JPhCS.803a2069K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JPhCS.803a2069K"><span>Comparison of kinematic and <span class="hlt">dynamic</span> leg trajectory <span class="hlt">optimization</span> techniques for biped robot locomotion</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Khusainov, R.; Klimchik, A.; Magid, E.</p> <p>2017-01-01</p> <p>The paper presents comparison analysis of two approaches in defining leg trajectories for biped locomotion. The first one operates only with kinematic limitations of leg joints and finds the maximum possible locomotion speed for given limits. The second approach defines leg trajectories from the <span class="hlt">dynamic</span> stability point of view and utilizes ZMP criteria. We show that two methods give different trajectories and demonstrate that trajectories based on pure <span class="hlt">dynamic</span> <span class="hlt">optimization</span> cannot be realized due to joint limits. Kinematic <span class="hlt">optimization</span> provides unstable solution which can be balanced by upper body movement.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/289974','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/289974"><span>Discrete-time <span class="hlt">dynamic</span> user-<span class="hlt">optimal</span> departure time/route choice model</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Chen, H.K.; Hsueh, C.F.</p> <p>1998-05-01</p> <p>This paper concerns a discrete-time, link-based, <span class="hlt">dynamic</span> user-<span class="hlt">optimal</span> departure time/route choice model using the variational inequality approach. The model complies with a <span class="hlt">dynamic</span> user-<span class="hlt">optimal</span> equilibrium condition in which for each origin-destination pair, the actual route travel times experienced by travelers, regardless the departure time, is equal and minimal. A nested diagonalization procedure is proposed to solve the model. Numerical examples are then provided for demonstration and detailed elaboration for multiple solutions and Braess`s paradox.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JChPh.144v4109B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JChPh.144v4109B"><span>Wave packet <span class="hlt">dynamics</span> in the <span class="hlt">optimal</span> superadiabatic approximation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Betz, V.; Goddard, B. D.; Manthe, U.</p> <p>2016-06-01</p> <p>We explain the concept of superadiabatic representations and show how in the context of electronically non-adiabatic transitions they lead to an explicit formula that can be used to predict transitions at avoided crossings. Based on this formula, we present a simple method for computing wave packet <span class="hlt">dynamics</span> across avoided crossings. Only knowledge of the adiabatic potential energy surfaces near the avoided crossing is required for the computation. In particular, this means that no diabatization procedure is necessary, the adiabatic electronic energies can be computed on the fly, and they only need to be computed to higher accuracy when an avoided crossing is detected. We test the quality of our method on the paradigmatic example of photo-dissociation of NaI, finding very good agreement with results of exact wave packet calculations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1155060','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1155060"><span><span class="hlt">Dynamical</span> Arrest, Structural Disorder, and <span class="hlt">Optimization</span> of Organic Photovoltaic Devices</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Gould, Ian; Dmitry, Matyushov</p> <p>2014-09-11</p> <p>This project describes fundamental experimental and theoretical work that relates to charge separation and migration in the solid, heterogeneous or aggregated state. Marcus theory assumes a system in equilibrium with all possible solvent (dipolar) configurations, with rapid interconversion among these on the ET timescale. This project has addressed the more general situation where the medium is at least partially frozen on the ET timescale, i.e. under conditions of <span class="hlt">dynamical</span> arrest. The approach combined theory and experiment and includes: (1) Computer simulations of model systems, (2) Development of analytical procedures consistent with computer experiment and (3) Experimental studies and testing of the formal theories on this data. Electron transfer processes are unique as a consequence of the close connection between kinetics, spectroscopy and theory, which is an essential component of this work.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4935895','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4935895"><span><span class="hlt">Optimal</span> Perceived Timing: Integrating Sensory Information with <span class="hlt">Dynamically</span> Updated Expectations</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Di Luca, Massimiliano; Rhodes, Darren</p> <p>2016-01-01</p> <p>The environment has a temporal structure, and knowing when a stimulus will appear translates into increased perceptual performance. Here we investigated how the human brain exploits temporal regularity in stimulus sequences for perception. We find that the timing of stimuli that occasionally deviate from a regularly paced sequence is perceptually distorted. Stimuli presented earlier than expected are perceptually delayed, whereas stimuli presented on time and later than expected are perceptually accelerated. This result suggests that the brain regularizes slightly deviant stimuli with an asymmetry that leads to the perceptual acceleration of expected stimuli. We present a Bayesian model for the combination of <span class="hlt">dynamically</span>-updated expectations, in the form of a priori probability of encountering future stimuli, with incoming sensory information. The asymmetries in the results are accounted for by the asymmetries in the distributions involved in the computational process. PMID:27385184</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4707024','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4707024"><span>Modeling Illicit Drug Use <span class="hlt">Dynamics</span> and Its <span class="hlt">Optimal</span> Control Analysis</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2015-01-01</p> <p>The global burden of death and disability attributable to illicit drug use, remains a significant threat to public health for both developed and developing nations. This paper presents a new mathematical modeling framework to investigate the effects of illicit drug use in the community. In our model the transmission process is captured as a social “contact” process between the susceptible individuals and illicit drug users. We conduct both epidemic and endemic analysis, with a focus on the threshold <span class="hlt">dynamics</span> characterized by the basic reproduction number. Using our model, we present illustrative numerical results with a case study in Cape Town, Gauteng, Mpumalanga and Durban communities of South Africa. In addition, the basic model is extended to incorporate time dependent intervention strategies. PMID:26819625</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/891553','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/891553"><span><span class="hlt">OPTIMIZING</span> THE <span class="hlt">DYNAMIC</span> APERTURE FOR TRIPLE BEND ACHROMATIC LATTICES.</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>KRAMER, S.L.; BENGTSSON, J.</p> <p>2006-06-26</p> <p>The Triple Bend Achromatic (TBA) lattice has the potential for lower natural emittance per period than the Double Bend Achromatic (DBA) lattice for high brightness light sources. However, the DBA has been chosen for 3rd generation light sources more often due to the higher number of undulator straight section available for a comparable emittance. The TBA has considerable flexibility in linear optics tuning while maintaining this emittance advantage. We have used the tune and chromaticity flexibility of a TBA lattice to minimize the lowest order nonlinearities to implement a 3rd order achromatic tune, while maintaining a constant emittance. This frees the geometric sextupoles to counter the higher order nonlinearities. This procedure is being used to improve the nonlinear <span class="hlt">dynamics</span> of the TBA as a proposed lattice for NSLS-II facility. The flexibility of the TBA lattice will also provide for future upgrade capabilities of the beam parameters.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AIPC.1332..289A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AIPC.1332..289A"><span><span class="hlt">Optimal</span> mutation rates in <span class="hlt">dynamic</span> environments: The eigen model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ancliff, Mark; Park, Jeong-Man</p> <p>2011-03-01</p> <p>We consider the Eigen quasispecies model with a <span class="hlt">dynamic</span> environment. For an environment with sharp-peak fitness in which the most-fit sequence moves by k spin-flips each period T we find an asymptotic stationary state in which the quasispecies population changes regularly according to the regular environmental change. From this stationary state we estimate the maximum and the minimum mutation rates for a quasispecies to survive under the changing environment and calculate the optimum mutation rate that maximizes the population growth. Interestingly we find that the optimum mutation rate in the Eigen model is lower than that in the Crow-Kimura model, and at their optimum mutation rates the corresponding mean fitness in the Eigen model is lower than that in the Crow-Kimura model, suggesting that the mutation process which occurs in parallel to the replication process as in the Crow-Kimura model gives an adaptive advantage under changing environment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010PhRvE..82b1904A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010PhRvE..82b1904A"><span><span class="hlt">Optimal</span> mutation rates in <span class="hlt">dynamic</span> environments: The Eigen model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ancliff, Mark; Park, Jeong-Man</p> <p>2010-08-01</p> <p>We consider the Eigen quasispecies model with a <span class="hlt">dynamic</span> environment. For an environment with sharp-peak fitness in which the most-fit sequence moves by k spin-flips each period T we find an asymptotic stationary state in which the quasispecies population changes regularly according to the regular environmental change. From this stationary state we estimate the maximum and the minimum mutation rates for a quasispecies to survive under the changing environment and calculate the optimum mutation rate that maximizes the population growth. Interestingly we find that the optimum mutation rate in the Eigen model is lower than that in the Crow-Kimura model, and at their optimum mutation rates the corresponding mean fitness in the eigenmodel is lower than that in the Crow-Kimura model, suggesting that the mutation process which occurs in parallel to the replication process as in the Crow-Kimura model gives an adaptive advantage under changing environment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AcAau.105..428H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AcAau.105..428H"><span><span class="hlt">Dynamic</span> modeling and <span class="hlt">optimization</span> for space logistics using time-expanded networks</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ho, Koki; de Weck, Olivier L.; Hoffman, Jeffrey A.; Shishko, Robert</p> <p>2014-12-01</p> <p>This research develops a <span class="hlt">dynamic</span> logistics network formulation for lifecycle <span class="hlt">optimization</span> of mission sequences as a system-level integrated method to find an <span class="hlt">optimal</span> combination of technologies to be used at each stage of the campaign. This formulation can find the <span class="hlt">optimal</span> transportation architecture considering its technology trades over time. The proposed methodologies are inspired by the ground logistics analysis techniques based on linear programming network <span class="hlt">optimization</span>. Particularly, the time-expanded network and its extension are developed for <span class="hlt">dynamic</span> space logistics network <span class="hlt">optimization</span> trading the quality of the solution with the computational load. In this paper, the methodologies are applied to a human Mars exploration architecture design problem. The results reveal multiple <span class="hlt">dynamic</span> system-level trades over time and give recommendation of the <span class="hlt">optimal</span> strategy for the human Mars exploration architecture. The considered trades include those between In-Situ Resource Utilization (ISRU) and propulsion technologies as well as the orbit and depot location selections over time. This research serves as a precursor for eventual permanent settlement and colonization of other planets by humans and us becoming a multi-planet species.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25570695','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25570695"><span>An <span class="hlt">optimized</span> ultrasound digital beamformer with <span class="hlt">dynamic</span> focusing implemented on FPGA.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Almekkawy, Mohamed; Xu, Jingwei; Chirala, Mohan</p> <p>2014-01-01</p> <p>We present a resource-<span class="hlt">optimized</span> <span class="hlt">dynamic</span> digital beamformer for an ultrasound system based on a field-programmable gate array (FPGA). A comprehensive 64-channel receive beamformer with full <span class="hlt">dynamic</span> focusing is embedded in the Altera Arria V FPGA chip. To improve spatial and contrast resolution, full <span class="hlt">dynamic</span> beamforming is implemented by a novel method with resource <span class="hlt">optimization</span>. This was conceived using the implementation of the delay summation through a bulk (coarse) delay and fractional (fine) delay. The sampling frequency is 40 MHz and the beamformer includes a 240 MHz polyphase filter that enhances the temporal resolution of the system while relaxing the Analog-to-Digital converter (ADC) bandwidth requirement. The results indicate that our 64-channel <span class="hlt">dynamic</span> beamformer architecture is amenable for a low power FPGA-based implementation in a portable ultrasound system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3756725','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3756725"><span>An Improved Co-evolutionary Particle Swarm <span class="hlt">Optimization</span> for Wireless Sensor Networks with <span class="hlt">Dynamic</span> Deployment</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Wang, Xue; Wang, Sheng; Ma, Jun-Jie</p> <p>2007-01-01</p> <p>The effectiveness of wireless sensor networks (WSNs) depends on the coverage and target detection probability provided by <span class="hlt">dynamic</span> deployment, which is usually supported by the virtual force (VF) algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm <span class="hlt">optimization</span> (PSO) is introduced as another <span class="hlt">dynamic</span> deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a <span class="hlt">dynamic</span> deployment algorithm which is named “virtual force directed co-evolutionary particle swarm optimization” (VFCPSO), since this algorithm combines the co-evolutionary particle swarm <span class="hlt">optimization</span> (CPSO) with the VF algorithm, whereby the CPSO uses multiple swarms to <span class="hlt">optimize</span> different components of the solution vectors for <span class="hlt">dynamic</span> deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global <span class="hlt">optimal</span> solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for <span class="hlt">dynamic</span> deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002JMP....43.2097B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002JMP....43.2097B"><span>Reversing quantum <span class="hlt">dynamics</span> with near-<span class="hlt">optimal</span> quantum and classical fidelity</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barnum, H.; Knill, E.</p> <p>2002-05-01</p> <p>We consider the problem of reversing quantum <span class="hlt">dynamics</span>, with the goal of preserving an initial state's quantum entanglement or classical correlation with a reference system. We exhibit an approximate reversal operation, adapted to the initial density operator and the "noise" <span class="hlt">dynamics</span> to be reversed. We show that its error in preserving either quantum or classical information is no more than twice that of the <span class="hlt">optimal</span> reversal operation. Applications to quantum algorithms and information transmission are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA545617','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA545617"><span>Characterization and Performance <span class="hlt">Optimization</span> of a Cementitious Composite for Quasi-Static and <span class="hlt">Dynamic</span> Loads</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2011-01-01</p> <p>rapid-set, high-strength geopolymer cement under quasi-static and <span class="hlt">dynamic</span> loads. Four unique tensile experiments were conducted to characterize and...review under responsibility of ICM11 Keywords: Material characterization, fiber reinforced concrete, geopolymer cement 1. Introduction A mission... geopolymer cement under quasi-static and <span class="hlt">dynamic</span> loads. Four unique tensile experiments were conducted to characterize and <span class="hlt">optimize</span> material response of the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhRvE..90d2812T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhRvE..90d2812T"><span>Collision-free nonuniform <span class="hlt">dynamics</span> within continuous <span class="hlt">optimal</span> velocity models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tordeux, Antoine; Seyfried, Armin</p> <p>2014-10-01</p> <p><span class="hlt">Optimal</span> velocity (OV) car-following models give with few parameters stable stop-and -go waves propagating like in empirical data. Unfortunately, classical OV models locally oscillate with vehicles colliding and moving backward. In order to solve this problem, the models have to be completed with additional parameters. This leads to an increase of the complexity. In this paper, a new OV model with no additional parameters is defined. For any value of the inputs, the model is intrinsically asymmetric and collision-free. This is achieved by using a first-order ordinary model with two predecessors in interaction, instead of the usual inertial delayed first-order or second-order models coupled with the predecessor. The model has stable uniform solutions as well as various stable stop-and -go patterns with bimodal distribution of the speed. As observable in real data, the modal speed values in congested states are not restricted to the free flow speed and zero. They depend on the form of the OV function. Properties of linear, concave, convex, or sigmoid speed functions are explored with no limitation due to collisions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1988JSV...123..157J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1988JSV...123..157J"><span><span class="hlt">Optimal</span> design of linear and non-linear <span class="hlt">dynamic</span> vibration absorbers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jordanov, I. N.; Cheshankov, B. I.</p> <p>1988-05-01</p> <p>An efficient numerical method is applied to obtain <span class="hlt">optimal</span> parameters for both linear and non-linear damped <span class="hlt">dynamic</span> vibration absorbers. The minimization of the vibration response has been carried out for damped as well as undamped force excited primary systems with linear and non-linear spring characteristics. Comparison is made with the optimum absorber parameters that are determined by using Den Hartog's classical results in the linear case. Six <span class="hlt">optimization</span> criteria by which the response is minimized over narrow and broad frequency bands are examined. Pareto <span class="hlt">optimal</span> solutions of the multi-objective decision making problem are obtained.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PhRvA..94f3421G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PhRvA..94f3421G"><span><span class="hlt">Optimal</span> control with nonadiabatic molecular <span class="hlt">dynamics</span>: Application to the Coulomb explosion of sodium clusters</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gómez Pueyo, Adrián; Budagosky M., Jorge A.; Castro, Alberto</p> <p>2016-12-01</p> <p>We present an implementation of <span class="hlt">optimal</span> control theory for the first-principles nonadiabatic Ehrenfest molecular <span class="hlt">dynamics</span> model, which describes a condensed matter system by considering classical point-particle nuclei, and quantum electrons, handled in our case with time-dependent density-functional theory. The scheme is demonstrated by <span class="hlt">optimizing</span> the Coulomb explosion of small sodium clusters: the algorithm is set to find the <span class="hlt">optimal</span> femtosecond laser pulses that disintegrate the clusters, for a given total duration, fluence, and cutoff frequency. We describe the numerical details and difficulties of the method.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20447042','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20447042"><span>Shape <span class="hlt">optimization</span> of the diffuser blade of an axial blood pump by computational fluid <span class="hlt">dynamics</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zhu, Lailai; Zhang, Xiwen; Yao, Zhaohui</p> <p>2010-03-01</p> <p>Computational fluid <span class="hlt">dynamics</span> (CFD) has been a viable and effective way to predict hydraulic performance, flow field, and shear stress distribution within a blood pump. We developed an axial blood pump with CFD and carried out a CFD-based shape <span class="hlt">optimization</span> of the diffuser blade to enhance pressure output and diminish backflow in the impeller-diffuser connecting region at a fixed design point. Our <span class="hlt">optimization</span> combined a computer-aided design package, a mesh generator, and a CFD solver in an automation environment with process integration and <span class="hlt">optimization</span> software. A genetic <span class="hlt">optimization</span> algorithm was employed to find the pareto-<span class="hlt">optimal</span> designs from which we could make trade-off decisions. Finally, a set of representative designs was analyzed and compared on the basis of the energy equation. The role of the inlet angle of the diffuser blade was analyzed, accompanied by its relationship with pressure output and backflow in the impeller-diffuser connecting region.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19920004750','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19920004750"><span>A new method of <span class="hlt">optimal</span> design for a two-dimensional diffuser by using <span class="hlt">dynamic</span> programming</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gu, Chuangang; Zhang, Moujin; Chen, XI; Miao, Yongmiao</p> <p>1991-01-01</p> <p>A new method for predicting the <span class="hlt">optimal</span> velocity distribution on the wall of a two dimensional diffuser is presented. The method uses <span class="hlt">dynamic</span> programming to solve the <span class="hlt">optimal</span> control problem with inequality constraints of state variables. The physical model of <span class="hlt">optimization</span> is designed to prevent the separation of the boundary layer while approaching the maximum pressure ratio in a diffuser of a specified length. The computational results are in fair agreement with the experimental ones. <span class="hlt">Optimal</span> velocity distribution on a diffuser wall is said to occur when the flow decelerates quickly at first and then smoothly, while the flow is near separation, but always protected from it. The <span class="hlt">optimal</span> velocity distribution can be used to design the contour of the diffuser.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3985312','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3985312"><span>Fuzzy Mixed Assembly Line Sequencing and Scheduling <span class="hlt">Optimization</span> Model Using Multiobjective <span class="hlt">Dynamic</span> Fuzzy GA</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari</p> <p>2014-01-01</p> <p>A new multiobjective <span class="hlt">dynamic</span> fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this <span class="hlt">optimization</span> model. In establishing the FAGA, five <span class="hlt">dynamic</span> fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning <span class="hlt">dynamic</span> fuzzy controller (ALDFC) technique. The enhanced algorithm <span class="hlt">dynamically</span> adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by <span class="hlt">dynamic</span> adjustment and control of the five parameters. Verification and validation of the <span class="hlt">dynamic</span> fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing <span class="hlt">optimization</span> problem. The simulation results highlight that the performance and efficacy of the proposed novel <span class="hlt">optimization</span> algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model. PMID:24982962</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JHyd..529..928J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JHyd..529..928J"><span>Credibility theory based <span class="hlt">dynamic</span> control bound <span class="hlt">optimization</span> for reservoir flood limited water level</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jiang, Zhiqiang; Sun, Ping; Ji, Changming; Zhou, Jianzhong</p> <p>2015-10-01</p> <p>The <span class="hlt">dynamic</span> control operation of reservoir flood limited water level (FLWL) can solve the contradictions between reservoir flood control and beneficial operation well, and it is an important measure to make sure the security of flood control and realize the flood utilization. The <span class="hlt">dynamic</span> control bound of FLWL is a fundamental key element for implementing reservoir <span class="hlt">dynamic</span> control operation. In order to <span class="hlt">optimize</span> the <span class="hlt">dynamic</span> control bound of FLWL by considering flood forecasting error, this paper took the forecasting error as a fuzzy variable, and described it with the emerging credibility theory in recent years. By combining the flood forecasting error quantitative model, a credibility-based fuzzy chance constrained model used to <span class="hlt">optimize</span> the <span class="hlt">dynamic</span> control bound was proposed in this paper, and fuzzy simulation technology was used to solve the model. The FENGTAN reservoir in China was selected as a case study, and the results show that, compared with the original operation water level, the initial operation water level (IOWL) of FENGTAN reservoir can be raised 4 m, 2 m and 5.5 m respectively in the three division stages of flood season, and without increasing flood control risk. In addition, the rationality and feasibility of the proposed forecasting error quantitative model and credibility-based <span class="hlt">dynamic</span> control bound <span class="hlt">optimization</span> model are verified by the calculation results of extreme risk theory.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24982962','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24982962"><span>Fuzzy mixed assembly line sequencing and scheduling <span class="hlt">optimization</span> model using multiobjective <span class="hlt">dynamic</span> fuzzy GA.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari</p> <p>2014-01-01</p> <p>A new multiobjective <span class="hlt">dynamic</span> fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this <span class="hlt">optimization</span> model. In establishing the FAGA, five <span class="hlt">dynamic</span> fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning <span class="hlt">dynamic</span> fuzzy controller (ALDFC) technique. The enhanced algorithm <span class="hlt">dynamically</span> adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by <span class="hlt">dynamic</span> adjustment and control of the five parameters. Verification and validation of the <span class="hlt">dynamic</span> fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing <span class="hlt">optimization</span> problem. The simulation results highlight that the performance and efficacy of the proposed novel <span class="hlt">optimization</span> algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1345931-co-optimization-co2-eor-storage-processes-mature-oil-reservoirs','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1345931-co-optimization-co2-eor-storage-processes-mature-oil-reservoirs"><span>Co-<span class="hlt">Optimization</span> of CO2-EOR and Storage Processes in Mature Oil Reservoirs</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Ampomah, William; Balch, Robert S.; Grigg, Reid B.; ...</p> <p>2016-08-02</p> <p>This article presents an <span class="hlt">optimization</span> methodology for CO2 enhanced oil recovery in partially depleted reservoirs. A field-scale compositional reservoir flow model was developed for assessing the performance history of an active CO2 flood and for <span class="hlt">optimizing</span> both oil production and CO2 storage in the Farnsworth Unit (FWU), Ochiltree County, Texas. A geological framework model constructed from geophysical, geological, and engineering data acquired from the FWU was the basis for all reservoir simulations and the <span class="hlt">optimization</span> method. An equation of state was calibrated with laboratory fluid analyses and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). Initial history calibrationsmore » of primary, secondary and tertiary recovery were conducted as the basis for the study. After a good match was achieved, an <span class="hlt">optimization</span> approach consisting of a proxy or surrogate model was constructed with a polynomial response surface method (PRSM). The PRSM utilized an objective function that maximized both oil recovery and CO2 storage. Experimental design was used to link uncertain parameters to the objective function. Control variables considered in this study included: water alternating gas cycle and ratio, production rates and bottom-hole pressure of injectors and producers. Other key parameters considered in the modeling process were CO2 purchase, gas recycle and addition of infill wells and/or patterns. The PRSM proxy model was ‘trained’ or calibrated with a series of training simulations. This involved an iterative process until the surrogate model reached a specific validation criterion. A sensitivity analysis was first conducted to ascertain which of these control variables to retain in the surrogate model. A genetic algorithm with a <span class="hlt">mixed-integer</span> capability <span class="hlt">optimization</span> approach was employed to determine the optimum developmental strategy to maximize both oil recovery and CO2 storage. The proxy model reduced the computational cost</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006NIMPA.557...87R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006NIMPA.557...87R"><span>Emittance compensation with <span class="hlt">dynamically</span> <span class="hlt">optimized</span> photoelectron beam profiles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rosenzweig, J. B.; Cook, A. M.; England, R. J.; Dunning, M.; Anderson, S. G.; Ferrario, Massimo</p> <p>2006-02-01</p> <p>Much of the theory and experimentation concerning creation of a high-brightness electron beam from a photocathode, and then applying emittance compensation techniques, assumes that one must strive for a uniform density electron beam, having a cylindrical shape. On the other hand, this shape has large nonlinearities in the space-charge field profiles near the beam's longitudinal extrema. These nonlinearities are known to produce both transverse and longitudinal emittance growth. On the other hand, it has recently been shown by Luiten that by illuminating the cathode with an ultra-short laser pulse of appropriate transverse profile, a uniform density, ellipsoidally shaped bunch is <span class="hlt">dynamically</span> formed, which then has linear space-charge fields in all dimensions inside of the bunch. We study here this process, and its marriage to the standard emittance compensation scenario that is implemented in most recent photoinjectors. It is seen that the two processes are compatible, with simulations indicating a very high brightness beam can be obtained. The robustness of this scheme to systematic errors is examined. Prospects for experimental tests of this scheme are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3532319','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3532319"><span><span class="hlt">Dynamic</span> <span class="hlt">optimization</span> of distributed biological systems using robust and efficient numerical techniques</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2012-01-01</p> <p>Background Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as <span class="hlt">dynamic</span> <span class="hlt">optimization</span> problems which are particularly challenging when the system is described by partial differential equations. This work addresses the numerical solution of such <span class="hlt">dynamic</span> <span class="hlt">optimization</span> problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the <span class="hlt">optimization</span> problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Results Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global <span class="hlt">optimization</span> methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. Conclusions In the process of chemotaxis the objective was to efficiently compute the time-varying <span class="hlt">optimal</span> concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how <span class="hlt">dynamic</span> <span class="hlt">optimization</span> may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EnOp...44..565I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EnOp...44..565I"><span>Establishing <span class="hlt">optimal</span> project-level strategies for pavement maintenance and rehabilitation - A framework and case study</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Irfan, Muhammad; Bilal Khurshid, Muhammad; Bai, Qiang; Labi, Samuel; Morin, Thomas L.</p> <p>2012-05-01</p> <p>This article presents a framework and an illustrative example for identifying the <span class="hlt">optimal</span> pavement maintenance and rehabilitation (M&R) strategy using a <span class="hlt">mixed-integer</span> nonlinear programming model. The objective function is to maximize the cost-effectiveness expressed as the ratio of the effectiveness to the cost. The constraints for the <span class="hlt">optimization</span> problem are related to performance, budget, and choice. Two different formulations of effectiveness are derived using treatment-specific performance models for each constituent treatment of the strategy; and cost is expressed in terms of the agency and user costs over the life cycle. The proposed methodology is demonstrated using a case study. Probability distributions are established for the <span class="hlt">optimization</span> input variables and Monte Carlo simulations are carried out to yield <span class="hlt">optimal</span> solutions. Using the results of these simulations, M&R strategy contours are developed as a novel tool that can help pavement managers quickly identify the <span class="hlt">optimal</span> M&R strategy for a given pavement section.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930050979&hterms=static+dynamic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dstatic%2Bdynamic','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930050979&hterms=static+dynamic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dstatic%2Bdynamic"><span>Construction and parameterization of all static and <span class="hlt">dynamic</span> H2-<span class="hlt">optimal</span> state feedback solutions, <span class="hlt">optimal</span> fixed modes, and fixed decoupling zeros</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chen, Ben M.; Saberi, Ali; Sannuti, Peddapullaiah; Shamash, Yacov</p> <p>1993-01-01</p> <p>This paper considers an H2 <span class="hlt">optimization</span> problem via state feedback. The class of problems dealt with here are general singular type which have a left invertible transfer matrix function from the control input to the controlled output. This class subsumes the regular H2 <span class="hlt">optimization</span> problems. The paper constructs and parameterizes all the static and <span class="hlt">dynamic</span> H2 <span class="hlt">optimal</span> state feedback solutions. Moreover, all the eigenvalues of an <span class="hlt">optimal</span> closed-loop system are characterized. All <span class="hlt">optimal</span> closed-loop systems share a set of eigenvalues which are termed here as the <span class="hlt">optimal</span> fixed modes. Every H2 <span class="hlt">optimal</span> controller must assign among the closed-loop eigenvalues the set of <span class="hlt">optimal</span> fixed modes. This set of <span class="hlt">optimal</span> fixed modes includes a set of <span class="hlt">optimal</span> fixed decoupling zeros which shows the minimum absolutely necessary number and locations of pole-zero cancellations present in any H2 <span class="hlt">optimal</span> design. It is shown that both the sets of <span class="hlt">optimal</span> fixed modes and <span class="hlt">optimal</span> fixed decoupling zeros do not vary depending upon whether the static or the <span class="hlt">dynamic</span> controllers are used.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26280190','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26280190"><span>Multi-host transmission <span class="hlt">dynamics</span> of schistosomiasis and its <span class="hlt">optimal</span> control.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ding, Chunxiao; Qiu, Zhipeng; Zhu, Huaiping</p> <p>2015-10-01</p> <p>In this paper we formulate a <span class="hlt">dynamical</span> model to study the transmission <span class="hlt">dynamics</span> of schistosomiasis in humans and snails. We also incorporate bovines in the model to study their impact on transmission and controlling the spread of Schistosoma japonicum in humans in China. The <span class="hlt">dynamics</span> of the model is rigorously analyzed by using the theory of <span class="hlt">dynamical</span> systems. The theoretical results show that the disease free equilibrium is globally asymptotically stable if R0 < 1, and if R0 > 1 the system has only one positive equilibrium. The local stability of the unique positive equilibrium is investigated and sufficient conditions are also provided for the global stability of the positive equilibrium. The <span class="hlt">optimal</span> control theory are further applied to the model to study the corresponding <span class="hlt">optimal</span> control problem. Both analytical and numerical results suggest that: (a) the infected bovines play an important role in the spread of schistosomiasis among humans, and killing the infected bovines will be useful to prevent transmission of schistosomiasis among humans; (b) <span class="hlt">optimal</span> control strategy performs better than the constant controls in reducing the prevalence of the infected human and the cost for implementing <span class="hlt">optimal</span> control is much less than that for constant controls; and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AIPC.1389.1280P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AIPC.1389.1280P"><span>A <span class="hlt">Dynamic</span> Process Model for <span class="hlt">Optimizing</span> the Hospital Environment Cash-Flow</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pater, Flavius; Rosu, Serban</p> <p>2011-09-01</p> <p>In this article is presented a new approach to some fundamental techniques of solving <span class="hlt">dynamic</span> programming problems with the use of functional equations. We will analyze the problem of minimizing the cost of treatment in a hospital environment. Mathematical modeling of this process leads to an <span class="hlt">optimal</span> control problem with a finite horizon.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010IEITI..93..531Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010IEITI..93..531Z"><span>An <span class="hlt">Optimal</span> Algorithm towards Successive Location Privacy in Sensor Networks with <span class="hlt">Dynamic</span> Programming</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Baokang; Wang, Dan; Shao, Zili; Cao, Jiannong; Chan, Keith C. C.; Su, Jinshu</p> <p></p> <p>In wireless sensor networks, preserving location privacy under successive inference attacks is extremely critical. Although this problem is NP-complete in general cases, we propose a <span class="hlt">dynamic</span> programming based algorithm and prove it is <span class="hlt">optimal</span> in special cases where the correlation only exists between p immediate adjacent observations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=320519','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=320519"><span>Evaluation of <span class="hlt">dynamically</span> dimensioned search algorithm for <span class="hlt">optimizing</span> SWAT by altering sampling distributions and searching range</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>The primary advantage of <span class="hlt">Dynamically</span> Dimensioned Search algorithm (DDS) is that it outperforms many other <span class="hlt">optimization</span> techniques in both convergence speed and the ability in searching for parameter sets that satisfy statistical guidelines while requiring only one algorithm parameter (perturbation f...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010IEITC..91..110H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010IEITC..91..110H"><span>Autonomous and Decentralized <span class="hlt">Optimization</span> of Large-Scale Heterogeneous Wireless Networks by Neural Network <span class="hlt">Dynamics</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hasegawa, Mikio; Tran, Ha Nguyen; Miyamoto, Goh; Murata, Yoshitoshi; Harada, Hiroshi; Kato, Shuzo</p> <p></p> <p>We propose a neurodynamical approach to a large-scale <span class="hlt">optimization</span> problem in Cognitive Wireless Clouds, in which a huge number of mobile terminals with multiple different air interfaces autonomously utilize the most appropriate infrastructure wireless networks, by sensing available wireless networks, selecting the most appropriate one, and reconfiguring themselves with seamless handover to the target networks. To deal with such a cognitive radio network, game theory has been applied in order to analyze the stability of the <span class="hlt">dynamical</span> systems consisting of the mobile terminals' distributed behaviors, but it is not a tool for globally <span class="hlt">optimizing</span> the state of the network. As a natural <span class="hlt">optimization</span> <span class="hlt">dynamical</span> system model suitable for large-scale complex systems, we introduce the neural network <span class="hlt">dynamics</span> which converges to an <span class="hlt">optimal</span> state since its property is to continually decrease its energy function. In this paper, we apply such neurodynamics to the <span class="hlt">optimization</span> problem of radio access technology selection. We compose a neural network that solves the problem, and we show that it is possible to improve total average throughput simply by using distributed and autonomous neuron updates on the terminal side.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25794375','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25794375"><span>Adaptive <span class="hlt">optimal</span> control of highly dissipative nonlinear spatially distributed processes with neuro-<span class="hlt">dynamic</span> programming.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong</p> <p>2015-04-01</p> <p>Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system <span class="hlt">dynamics</span> of industrial spatially distributed processes (SDPs). In this paper, we consider the <span class="hlt">optimal</span> control problem of the general highly dissipative SDPs, and propose an adaptive <span class="hlt">optimal</span> control approach based on neuro-<span class="hlt">dynamic</span> programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant <span class="hlt">dynamics</span> of the PDE system. Subsequently, the <span class="hlt">optimal</span> control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive <span class="hlt">optimal</span> control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive <span class="hlt">optimal</span> control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5079478','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5079478"><span>AMIGO2, a toolbox for <span class="hlt">dynamic</span> modeling, <span class="hlt">optimization</span> and control in systems biology</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Balsa-Canto, Eva; Henriques, David; Gábor, Attila; Banga, Julio R.</p> <p>2016-01-01</p> <p>Motivation: Many problems of interest in <span class="hlt">dynamic</span> modeling and control of biological systems can be posed as non-linear <span class="hlt">optimization</span> problems subject to algebraic and <span class="hlt">dynamic</span> constraints. In the context of modeling, this is the case of, e.g. parameter estimation, <span class="hlt">optimal</span> experimental design and <span class="hlt">dynamic</span> flux balance analysis. In the context of control, model-based metabolic engineering or drug dose <span class="hlt">optimization</span> problems can be formulated as (multi-objective) <span class="hlt">optimal</span> control problems. Finding a solution to those problems is a very challenging task which requires advanced numerical methods. Results: This work presents the AMIGO2 toolbox: the first multiplatform software tool that automatizes the solution of all those problems, offering a suite of state-of-the-art (multi-objective) global <span class="hlt">optimizers</span> and advanced simulation approaches. Availability and Implementation: The toolbox and its documentation are available at: sites.google.com/site/amigo2toolbox. Contact: ebalsa@iim.csic.es Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27378288</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4101942','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4101942"><span>Improving the <span class="hlt">Dynamic</span> Characteristics of Body-in-White Structure Using Structural <span class="hlt">Optimization</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Yahaya Rashid, Aizzat S.; Mohamed Haris, Sallehuddin; Alias, Anuar</p> <p>2014-01-01</p> <p>The <span class="hlt">dynamic</span> behavior of a body-in-white (BIW) structure has significant influence on the noise, vibration, and harshness (NVH) and crashworthiness of a car. Therefore, by improving the <span class="hlt">dynamic</span> characteristics of BIW, problems and failures associated with resonance and fatigue can be prevented. The design objectives attempt to improve the existing torsion and bending modes by using structural <span class="hlt">optimization</span> subjected to <span class="hlt">dynamic</span> load without compromising other factors such as mass and stiffness of the structure. The natural frequency of the design was modified by identifying and reinforcing the structure at critical locations. These crucial points are first identified by topology <span class="hlt">optimization</span> using mass and natural frequencies as the design variables. The individual components obtained from the analysis go through a size <span class="hlt">optimization</span> step to find their target thickness of the structure. The thickness of affected regions of the components will be modified according to the analysis. The results of both <span class="hlt">optimization</span> steps suggest several design modifications to achieve the target vibration specifications without compromising the stiffness of the structure. A method of combining both <span class="hlt">optimization</span> approaches is proposed to improve the design modification process. PMID:25101312</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012IJSyS..43..809L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012IJSyS..43..809L"><span>Nonlinear <span class="hlt">dynamical</span> systems of fed-batch fermentation and their <span class="hlt">optimal</span> control</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Chongyang; Gong, Zhaohua; Feng, Enmin; Yin, Hongchao</p> <p>2012-05-01</p> <p>In this article, we propose a controlled nonlinear <span class="hlt">dynamical</span> system with variable switching instants, in which the feeding rate of glycerol is regarded as the control function and the moments between the batch and feeding processes as switching instants, to formulate the fed-batch fermentation of glycerol bioconversion to 1,3-propanediol (1,3-PD). Some important properties of the proposed system and its solution are then discussed. Taking the concentration of 1,3-PD at the terminal time as the cost functional, we establish an <span class="hlt">optimal</span> control model involving the controlled nonlinear <span class="hlt">dynamical</span> system and subject to continuous state inequality constraints. The existence of the <span class="hlt">optimal</span> control is also proved. A computational approach is constructed on the basis of constraint transcription and smoothing approximation techniques. Numerical results show that, by employing the <span class="hlt">optimal</span> control strategy, the concentration of 1,3-PD at the terminal time can be increased considerably.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5375833','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5375833"><span><span class="hlt">Optimal</span> Power Control in Wireless Powered Sensor Networks: A <span class="hlt">Dynamic</span> Game-Based Approach</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Xu, Haitao; Guo, Chao; Zhang, Long</p> <p>2017-01-01</p> <p>In wireless powered sensor networks (WPSN), it is essential to research uplink transmit power control in order to achieve throughput performance balancing and energy scheduling. Each sensor should have an <span class="hlt">optimal</span> transmit power level for revenue maximization. In this paper, we discuss a <span class="hlt">dynamic</span> game-based algorithm for <span class="hlt">optimal</span> power control in WPSN. The main idea is to use the non-cooperative differential game to control the uplink transmit power of wireless sensors in WPSN, to extend their working hours and to meet QoS (Quality of Services) requirements. Subsequently, the Nash equilibrium solutions are obtained through Bellman <span class="hlt">dynamic</span> programming. At the same time, an uplink power control algorithm is proposed in a distributed manner. Through numerical simulations, we demonstrate that our algorithm can obtain <span class="hlt">optimal</span> power control and reach convergence for an infinite horizon. PMID:28282945</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19730019051','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19730019051"><span>Perform - A performance <span class="hlt">optimizing</span> computer program for <span class="hlt">dynamic</span> systems subject to transient loadings</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pilkey, W. D.; Wang, B. P.; Yoo, Y.; Clark, B.</p> <p>1973-01-01</p> <p>A description and applications of a computer capability for determining the ultimate <span class="hlt">optimal</span> behavior of a <span class="hlt">dynamically</span> loaded structural-mechanical system are presented. This capability provides characteristics of the theoretically best, or limiting, design concept according to response criteria dictated by design requirements. Equations of motion of the system in first or second order form include incompletely specified elements whose characteristics are determined in the <span class="hlt">optimization</span> of one or more performance indices subject to the response criteria in the form of constraints. The system is subject to deterministic transient inputs, and the computer capability is designed to operate with a large linear programming on-the-shelf software package which performs the desired <span class="hlt">optimization</span>. The report contains user-oriented program documentation in engineering, problem-oriented form. Applications cover a wide variety of <span class="hlt">dynamics</span> problems including those associated with such diverse configurations as a missile-silo system, impacting freight cars, and an aircraft ride control system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160009381','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160009381"><span>Conceptual Design <span class="hlt">Optimization</span> of an Augmented Stability Aircraft Incorporating <span class="hlt">Dynamic</span> Response Performance Constraints</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Welstead, Jason</p> <p>2014-01-01</p> <p>This research focused on incorporating stability and control into a multidisciplinary de- sign <span class="hlt">optimization</span> on a Boeing 737-class advanced concept called the D8.2b. A new method of evaluating the aircraft handling performance using quantitative evaluation of the sys- tem to disturbances, including perturbations, continuous turbulence, and discrete gusts, is presented. A multidisciplinary design <span class="hlt">optimization</span> was performed using the D8.2b transport air- craft concept. The con guration was <span class="hlt">optimized</span> for minimum fuel burn using a design range of 3,000 nautical miles. <span class="hlt">Optimization</span> cases were run using xed tail volume coecients, static trim constraints, and static trim and <span class="hlt">dynamic</span> response constraints. A Cessna 182T model was used to test the various <span class="hlt">dynamic</span> analysis components, ensuring the analysis was behaving as expected. Results of the <span class="hlt">optimizations</span> show that including stability and con- trol in the design process drastically alters the <span class="hlt">optimal</span> design, indicating that stability and control should be included in conceptual design to avoid system level penalties later in the design process.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/20853023','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/20853023"><span>Quantum <span class="hlt">optimal</span> control theory and <span class="hlt">dynamic</span> coupling in the spin-boson model</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Jirari, H.; Poetz, W.</p> <p>2006-08-15</p> <p>A Markovian master equation describing the evolution of open quantum systems in the presence of a time-dependent external field is derived within the Bloch-Redfield formalism. It leads to a system-bath interaction which depends on the control field. <span class="hlt">Optimal</span> control theory is used to select control fields which allow accelerated or decelerated system relaxation, or suppression of relaxation (dissipation) altogether, depending on the <span class="hlt">dynamics</span> we impose on the quantum system. The control-dissipation correlation and the nonperturbative treatment of the control field are essential for reaching this goal. The <span class="hlt">optimal</span> control problem is formulated within Pontryagin's minimum principle and the resulting <span class="hlt">optimal</span> differential system is solved numerically. As an application, we study the <span class="hlt">dynamics</span> of a spin-boson model in the strong coupling regime under the influence of an external control field. We show how trapping the system in unstable quantum states and transfer of population can be achieved by <span class="hlt">optimized</span> control of the dissipative quantum system. We also used <span class="hlt">optimal</span> control theory to find the driving field that generates the quantum Z gate. In several cases studied, we find that the selected <span class="hlt">optimal</span> field which reduces the purity loss significantly is a multicomponent low-frequency field including higher harmonics, all of which lie below the phonon cutoff frequency. Finally, in the undriven case we present an analytic result for the Lamb shift at zero temperature.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040087025','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040087025"><span>Multidisciplinary Design <span class="hlt">Optimization</span> Techniques: Implications and Opportunities for Fluid <span class="hlt">Dynamics</span> Research</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zang, Thomas A.; Green, Lawrence L.</p> <p>1999-01-01</p> <p>A challenge for the fluid <span class="hlt">dynamics</span> community is to adapt to and exploit the trend towards greater multidisciplinary focus in research and technology. The past decade has witnessed substantial growth in the research field of Multidisciplinary Design <span class="hlt">Optimization</span> (MDO). MDO is a methodology for the design of complex engineering systems and subsystems that coherently exploits the synergism of mutually interacting phenomena. As evidenced by the papers, which appear in the biannual AIAA/USAF/NASA/ISSMO Symposia on Multidisciplinary Analysis and <span class="hlt">Optimization</span>, the MDO technical community focuses on vehicle and system design issues. This paper provides an overview of the MDO technology field from a fluid <span class="hlt">dynamics</span> perspective, giving emphasis to suggestions of specific applications of recent MDO technologies that can enhance fluid <span class="hlt">dynamics</span> research itself across the spectrum, from basic flow physics to full configuration aerodynamics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26379275','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26379275"><span>Efficient <span class="hlt">Optimization</span> of Stimuli for Model-Based Design of Experiments to Resolve <span class="hlt">Dynamical</span> Uncertainty.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Mdluli, Thembi; Buzzard, Gregery T; Rundell, Ann E</p> <p>2015-09-01</p> <p>This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to <span class="hlt">optimally</span> constrain the uncertain <span class="hlt">dynamics</span> of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system <span class="hlt">dynamics</span>, (2) representative parameters that uniformly represent the data-consistent <span class="hlt">dynamical</span> space, and (3) probability weights of the represented experimentally distinguishable <span class="hlt">dynamics</span>. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the <span class="hlt">optimal</span> input sequence from a greedy search, and defines the associated <span class="hlt">optimal</span> measurements using a scenario tree. We explore the <span class="hlt">optimality</span> of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm's scalability to higher dimensions. In both cases, the <span class="hlt">dynamical</span> uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving <span class="hlt">dynamical</span> uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ChPhB..24c0502W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ChPhB..24c0502W"><span>Policy iteration <span class="hlt">optimal</span> tracking control for chaotic systems by using an adaptive <span class="hlt">dynamic</span> programming approach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wei, Qing-Lai; Liu, De-Rong; Xu, Yan-Cai</p> <p>2015-03-01</p> <p>A policy iteration algorithm of adaptive <span class="hlt">dynamic</span> programming (ADP) is developed to solve the <span class="hlt">optimal</span> tracking control for a class of discrete-time chaotic systems. By system transformations, the <span class="hlt">optimal</span> tracking problem is transformed into an <span class="hlt">optimal</span> regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then, the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks, the developed <span class="hlt">optimal</span> tracking control scheme for chaotic systems is verified by a simulation. Project supported by the National Natural Science Foundation of China (Grant Nos. 61034002, 61233001, 61273140, 61304086, and 61374105) and the Beijing Natural Science Foundation, China (Grant No. 4132078).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007ApPhL..90a3902M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007ApPhL..90a3902M"><span><span class="hlt">Dynamic</span> <span class="hlt">optimization</span> of on-chip polymerase chain reaction by monitoring intracycle fluorescence using fast synchronous detection</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mondal, Sudip; Paul, Debjani; Venkataraman, V.</p> <p>2007-01-01</p> <p>The authors report on-chip <span class="hlt">dynamic</span> <span class="hlt">optimization</span> of polymerase chain reaction (PCR) based on a feedback technique utilizing synchronous detection of intracycle fluorescence every 500ms. From a direct measurement of polymerase activity, the authors determine the optimum extension temperature. The authors <span class="hlt">dynamically</span> <span class="hlt">optimize</span> PCR in an inductively heated microchip by sensing the saturation of extension in each cycle and applying the feedback. They demonstrate that, even with fast ramp rates, <span class="hlt">dynamic</span> <span class="hlt">optimization</span> leads to faster reactions compared to fixed-duration extension protocols for long DNA (>500bp). This <span class="hlt">optimization</span> scheme uses a fairly universal dye Sybr Green I and can be applied to most PCRs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014APS..GECMW1077K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014APS..GECMW1077K"><span><span class="hlt">Optimizing</span> Natural Gas Networks through <span class="hlt">Dynamic</span> Manifold Theory and a Decentralized Algorithm: Belgium Case Study</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Koch, Caleb; Winfrey, Leigh</p> <p>2014-10-01</p> <p>Natural Gas is a major energy source in Europe, yet political instabilities have the potential to disrupt access and supply. Energy resilience is an increasingly essential construct and begins with transmission network design. This study proposes a new way of thinking about modelling natural gas flow. Rather than relying on classical economic models, this problem is cast into a time-dependent Hamiltonian <span class="hlt">dynamics</span> discussion. Traditional Natural Gas constraints, including inelastic demand and maximum/minimum pipe flows, are portrayed as energy functions and built into the <span class="hlt">dynamics</span> of each pipe flow. Doing so allows the constraints to be built into the <span class="hlt">dynamics</span> of each pipeline. As time progresses in the model, natural gas flow rates find the minimum energy, thus the <span class="hlt">optimal</span> gas flow rates. The most important result of this study is using <span class="hlt">dynamical</span> principles to ensure the output of natural gas at demand nodes remains constant, which is important for country to country natural gas transmission. Another important step in this study is building the <span class="hlt">dynamics</span> of each flow in a decentralized algorithm format. Decentralized regulation has solved congestion problems for internet data flow, traffic flow, epidemiology, and as demonstrated in this study can solve the problem of Natural Gas congestion. A mathematical description is provided for how decentralized regulation leads to globally <span class="hlt">optimized</span> network flow. Furthermore, the <span class="hlt">dynamical</span> principles and decentralized algorithm are applied to a case study of the Fluxys Belgium Natural Gas Network.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJC....89...99L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJC....89...99L"><span>Online adaptive <span class="hlt">optimal</span> control for continuous-time nonlinear systems with completely unknown <span class="hlt">dynamics</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu</p> <p>2016-01-01</p> <p>An online adaptive <span class="hlt">optimal</span> control is proposed for continuous-time nonlinear systems with completely unknown <span class="hlt">dynamics</span>, which is achieved by developing a novel identifier-critic-based approximate <span class="hlt">dynamic</span> programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system <span class="hlt">dynamics</span>, and a critic NN is employed to approximate the <span class="hlt">optimal</span> value function. Then, the <span class="hlt">optimal</span> control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the <span class="hlt">optimal</span> solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016APS..MAR.T1321H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016APS..MAR.T1321H"><span><span class="hlt">Optimal</span> bipedal interactions with <span class="hlt">dynamic</span> terrain: synthesis and analysis via nonlinear programming</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hubicki, Christian; Goldman, Daniel; Ames, Aaron</p> <p></p> <p>In terrestrial locomotion, gait <span class="hlt">dynamics</span> and motor control behaviors are tuned to interact efficiently and stably with the <span class="hlt">dynamics</span> of the terrain (i.e. terradynamics). This controlled interaction must be particularly thoughtful in bipeds, as their reduced contact points render them highly susceptible to falls. While bipedalism under rigid terrain assumptions is well-studied, insights for two-legged locomotion on soft terrain, such as sand and dirt, are comparatively sparse. We seek an understanding of how biological bipeds stably and economically negotiate granular media, with an eye toward imbuing those abilities in bipedal robots. We present a trajectory <span class="hlt">optimization</span> method for controlled systems subject to granular intrusion. By formulating a large-scale nonlinear program (NLP) with reduced-order resistive force theory (RFT) models and jamming cone <span class="hlt">dynamics</span>, the <span class="hlt">optimized</span> motions are informed and shaped by the <span class="hlt">dynamics</span> of the terrain. Using a variant of direct collocation methods, we can express all <span class="hlt">optimization</span> objectives and constraints in closed-form, resulting in rapid solving by standard NLP solvers, such as IPOPT. We employ this tool to analyze emergent features of bipedal locomotion in granular media, with an eye toward robotic implementation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22251304','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22251304"><span>Extended Lagrangian Born-Oppenheimer molecular <span class="hlt">dynamics</span> in the limit of vanishing self-consistent field <span class="hlt">optimization</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Souvatzis, Petros; Niklasson, Anders M. N.</p> <p>2013-12-07</p> <p>We present an efficient general approach to first principles molecular <span class="hlt">dynamics</span> simulations based on extended Lagrangian Born-Oppenheimer molecular <span class="hlt">dynamics</span> [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] in the limit of vanishing self-consistent field <span class="hlt">optimization</span>. The reduction of the <span class="hlt">optimization</span> requirement reduces the computational cost to a minimum, but without causing any significant loss of accuracy or long-term energy drift. The <span class="hlt">optimization</span>-free first principles molecular <span class="hlt">dynamics</span> requires only one single diagonalization per time step, but is still able to provide trajectories at the same level of accuracy as “exact,” fully converged, Born-Oppenheimer molecular <span class="hlt">dynamics</span> simulations. The <span class="hlt">optimization</span>-free limit of extended Lagrangian Born-Oppenheimer molecular <span class="hlt">dynamics</span> therefore represents an ideal starting point for robust and efficient first principles quantum mechanical molecular <span class="hlt">dynamics</span> simulations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AdSpR..52.1530Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AdSpR..52.1530Z"><span>Long term <span class="hlt">dynamics</span> and <span class="hlt">optimal</span> control of nano-satellite deorbit using a short electrodynamic tether</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhong, R.; Zhu, Z. H.</p> <p>2013-10-01</p> <p>This paper studies the long term <span class="hlt">dynamics</span> and <span class="hlt">optimal</span> control of a nano-satellite deorbit by a short electrodynamic tether. The long term deorbit process is discretized into intervals and within each interval a two-phase <span class="hlt">optimal</span> control law is proposed to achieve libration stability and fast deorbit simultaneously. The first-phase formulates an open-loop fast-deorbit control trajectory by a simplified model that assumes the slow-varying orbital elements of electrodynamic tethered system as constant and ignores perturbation forces other than the electrodynamic force. The second phase tracks the <span class="hlt">optimal</span> trajectory derived in the first phase by a finite receding horizon control method while considering a full <span class="hlt">dynamic</span> model of electrodynamic tether system. Both <span class="hlt">optimal</span> control problems are solved by direct collocation method base on the Hermite-Simpson discretization schemes with coincident nodes. The resulting piecewise nonlinear programing problems in the sequential intervals reduces the problem size and improve the computational efficiency, which enable an on-orbit control application. Numerical results for deorbit control of a short electrodynamic tethered nano-satellite system in both equatorial and highly inclined orbits demonstrate the efficiency of the proposed control method. An <span class="hlt">optimal</span> balance between the libration stability and a fast deorbit of satellite with minimum control efforts is achieved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130014121','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130014121"><span>Risk-Constrained <span class="hlt">Dynamic</span> Programming for <span class="hlt">Optimal</span> Mars Entry, Descent, and Landing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ono, Masahiro; Kuwata, Yoshiaki</p> <p>2013-01-01</p> <p>A chance-constrained <span class="hlt">dynamic</span> programming algorithm was developed that is capable of making <span class="hlt">optimal</span> sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard <span class="hlt">dynamic</span> programming (DP) provides a general framework for <span class="hlt">optimal</span> sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the <span class="hlt">optimization</span> problem. As a result, the chance-constraint <span class="hlt">optimization</span> problem can be turned into an unconstrained <span class="hlt">optimization</span> over a Lagrangian, which can be solved efficiently using a standard DP approach.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016Fract..2450044K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016Fract..2450044K"><span>An <span class="hlt">Optimization</span> of Maximal Invariance in a Class of Multiple Valued Iterative <span class="hlt">Dynamics</span> Models of Nonlinear Disturbed Control Systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kahng, Byungik</p> <p>2016-11-01</p> <p>We discuss an <span class="hlt">optimization</span> problem on the maximal invariance of a class of multiple-valued iterative <span class="hlt">dynamics</span> (MVID) models of discrete-time nonlinear control <span class="hlt">dynamical</span> systems with singular disturbance. We study the inner and outer bounds of the maximal invariance, between which all noninterfering MVID models of nonlinear discrete-time control <span class="hlt">dynamical</span> systems with singular disturbance reside. We also study the invariant fractal structure and an <span class="hlt">optimization</span> of Lyapunov multipliers associated to it.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/934620','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/934620"><span>Reduced-Order Model for <span class="hlt">Dynamic</span> <span class="hlt">Optimization</span> of Pressure Swing Adsorption</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Agarwal, Anshul; Biegler, L.T.; Zitney, S.E.</p> <p>2007-11-01</p> <p> <span class="hlt">optimization</span>, if <span class="hlt">dynamic</span> PSA models are incorporated with other steady state models in the flowsheet then it will require much faster approaches for integrated <span class="hlt">optimization</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1345931','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1345931"><span>Co-<span class="hlt">Optimization</span> of CO<sub>2</sub>-EOR and Storage Processes in Mature Oil Reservoirs</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Ampomah, William; Balch, Robert S.; Grigg, Reid B.; McPherson, Brian; Will, Robert A.; Lee, Si-Yong; Dai, Zhenxue; Pan, Feng</p> <p>2016-08-02</p> <p>This article presents an <span class="hlt">optimization</span> methodology for CO<sub>2</sub> enhanced oil recovery in partially depleted reservoirs. A field-scale compositional reservoir flow model was developed for assessing the performance history of an active CO<sub>2</sub> flood and for <span class="hlt">optimizing</span> both oil production and CO<sub>2</sub> storage in the Farnsworth Unit (FWU), Ochiltree County, Texas. A geological framework model constructed from geophysical, geological, and engineering data acquired from the FWU was the basis for all reservoir simulations and the <span class="hlt">optimization</span> method. An equation of state was calibrated with laboratory fluid analyses and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). Initial history calibrations of primary, secondary and tertiary recovery were conducted as the basis for the study. After a good match was achieved, an <span class="hlt">optimization</span> approach consisting of a proxy or surrogate model was constructed with a polynomial response surface method (PRSM). The PRSM utilized an objective function that maximized both oil recovery and CO<sub>2</sub> storage. Experimental design was used to link uncertain parameters to the objective function. Control variables considered in this study included: water alternating gas cycle and ratio, production rates and bottom-hole pressure of injectors and producers. Other key parameters considered in the modeling process were CO<sub>2</sub> purchase, gas recycle and addition of infill wells and/or patterns. The PRSM proxy model was ‘trained’ or calibrated with a series of training simulations. This involved an iterative process until the surrogate model reached a specific validation criterion. A sensitivity analysis was first conducted to ascertain which of these control variables to retain in the surrogate model. A genetic algorithm with a <span class="hlt">mixed-integer</span> capability <span class="hlt">optimization</span> approach was employed to determine the optimum developmental strategy to maximize both oil recovery and CO<sub>2</sub</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006PhDT.......101K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006PhDT.......101K"><span>Analysis and formulation of a class of complex <span class="hlt">dynamic</span> <span class="hlt">optimization</span> problems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kameswaran, Shivakumar</p> <p></p> <p>The Direct Transcription approach, also known as the direct simultaneous approach, is a widely used solution strategy for the solution of <span class="hlt">dynamic</span> <span class="hlt">optimization</span> problems involving differential-algebraic equations (DAEs). Direct transcription refers to the procedure of approximating the infinite dimensional problem by a finite dimensional one, which is then solved using a nonlinear programming (NLP) solver tailored to large-scale problems. Systems governed by partial differential equations (PDEs) can also be handled by spatially discretizing the PDEs to convert them to a system of DAEs. The objective of this thesis is firstly to ensure that direct transcription using Radau collocation is provably correct, and secondly to widen the applicability of the direct simultaneous approach to a larger class of <span class="hlt">dynamic</span> <span class="hlt">optimization</span> and <span class="hlt">optimal</span> control problems (OCPs). This thesis aims at addressing these issues using rigorous theoretical tools and/or characteristic examples, and at the same time use the results for solving large-scale industrial applications to realize the benefits. The first part of this work deals with the analysis of convergence rates for direct transcription of unconstrained and final-time equality constrained <span class="hlt">optimal</span> control problems. The problems are discretized using collocation at Radau points. Convergence is analyzed from an NLP/matrix-algebra perspective, which enables the prediction of the conditioning of the direct transcription NLP as the mesh size becomes finer. Several convergence results are presented along with tests on numerous example problems. These convergence results lead to an adjoint estimation procedure given the Lagrange multipliers for the large-scale NLP. The work also reveals the role of process control concepts such as controllability on the convergence analysis, and provides a very important link between control and <span class="hlt">optimization</span> inside the framework of <span class="hlt">dynamic</span> <span class="hlt">optimization</span>. As an effort to extend the applicability of the direct</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011LNCS.6589..260K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011LNCS.6589..260K"><span>An Approach for <span class="hlt">Dynamic</span> <span class="hlt">Optimization</span> of Prevention Program Implementation in Stochastic Environments</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kang, Yuncheol; Prabhu, Vittal</p> <p></p> <p>The science of preventing youth problems has significantly advanced in developing evidence-based prevention program (EBP) by using randomized clinical trials. Effective EBP can reduce delinquency, aggression, violence, bullying and substance abuse among youth. Unfortunately the outcomes of EBP implemented in natural settings usually tend to be lower than in clinical trials, which has motivated the need to study EBP implementations. In this paper we propose to model EBP implementations in natural settings as stochastic <span class="hlt">dynamic</span> processes. Specifically, we propose Markov Decision Process (MDP) for modeling and <span class="hlt">dynamic</span> <span class="hlt">optimization</span> of such EBP implementations. We illustrate these concepts using simple numerical examples and discuss potential challenges in using such approaches in practice.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhRvA..95a2335A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhRvA..95a2335A"><span>Using recurrent neural networks to <span class="hlt">optimize</span> <span class="hlt">dynamical</span> decoupling for quantum memory</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>August, Moritz; Ni, Xiaotong</p> <p>2017-01-01</p> <p>We utilize machine learning models that are based on recurrent neural networks to <span class="hlt">optimize</span> <span class="hlt">dynamical</span> decoupling (DD) sequences. <span class="hlt">Dynamical</span> decoupling is a relatively simple technique for suppressing the errors in quantum memory for certain noise models. In numerical simulations, we show that with minimum use of prior knowledge and starting from random sequences, the models are able to improve over time and eventually output DD sequences with performance better than that of the well known DD families. Furthermore, our algorithm is easy to implement in experiments to find solutions tailored to the specific hardware, as it treats the figure of merit as a black box.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EnOp...47..328H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EnOp...47..328H"><span>Applying the approximation method PAINT and the interactive method NIMBUS to the multiobjective <span class="hlt">optimization</span> of operating a wastewater treatment plant</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hartikainen, Markus E.; Ojalehto, Vesa; Sahlstedt, Kristian</p> <p>2015-03-01</p> <p>Using an interactive multiobjective <span class="hlt">optimization</span> method called NIMBUS and an approximation method called PAINT, preferable solutions to a five-objective problem of operating a wastewater treatment plant are found. The decision maker giving preference information is an expert in wastewater treatment plant design at the engineering company Pöyry Finland Ltd. The wastewater treatment problem is computationally expensive and requires running a simulator to evaluate the values of the objective functions. This often leads to problems with interactive methods as the decision maker may get frustrated while waiting for new solutions to be computed. Thus, a newly developed PAINT method is used to speed up the iterations of the NIMBUS method. The PAINT method interpolates between a given set of Pareto <span class="hlt">optimal</span> outcomes and constructs a computationally inexpensive <span class="hlt">mixed</span> <span class="hlt">integer</span> linear surrogate problem for the original wastewater treatment problem. With the <span class="hlt">mixed</span> <span class="hlt">integer</span> surrogate problem, the time required from the decision maker is comparatively short. In addition, a new IND-NIMBUS® PAINT module is developed to allow the smooth interoperability of the NIMBUS method and the PAINT method.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008JAMDS...2..417H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008JAMDS...2..417H"><span>Topology Mining for <span class="hlt">Optimization</span> of Framed Structures</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hagishita, Takao; Ohsaki, Makoto</p> <p></p> <p>A new heuristic method called Topology Mining (TM) is proposed for topology <span class="hlt">optimization</span> of framed structures, where the problem is formulated as 0-1 <span class="hlt">mixed-integer</span> <span class="hlt">optimization</span> problem. TM uses the apriori algorithm, developed in the field of data mining, to efficiently extract the bar sets that frequently appears among superior solutions, and proceeds so as to preserve the sets. Hence, the process of <span class="hlt">optimization</span> can be investigated by tracing the frequent bar sets, accordingly, the parameters for <span class="hlt">optimization</span> can easily be adjusted. It is pointed out that the ground structure method based on nonlinear programming is not effective for finding <span class="hlt">optimal</span> placement of braces for a given frame under local buckling constraints. We propose an integrated approach to obtain an accurate solution of this problem, where <span class="hlt">optimal</span> placement of braces is searched by TM, and the sizing <span class="hlt">optimization</span> is performed by nonlinear programming. Three numerical examples are solved to demonstrate the performance of TM in comparison with another heuristic method called tabu search.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20967269','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20967269"><span>Prediction of <span class="hlt">optimal</span> folding routes of proteins that satisfy the principle of lowest entropy loss: <span class="hlt">dynamic</span> contact maps and <span class="hlt">optimal</span> control.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Arkun, Yaman; Erman, Burak</p> <p>2010-10-12</p> <p>An <span class="hlt">optimization</span> model is introduced in which proteins try to evade high energy regions of the folding landscape, and prefer low entropy loss routes during folding. We make use of the framework of <span class="hlt">optimal</span> control whose convenient solution provides practical and useful insight into the sequence of events during folding. We assume that the native state is available. As the protein folds, it makes different set of contacts at different folding steps. The <span class="hlt">dynamic</span> contact map is constructed from these contacts. The topology of the <span class="hlt">dynamic</span> contact map changes during the course of folding and this information is utilized in the <span class="hlt">dynamic</span> <span class="hlt">optimization</span> model. The solution is obtained using the <span class="hlt">optimal</span> control theory. We show that the <span class="hlt">optimal</span> solution can be cast into the form of a Gaussian Network that governs the <span class="hlt">optimal</span> folding <span class="hlt">dynamics</span>. Simulation results on three examples (CI2, Sso7d and Villin) show that folding starts by the formation of local clusters. Non-local clusters generally require the formation of several local clusters. Non-local clusters form cooperatively and not sequentially. We also observe that the <span class="hlt">optimal</span> controller prefers "zipping" or small loop closure steps during folding. The folding routes predicted by the proposed method bear strong resemblance to the results in the literature.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19900020067','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19900020067"><span>An enhanced integrated aerodynamic load/<span class="hlt">dynamic</span> <span class="hlt">optimization</span> procedure for helicopter rotor blades</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chattopadhyay, Aditi; Chiu, Y. Danny</p> <p>1990-01-01</p> <p>An enhanced integrated aerodynamic load/<span class="hlt">dynamic</span> <span class="hlt">optimization</span> procedure is developed to minimize vibratory root shears and moments. The <span class="hlt">optimization</span> is formulated with 4/rev vertical and 3/rev inplane shears at the blade root as objective functions and constraints, and 4/rev lagging moment. Constraints are also imposed on blade natural frequencies, weight, autorotational inertia, centrifugal stress, and rotor thrust. The 'Global Criteria Approach' is used for formulating the multi-objective <span class="hlt">optimization</span>. Design variables include spanwise distributions of bending stiffnesses, torsional stiffness, nonstructural mass, chord, radius of gyration, and blade taper ratio. The program CAMRAD is coupled with an <span class="hlt">optimizer</span>, which consists of the program CONMIN and an approximate analysis, to obtain optimum designs. The <span class="hlt">optimization</span> procedure is applied to an advanced rotor as a reference design. Optimum blade designs, obtained with and without a constraint on the rotor thrust, are presented and are compared to the reference blade. Substantial reductions are obtained in the vibratory root forces and moments. As a byproduct, improvements are also found in some performance parameters, such as total power required, which were not considered during <span class="hlt">optimization</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015IJSyS..46.2421P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015IJSyS..46.2421P"><span>Inverse <span class="hlt">optimal</span> sliding mode control of spacecraft with coupled translation and attitude <span class="hlt">dynamics</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pukdeboon, Chutiphon</p> <p>2015-10-01</p> <p>This paper proposes two robust inverse <span class="hlt">optimal</span> control schemes for spacecraft with coupled translation and attitude <span class="hlt">dynamics</span> in the presence of external disturbances. For the first controller, an inverse <span class="hlt">optimal</span> control law is designed based on Sontag-type formula and the control Lyapunov function. Then a robust inverse <span class="hlt">optimal</span> position and attitude controller is designed by using a new second-order integral sliding mode control method to combine a sliding mode control with the derived inverse <span class="hlt">optimal</span> control. The global asymptotic stability of the proposed control law is proved by using the second method of Lyapunov. For the other control law, a nonlinear H∞ inverse <span class="hlt">optimal</span> controller for spacecraft position and attitude tracking motion is developed to achieve the design conditions of controller gains that the control law becomes suboptimal H∞ state feedback control. The ultimate boundedness of system state is proved by using the Lyapunov stability theory. Both developed robust inverse <span class="hlt">optimal</span> controllers can minimise a performance index and ensure the stability of the closed-loop system and external disturbance attenuation. An example of position and attitude tracking manoeuvres is presented and simulation results are included to show the performance of the proposed controllers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040087841&hterms=Human+anatomy&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DHuman%2Banatomy','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040087841&hterms=Human+anatomy&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DHuman%2Banatomy"><span>Human motion planning based on recursive <span class="hlt">dynamics</span> and <span class="hlt">optimal</span> control techniques</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lo, Janzen; Huang, Gang; Metaxas, Dimitris</p> <p>2002-01-01</p> <p>This paper presents an efficient <span class="hlt">optimal</span> control and recursive <span class="hlt">dynamics</span>-based computer animation system for simulating and controlling the motion of articulated figures. A quasi-Newton nonlinear programming technique (super-linear convergence) is implemented to solve minimum torque-based human motion-planning problems. The explicit analytical gradients needed in the <span class="hlt">dynamics</span> are derived using a matrix exponential formulation and Lie algebra. Cubic spline functions are used to make the search space for an <span class="hlt">optimal</span> solution finite. Based on our formulations, our method is well conditioned and robust, in addition to being computationally efficient. To better illustrate the efficiency of our method, we present results of natural looking and physically correct human motions for a variety of human motion tasks involving open and closed loop kinematic chains.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26043376','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26043376"><span>Process simulation and <span class="hlt">dynamic</span> control for marine oily wastewater treatment using UV irradiation.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jing, Liang; Chen, Bing; Zhang, Baiyu; Li, Pu</p> <p>2015-09-15</p> <p>UV irradiation and advanced oxidation processes have been recently regarded as promising solutions in removing polycyclic aromatic hydrocarbons (PAHs) from marine oily wastewater. However, such treatment methods are generally not sufficiently understood in terms of reaction mechanisms, process simulation and process control. These deficiencies can drastically hinder their application in shipping and offshore petroleum industries which produce bilge/ballast water and produced water as the main streams of marine oily wastewater. In this study, the factorial design of experiment was carried out to investigate the degradation mechanism of a typical PAH, namely naphthalene, under UV irradiation in seawater. Based on the experimental results, a three-layer feed-forward artificial neural network simulation model was developed to simulate the treatment process and to forecast the removal performance. A simulation-based <span class="hlt">dynamic</span> <span class="hlt">mixed</span> <span class="hlt">integer</span> nonlinear programming (SDMINP) approach was then proposed to intelligently control the treatment process by integrating the developed simulation model, genetic algorithm and multi-stage programming. The applicability and effectiveness of the developed approach were further tested though a case study. The experimental results showed that the influences of fluence rate and temperature on the removal of naphthalene were greater than those of salinity and initial concentration. The developed simulation model could well predict the UV-induced removal process under varying conditions. The case study suggested that the SDMINP approach, with the aid of the multi-stage control strategy, was able to significantly reduce treatment cost when comparing to the traditional single-stage process <span class="hlt">optimization</span>. The developed approach and its concept/framework have high potential of applicability in other environmental fields where a treatment process is involved and experimentation and modeling are used for process simulation and control.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1034620','DOE-PATENT-XML'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1034620"><span>Performance monitoring for new phase <span class="hlt">dynamic</span> <span class="hlt">optimization</span> of instruction dispatch cluster configuration</span></a></p> <p><a target="_blank" href="http://www.osti.gov/doepatents">DOEpatents</a></p> <p>Balasubramonian, Rajeev [Sandy, UT; Dwarkadas, Sandhya [Rochester, NY; Albonesi, David [Ithaca, NY</p> <p>2012-01-24</p> <p>In a processor having multiple clusters which operate in parallel, the number of clusters in use can be varied <span class="hlt">dynamically</span>. At the start of each program phase, the configuration option for an interval is run to determine the <span class="hlt">optimal</span> configuration, which is used until the next phase change is detected. The optimum instruction interval is determined by starting with a minimum interval and doubling it until a low stability factor is reached.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1998PhDT.......106T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1998PhDT.......106T"><span>Experimental/analytical approaches to modeling, calibrating and <span class="hlt">optimizing</span> shaking table <span class="hlt">dynamics</span> for structural <span class="hlt">dynamic</span> applications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Trombetti, Tomaso</p> <p></p> <p>This thesis presents an Experimental/Analytical approach to modeling and calibrating shaking tables for structural <span class="hlt">dynamic</span> applications. This approach was successfully applied to the shaking table recently built in the structural laboratory of the Civil Engineering Department at Rice University. This shaking table is capable of reproducing model earthquake ground motions with a peak acceleration of 6 g's, a peak velocity of 40 inches per second, and a peak displacement of 3 inches, for a maximum payload of 1500 pounds. It has a frequency bandwidth of approximately 70 Hz and is designed to test structural specimens up to 1/5 scale. The rail/table system is mounted on a reaction mass of about 70,000 pounds consisting of three 12 ft x 12 ft x 1 ft reinforced concrete slabs, post-tensioned together and connected to the strong laboratory floor. The slip table is driven by a hydraulic actuator governed by a 407 MTS controller which employs a proportional-integral-derivative-feedforward-differential pressure algorithm to control the actuator displacement. Feedback signals are provided by two LVDT's (monitoring the slip table relative displacement and the servovalve main stage spool position) and by one differential pressure transducer (monitoring the actuator force). The <span class="hlt">dynamic</span> actuator-foundation-specimen system is modeled and analyzed by combining linear control theory and linear structural <span class="hlt">dynamics</span>. The analytical model developed accounts for the effects of actuator oil compressibility, oil leakage in the actuator, time delay in the response of the servovalve spool to a given electrical signal, foundation flexibility, and <span class="hlt">dynamic</span> characteristics of multi-degree-of-freedom specimens. In order to study the actual <span class="hlt">dynamic</span> behavior of the shaking table, the transfer function between target and actual table accelerations were identified using experimental results and spectral estimation techniques. The power spectral density of the system input and the cross power spectral</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4000643','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4000643"><span>Mathematical Modeling of Transmission <span class="hlt">Dynamics</span> and <span class="hlt">Optimal</span> Control of Vaccination and Treatment for Hepatitis B Virus</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Kamyad, Ali Vahidian; Heydari, Ali Akbar; Heydari, Aghileh</p> <p>2014-01-01</p> <p>Hepatitis B virus (HBV) infection is a worldwide public health problem. In this paper, we study the <span class="hlt">dynamics</span> of hepatitis B virus (HBV) infection which can be controlled by vaccination as well as treatment. Initially we consider constant controls for both vaccination and treatment. In the constant controls case, by determining the basic reproduction number, we study the existence and stability of the disease-free and endemic steady-state solutions of the model. Next, we take the controls as time and formulate the appropriate <span class="hlt">optimal</span> control problem and obtain the <span class="hlt">optimal</span> control strategy to minimize both the number of infectious humans and the associated costs. Finally at the end numerical simulation results show that <span class="hlt">optimal</span> combination of vaccination and treatment is the most effective way to control hepatitis B virus infection. PMID:24812572</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25751878','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25751878"><span>Error bounds of adaptive <span class="hlt">dynamic</span> programming algorithms for solving undiscounted <span class="hlt">optimal</span> control problems.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Liu, Derong; Li, Hongliang; Wang, Ding</p> <p>2015-06-01</p> <p>In this paper, we establish error bounds of adaptive <span class="hlt">dynamic</span> programming algorithms for solving undiscounted infinite-horizon <span class="hlt">optimal</span> control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted <span class="hlt">optimal</span> control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the <span class="hlt">optimal</span> value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1998PMB....43.1171D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1998PMB....43.1171D"><span>Leaf trajectory calculation for <span class="hlt">dynamic</span> multileaf collimation to realize <span class="hlt">optimized</span> fluence profiles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dirkx, M. L. P.; Heijmen, B. J. M.; van Santvoort, J. P. C.</p> <p>1998-05-01</p> <p>An algorithm for the calculation of the required leaf trajectories to generate <span class="hlt">optimized</span> intensity modulated beam profiles by means of <span class="hlt">dynamic</span> multileaf collimation is presented. This algorithm iteratively accounts for leaf transmission and collimator scatter and fully avoids tongue-and-groove underdosage effects. Tests on a large number of intensity modulated fields show that only a limited number of iterations, generally less than 10, are necessary to minimize the differences between <span class="hlt">optimized</span> and realized fluence profiles. To assess the accuracy of the algorithm in combination with the dose calculation algorithm of the Cadplan 3D treatment planning system, predicted absolute dose distributions for <span class="hlt">optimized</span> fluence profiles were compared with dose distributions measured on the MM50 Racetrack Microtron and resulting from the calculated leaf trajectories. Both theoretical and clinical cases yield an agreement within 2%, or within 2 mm in regions with a high dose gradient, showing that the accuracy is adequate for clinical application.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/9623648','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/9623648"><span>Leaf trajectory calculation for <span class="hlt">dynamic</span> multileaf collimation to realize <span class="hlt">optimized</span> fluence profiles.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Dirkx, M L; Heijmen, B J; van Santvoort, J P</p> <p>1998-05-01</p> <p>An algorithm for the calculation of the required leaf trajectories to generate <span class="hlt">optimized</span> intensity modulated beam profiles by means of <span class="hlt">dynamic</span> multileaf collimation is presented. This algorithm iteratively accounts for leaf transmission and collimator scatter and fully avoids tongue-and-groove underdosage effects. Tests on a large number of intensity modulated fields show that only a limited number of iterations, generally less than 10, are necessary to minimize the differences between <span class="hlt">optimized</span> and realized fluence profiles. To assess the accuracy of the algorithm in combination with the dose calculation algorithm of the Cadplan 3D treatment planning system, predicted absolute dose distributions for <span class="hlt">optimized</span> fluence profiles were compared with dose distributions measured on the MM50 Racetrack Microtron and resulting from the calculated leaf trajectories. Both theoretical and clinical cases yield an agreement within 2%, or within 2 mm in regions with a high dose gradient, showing that the accuracy is adequate for clinical application.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23818820','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23818820"><span>A new logistic <span class="hlt">dynamic</span> particle swarm <span class="hlt">optimization</span> algorithm based on random topology.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ni, Qingjian; Deng, Jianming</p> <p>2013-01-01</p> <p>Population topology of particle swarm <span class="hlt">optimization</span> (PSO) will directly affect the dissemination of <span class="hlt">optimal</span> information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic <span class="hlt">dynamic</span> particle <span class="hlt">optimization</span>, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930029136&hterms=Solving+optimal+control+problems&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DSolving%2Boptimal%2Bcontrol%2Bproblems','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930029136&hterms=Solving+optimal+control+problems&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DSolving%2Boptimal%2Bcontrol%2Bproblems"><span><span class="hlt">Optimal</span> control study for the Space Station Solar <span class="hlt">Dynamic</span> power module</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Papadopoulos, P. M.; Laub, A. J.; Kenney, C. S.; Pandey, P.; Ianculescu, G.; Ly, J.</p> <p>1991-01-01</p> <p>The authors present the design of an <span class="hlt">optimal</span> control system for the Space Station Freedom's Solar <span class="hlt">Dynamic</span> Fine Pointing and Tracking (SDFPT) module. A very large state model of six rigid body modes and 272 flexible modes is used in conjunction with classical LQG <span class="hlt">optimal</span> control to produce a full-order controller which satisfies the requirements. The results obtained are compared with those of a classically designed PID (proportional plus integral plus derivative) controller that was implemented for a six-rigid-body-mode forty-flexible-mode model. A major difficulty with designing LQG controllers for large models is solving the Riccati equation that arises from the <span class="hlt">optimal</span> formulation. A Riccati solver based on a Pade approximation to the matrix sign function is used. A symmetric version of this algorithm is derived for the special class of Hamiltonion matrices, thereby yielding, for large problems, a nearly twofold speed increase over a previous algorithm.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9501E..0YM','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9501E..0YM"><span><span class="hlt">Optimizing</span> meridional advection of the Advanced Research WRF (ARW) <span class="hlt">dynamics</span> for Intel Xeon Phi coprocessor</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.-L.</p> <p>2015-05-01</p> <p>The most widely used community weather forecast and research model in the world is the Weather Research and Forecast (WRF) model. Two distinct varieties of WRF exist. The one we are interested is the Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of <span class="hlt">dynamics</span> code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we <span class="hlt">optimize</span> a meridional (north-south direction) advection subroutine for Intel Xeon Phi coprocessor. Advection is of the most time consuming routines in the ARW <span class="hlt">dynamics</span> core. It advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed <span class="hlt">dynamics</span> code subroutine for MIC architecture. Furthermore, lessons learned from the code <span class="hlt">optimization</span> process will be discussed. The results show that the <span class="hlt">optimizations</span> improved performance of the original code on Xeon Phi 7120P by a factor of 1.2x.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EPJP..132...23S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EPJP..132...23S"><span><span class="hlt">Optimal</span> q-homotopy analysis method for time-space fractional gas <span class="hlt">dynamics</span> equation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Saad, K. M.; AL-Shareef, E. H.; Mohamed, Mohamed S.; Yang, Xiao-Jun</p> <p>2017-01-01</p> <p>It is well known that the homotopy analysis method is one of the most efficient methods for obtaining analytical or approximate semi-analytical solutions of both linear and non-linear partial differential equations. A more general form of HAM is introduced in this paper, which is called <span class="hlt">Optimal</span> q-Homotopy Analysis Method (Oq-HAM). It has better convergence properties as compared with the usual HAM, due to the presence of fraction factor associated with the solution. The convergence of q-HAM is studied in details elsewhere (M.A. El-Tawil, Int. J. Contemp. Math. Sci. 8, 481 (2013)). Oq-HAM is applied to the non-linear homogeneous and non-homogeneous time and space fractional gas <span class="hlt">dynamics</span> equations with initial condition. An <span class="hlt">optimal</span> convergence region is determined through the residual error. By minimizing the square residual error, the <span class="hlt">optimal</span> convergence control parameters can be obtained. The accuracy and efficiency of the proposed method are verified by comparison with the exact solution of the fractional gas <span class="hlt">dynamics</span> equation. Also, it is shown that the Oq-HAM for the fractional gas <span class="hlt">dynamics</span> equation is equivalent to the exact solution. We obtain graphical representations of the solutions using MATHEMATICA.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4784908','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4784908"><span><span class="hlt">Dynamical</span> Allocation of Cellular Resources as an <span class="hlt">Optimal</span> Control Problem: Novel Insights into Microbial Growth Strategies</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Giordano, Nils; Mairet, Francis; Gouzé, Jean-Luc</p> <p>2016-01-01</p> <p>Microbial physiology exhibits growth laws that relate the macromolecular composition of the cell to the growth rate. Recent work has shown that these empirical regularities can be derived from coarse-grained models of resource allocation. While these studies focus on steady-state growth, such conditions are rarely found in natural habitats, where microorganisms are continually challenged by environmental fluctuations. The aim of this paper is to extend the study of microbial growth strategies to <span class="hlt">dynamical</span> environments, using a self-replicator model. We formulate <span class="hlt">dynamical</span> growth maximization as an <span class="hlt">optimal</span> control problem that can be solved using Pontryagin’s Maximum Principle. We compare this theoretical gold standard with different possible implementations of growth control in bacterial cells. We find that simple control strategies enabling growth-rate maximization at steady state are suboptimal for transitions from one growth regime to another, for example when shifting bacterial cells to a medium supporting a higher growth rate. A near-<span class="hlt">optimal</span> control strategy in <span class="hlt">dynamical</span> conditions is shown to require information on several, rather than a single physiological variable. Interestingly, this strategy has structural analogies with the regulation of ribosomal protein synthesis by ppGpp in the enterobacterium Escherichia coli. It involves sensing a mismatch between precursor and ribosome concentrations, as well as the adjustment of ribosome synthesis in a switch-like manner. Our results show how the capability of regulatory systems to integrate information about several physiological variables is critical for <span class="hlt">optimizing</span> growth in a changing environment. PMID:26958858</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910065131&hterms=feature+discrete&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dfeature%2Bdiscrete','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910065131&hterms=feature+discrete&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dfeature%2Bdiscrete"><span><span class="hlt">Optimal</span> discrete-time <span class="hlt">dynamic</span> output-feedback design - A w-domain approach</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ha, Cheolkeun; Ly, Uy-Loi</p> <p>1991-01-01</p> <p>An alternative method for <span class="hlt">optimal</span> digital control design is described in this paper. The method is based on the usage of the w-transform and has many attractive design features. One of these is its immediate connection with frequency loop-shaping techniques that are now popular and effective for multivariable control synthesis in continuous-time domain. Furthermore, any design algorithms originally developed for continuous-time systems can now be immediately extended to the discrete-time domain. The main results presented in this paper are the exact problem formulation and solution of an <span class="hlt">optimal</span> discrete-time <span class="hlt">dynamic</span> output-feedback design in the w-domain involving a quadratic performance index to random disturbances. In addition, necessary conditions for <span class="hlt">optimality</span> are obtained for the numerical solution of the <span class="hlt">optimal</span> output-feedback compensator design. A numerical example is presented illustrating its application to the design of a low-order <span class="hlt">dynamic</span> compensator in a stability augmentation system of a commercial transport.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AIPC.1373..262K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AIPC.1373..262K"><span>Use of a Batch Reactive Distillation with <span class="hlt">Dynamic</span> <span class="hlt">Optimization</span> Strategy to Achieve Industrial Grade Ethyl Acetate</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Konakom, Kwantip; Saengchan, Aritsara; Kittisupakorn, Paisan; Mujtaba, Iqbal M.</p> <p>2011-08-01</p> <p>Industrial grade ethyl acetate is available with minimum purity of 85.0%. It is mostly produced by an ethanol esterification in a distillation process on both batch and continuous modes. However, researches on high purity production with short operating time are rarely achieved. Therefore, the objective in this work is to study an approach to produce ethyl acetate of 90.0% by 8 hours using a batch reactive distillation column. Based on open-loop simulations, the distillation with constant reflux ratio cannot achieve the product specification. Thus, the <span class="hlt">dynamic</span> <span class="hlt">optimization</span> strategy is proposed to handle this problem. For the process safety—preventing the dried column and fractured, a minimum reflux ratio must be determined in advance and then an <span class="hlt">optimal</span> reflux profile is calculated to achieve <span class="hlt">optimal</span> product yield. Simulation results show that the industrial grade ethyl acetate can be produced by the <span class="hlt">dynamic</span> <span class="hlt">optimization</span> programming with two or more time intervals. Besides, the increasing of time intervals can produce more distillate product.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002NJPh....4...33H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002NJPh....4...33H"><span>Volatile decision <span class="hlt">dynamics</span>: experiments, stochastic description, intermittency control and traffic <span class="hlt">optimization</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Helbing, Dirk; Schönhof, Martin; Kern, Daniel</p> <p>2002-06-01</p> <p>The coordinated and efficient distribution of limited resources by individual decisions is a fundamental, unsolved problem. When individuals compete for road capacities, time, space, money, goods, etc, they normally make decisions based on aggregate rather than complete information, such as TV news or stock market indices. In related experiments, we have observed a volatile decision <span class="hlt">dynamics</span> and far-from-<span class="hlt">optimal</span> payoff distributions. We have also identified methods of information presentation that can considerably improve the overall performance of the system. In order to determine <span class="hlt">optimal</span> strategies of decision guidance by means of user-specific recommendations, a stochastic behavioural description is developed. These strategies manage to increase the adaptibility to changing conditions and to reduce the deviation from the time-dependent user equilibrium, thereby enhancing the average and individual payoffs. Hence, our guidance strategies can increase the performance of all users by reducing overreaction and stabilizing the decision <span class="hlt">dynamics</span>. These results are highly significant for predicting decision behaviour, for reaching <span class="hlt">optimal</span> behavioural distributions by decision support systems and for information service providers. One of the promising fields of application is traffic <span class="hlt">optimization</span>.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011WRR....47.0G08G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011WRR....47.0G08G"><span><span class="hlt">Optimal</span> <span class="hlt">dynamic</span> water allocation: Irrigation extractions and environmental tradeoffs in the Murray River, Australia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Grafton, R. Quentin; Chu, Hoang Long; Stewardson, Michael; Kompas, Tom</p> <p>2011-12-01</p> <p>A key challenge in managing semiarid basins, such as in the Murray-Darling in Australia, is to balance the trade-offs between the net benefits of allocating water for irrigated agriculture, and other uses, versus the costs of reduced surface flows for the environment. Typically, water planners do not have the tools to <span class="hlt">optimally</span> and <span class="hlt">dynamically</span> allocate water among competing uses. We address this problem by developing a general stochastic, <span class="hlt">dynamic</span> programming model with four state variables (the drought status, the current weather, weather correlation, and current storage) and two controls (environmental release and irrigation allocation) to <span class="hlt">optimally</span> allocate water between extractions and in situ uses. The model is calibrated to Australia's Murray River that generates: (1) a robust qualitative result that "pulse" or artificial flood events are an <span class="hlt">optimal</span> way to deliver environmental flows over and above conveyance of base flows; (2) from 2001 to 2009 a water reallocation that would have given less to irrigated agriculture and more to environmental flows would have generated between half a billion and over 3 billion U.S. dollars in overall economic benefits; and (3) water markets increase <span class="hlt">optimal</span> environmental releases by reducing the losses associated with reduced water diversions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28092573','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28092573"><span>Environment Sensitivity-based Cooperative Co-evolutionary Algorithms for <span class="hlt">Dynamic</span> Multi-objective <span class="hlt">Optimization</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Xu, Biao; Zhang, Yong; Gong, Dunwei; Guo, Yinan; Rong, Miao</p> <p>2017-01-16</p> <p><span class="hlt">Dynamic</span> multi-objective <span class="hlt">optimization</span> problems (DMOPs) not only involve multiple conflicting objectives, but these objectives may also vary with time, raising a challenge for researchers to solve them. This paper presents a cooperative co-evolutionary strategy based on environment sensitivities for solving DMOPs. In this strategy, a new method that groups decision variables is first proposed, in which all the decision variables are partitioned into two subcomponents according to their interrelation with environment. Adopting two populations to cooperatively <span class="hlt">optimize</span> the two subcomponents, two prediction methods, i.e., differential prediction and Cauchy mutation, are then employed respectively to speed up their responses on the change of the environment. Furthermore, two improved <span class="hlt">dynamic</span> multi-objective <span class="hlt">optimization</span> algorithms, i.e., DNSGAII-CO and DMOPSO-CO, are proposed by incorporating the above strategy into NSGA-II and multi-objective particle swarm <span class="hlt">optimization</span>, respectively. The proposed algorithms are compared with three state-of-the-art algorithms by applying to seven benchmark DMOPs. Experimental results reveal that the proposed algorithms significantly outperform the compared algorithms in terms of convergence and distribution on most DMOPs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1014639','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1014639"><span>Integrating event detection system operation characteristics into sensor placement <span class="hlt">optimization</span>.</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Hart, William Eugene; McKenna, Sean Andrew; Phillips, Cynthia Ann; Murray, Regan Elizabeth; Hart, David Blaine</p> <p>2010-05-01</p> <p>We consider the problem of placing sensors in a municipal water network when we can choose both the location of sensors and the sensitivity and specificity of the contamination warning system. Sensor stations in a municipal water distribution network continuously send sensor output information to a centralized computing facility, and event detection systems at the control center determine when to signal an anomaly worthy of response. Although most sensor placement research has assumed perfect anomaly detection, signal analysis software has parameters that control the tradeoff between false alarms and false negatives. We describe a nonlinear sensor placement formulation, which we heuristically <span class="hlt">optimize</span> with a linear approximation that can be solved as a <span class="hlt">mixed-integer</span> linear program. We report the results of initial experiments on a real network and discuss tradeoffs between early detection of contamination incidents, and control of false alarms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24586257','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24586257"><span>Game theory and extremal <span class="hlt">optimization</span> for community detection in complex <span class="hlt">dynamic</span> networks.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca</p> <p>2014-01-01</p> <p>The detection of evolving communities in <span class="hlt">dynamic</span> complex networks is a challenging problem that recently received attention from the research community. <span class="hlt">Dynamics</span> clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal <span class="hlt">optimization</span> to address <span class="hlt">dynamic</span> communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EnOp...44.1073F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EnOp...44.1073F"><span>Partial constraint satisfaction approaches for <span class="hlt">optimal</span> operation of a hydropower system</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ferreira, Andre R.; Teegavarapu, Ramesh S. V.</p> <p>2012-09-01</p> <p><span class="hlt">Optimal</span> operation models for a hydropower system using partial constraint satisfaction (PCS) approaches are proposed and developed in this study. The models use <span class="hlt">mixed</span> <span class="hlt">integer</span> nonlinear programming (MINLP) formulations with binary variables. The models also integrate a turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream water quality impairment. New PCS-based models for hydropower <span class="hlt">optimization</span> formulations are developed using binary and continuous evaluator functions to maximize the constraint satisfaction. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to solve the <span class="hlt">optimization</span> formulations. Decision maker's preferences towards power production targets and water quality improvements are incorporated using partial satisfaction constraints to obtain compromise operating rules for a multi-objective reservoir operation problem dominated by conflicting goals of energy production, water quality and consumptive water uses.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011NTA.....2..497I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011NTA.....2..497I"><span>A hybrid approach using chaotic <span class="hlt">dynamics</span> and global search algorithms for combinatorial <span class="hlt">optimization</span> problems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Igeta, Hideki; Hasegawa, Mikio</p> <p></p> <p>Chaotic <span class="hlt">dynamics</span> have been effectively applied to improve various heuristic algorithms for combinatorial <span class="hlt">optimization</span> problems in many studies. Currently, the most used chaotic <span class="hlt">optimization</span> scheme is to drive heuristic solution search algorithms applicable to large-scale problems by chaotic neurodynamics including the tabu effect of the tabu search. Alternatively, meta-heuristic algorithms are used for combinatorial <span class="hlt">optimization</span> by combining a neighboring solution search algorithm, such as tabu, gradient, or other search method, with a global search algorithm, such as genetic algorithms (GA), ant colony <span class="hlt">optimization</span> (ACO), or others. In these hybrid approaches, the ACO has effectively <span class="hlt">optimized</span> the solution of many benchmark problems in the quadratic assignment problem library. In this paper, we propose a novel hybrid method that combines the effective chaotic search algorithm that has better performance than the tabu search and global search algorithms such as ACO and GA. Our results show that the proposed chaotic hybrid algorithm has better performance than the conventional chaotic search and conventional hybrid algorithms. In addition, we show that chaotic search algorithm combined with ACO has better performance than when combined with GA.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160007492','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160007492"><span><span class="hlt">Optimal</span> Reference Strain Structure for Studying <span class="hlt">Dynamic</span> Responses of Flexible Rockets</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tsushima, Natsuki; Su, Weihua; Wolf, Michael G.; Griffin, Edwin D.; Dumoulin, Marie P.</p> <p>2017-01-01</p> <p>In the proposed paper, the <span class="hlt">optimal</span> design of reference strain structures (RSS) will be performed targeting for the accurate observation of the <span class="hlt">dynamic</span> bending and torsion deformation of a flexible rocket. It will provide the detailed description of the finite-element (FE) model of a notional flexible rocket created in MSC.Patran. The RSS will be attached longitudinally along the side of the rocket and to track the deformation of the thin-walled structure under external loads. An integrated surrogate-based multi-objective <span class="hlt">optimization</span> approach will be developed to find the <span class="hlt">optimal</span> design of the RSS using the FE model. The Kriging method will be used to construct the surrogate model. For the data sampling and the performance evaluation, static/transient analyses will be performed with MSC.Natran/Patran. The multi-objective <span class="hlt">optimization</span> will be solved with NSGA-II to minimize the difference between the strains of the launch vehicle and RSS. Finally, the performance of the <span class="hlt">optimal</span> RSS will be evaluated by checking its strain-tracking capability in different numerical simulations of the flexible rocket.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25248561','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25248561"><span>Modeling multiple experiments using regularized <span class="hlt">optimization</span>: A case study on bacterial glucose utilization <span class="hlt">dynamics</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hartmann, András; Lemos, João M; Vinga, Susana</p> <p>2015-08-01</p> <p>The aim of inverse modeling is to capture the systems׳ <span class="hlt">dynamics</span> through a set of parameterized Ordinary Differential Equations (ODEs). Parameters are often required to fit multiple repeated measurements or different experimental conditions. This typically leads to a multi-objective <span class="hlt">optimization</span> problem that can be formulated as a non-convex <span class="hlt">optimization</span> problem. Modeling of glucose utilization of Lactococcus lactis bacteria is considered using in vivo Nuclear Magnetic Resonance (NMR) measurements in perturbation experiments. We propose an ODE model based on a modified time-varying exponential decay that is flexible enough to model several different experimental conditions. The starting point is an over-parameterized non-linear model that will be further simplified through an <span class="hlt">optimization</span> procedure with regularization penalties. For the parameter estimation, a stochastic global <span class="hlt">optimization</span> method, particle swarm <span class="hlt">optimization</span> (PSO) is used. A regularization is introduced to the identification, imposing that parameters should be the same across several experiments in order to identify a general model. On the remaining parameter that varies across the experiments a function is fit in order to be able to predict new experiments for any initial condition. The method is cross-validated by fitting the model to two experiments and validating the third one. Finally, the proposed model is integrated with existing models of glycolysis in order to reconstruct the remaining metabolites. The method was found useful as a general procedure to reduce the number of parameters of unidentifiable and over-parameterized models, thus supporting feature selection methods for parametric models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25725122','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25725122"><span>A differentiable reformulation for E-<span class="hlt">optimal</span> design of experiments in nonlinear <span class="hlt">dynamic</span> biosystems.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Telen, Dries; Van Riet, Nick; Logist, Flip; Van Impe, Jan</p> <p>2015-06-01</p> <p>Informative experiments are highly valuable for estimating parameters in nonlinear <span class="hlt">dynamic</span> bioprocesses. Techniques for <span class="hlt">optimal</span> experiment design ensure the systematic design of such informative experiments. The E-criterion which can be used as objective function in <span class="hlt">optimal</span> experiment design requires the maximization of the smallest eigenvalue of the Fisher information matrix. However, one problem with the minimal eigenvalue function is that it can be nondifferentiable. In addition, no closed form expression exists for the computation of eigenvalues of a matrix larger than a 4 by 4 one. As eigenvalues are normally computed with iterative methods, state-of-the-art <span class="hlt">optimal</span> control solvers are not able to exploit automatic differentiation to compute the derivatives with respect to the decision variables. In the current paper a reformulation strategy from the field of convex <span class="hlt">optimization</span> is suggested to circumvent these difficulties. This reformulation requires the inclusion of a matrix inequality constraint involving positive semidefiniteness. In this paper, this positive semidefiniteness constraint is imposed via Sylverster's criterion. As a result the maximization of the minimum eigenvalue function can be formulated in standard <span class="hlt">optimal</span> control solvers through the addition of nonlinear constraints. The presented methodology is successfully illustrated with a case study from the field of predictive microbiology.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JSV...335...55C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JSV...335...55C"><span>H∞ <span class="hlt">optimization</span> of <span class="hlt">dynamic</span> vibration absorber variant for vibration control of damped linear systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chun, Semin; Lee, Youngil; Kim, Tae-Hyoung</p> <p>2015-01-01</p> <p>This study focuses on the H∞ <span class="hlt">optimal</span> design of a <span class="hlt">dynamic</span> vibration absorber (DVA) variant for suppressing high-amplitude vibrations of damped primary systems. Unlike traditional DVA configurations, the damping element in this type of DVA is connected directly to the ground instead of the primary mass. First, a thorough graphical analysis of the variations in the maximum amplitude magnification factor depending on two design parameters, natural frequency and absorber damping ratios, is performed. The results of this analysis clearly show that any fixed-points-theory-based conventional method could provide, at best, only locally but not globally <span class="hlt">optimal</span> parameters. Second, for directly handling the H∞ <span class="hlt">optimization</span> for its <span class="hlt">optimal</span> design, a novel meta-heuristic search engine, called the diversity-guided cyclic-network-topology-based constrained particle swarm <span class="hlt">optimization</span> (Div-CNT-CPSO), is developed. The variant DVA system developed using the proposed Div-CNT-CPSO scheme is compared with those reported in the literature. The results of this comparison verified that the proposed system is better than the existing methods for suppressing the steady-state vibration amplitude of a controlled primary system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009JCoAM.232..252L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009JCoAM.232..252L"><span><span class="hlt">Optimal</span> control for nonlinear <span class="hlt">dynamical</span> system of microbial fed-batch culture</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Chongyang</p> <p>2009-10-01</p> <p>In fed-batch culture of glycerol bio-dissimilation to 1, 3-propanediol (1, 3-PD), the aim of adding glycerol is to obtain as much 1, 3-PD as possible. So a proper feeding rate is required during the process. Taking the concentration of 1, 3-PD at the terminal time as the performance index and the feeding rate of glycerol as the control function, we propose an <span class="hlt">optimal</span> control model subject to a nonlinear <span class="hlt">dynamical</span> system and constraints of continuous state and non-stationary control. A computational approach is constructed to seek the solution of the above model in two aspects. On the one hand we transcribe the <span class="hlt">optimal</span> control model into an unconstrained one based on the penalty functions and an extension of the state space; on the other hand, by approximating the control function with simple functions, we transform the unconstrained <span class="hlt">optimal</span> control problem into a sequence of nonlinear programming problems, which can be solved using gradient-based <span class="hlt">optimization</span> techniques. The convergence analysis of this approximation is also investigated. Numerical results show that, by employing the <span class="hlt">optimal</span> control policy, the concentration of 1, 3-PD at the terminal time can be increased considerably.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/877137','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/877137"><span>Developing a computationally efficient <span class="hlt">dynamic</span> multilevel hybrid <span class="hlt">optimization</span> scheme using multifidelity model interactions.</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr.; Giunta, Anthony Andrew</p> <p>2006-01-01</p> <p>Many engineering application problems use <span class="hlt">optimization</span> algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible <span class="hlt">optimization</span> algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in <span class="hlt">optimization</span>, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity <span class="hlt">optimization</span> algorithm (MFO) designed to improve the computational efficiency of an <span class="hlt">optimization</span> method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a <span class="hlt">dynamic</span> and computational time saving <span class="hlt">optimization</span> algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based <span class="hlt">optimization</span>, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMT.....8.3447L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMT.....8.3447L"><span><span class="hlt">Dynamic</span> statistical <span class="hlt">optimization</span> of GNSS radio occultation bending angles: advanced algorithm and performance analysis</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Norman, R.; Yuan, Y. B.; Fritzer, J.; Schwaerz, M.; Zhang, K.</p> <p>2015-08-01</p> <p>We introduce a new <span class="hlt">dynamic</span> statistical <span class="hlt">optimization</span> algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS)-based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical <span class="hlt">optimization</span> to provide <span class="hlt">optimal</span> bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAllenging Minisatellite Payload (CHAMP) and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction of random errors (standard deviations) of <span class="hlt">optimized</span> bending angles down to about half of their size or more; (2) reduction of the systematic differences in <span class="hlt">optimized</span> bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; and (4) realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new <span class="hlt">dynamic</span> approach in the processing of long-term RO data into a reference climate record, leading to well-characterized and high-quality atmospheric profiles over the entire stratosphere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMTD....8..811L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMTD....8..811L"><span><span class="hlt">Dynamic</span> statistical <span class="hlt">optimization</span> of GNSS radio occultation bending angles: an advanced algorithm and its performance analysis</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Norman, R.; Yuan, Y. B.; Fritzer, J.; Schwaerz, M.; Zhang, K.</p> <p>2015-01-01</p> <p>We introduce a new <span class="hlt">dynamic</span> statistical <span class="hlt">optimization</span> algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS) based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically-varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical <span class="hlt">optimization</span> to provide <span class="hlt">optimal</span> bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAMP and COSMIC measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction in random errors (standard deviations) of <span class="hlt">optimized</span> bending angles down to about two-thirds of their size or more; (2) reduction of the systematic differences in <span class="hlt">optimized</span> bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; (4) produces realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new <span class="hlt">dynamic</span> approach in the processing of long-term RO data into a reference climate record, leading to well characterized and high-quality atmospheric profiles over the entire stratosphere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJEEP..17..143X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJEEP..17..143X"><span>The <span class="hlt">Optimized</span> Operation of Gas Turbine Combined Heat and Power Units Oriented for the Grid-Connected Control</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xia, Shu; Ge, Xiaolin</p> <p>2016-04-01</p> <p>In this study, according to various grid-connected demands, the <span class="hlt">optimization</span> scheduling models of Combined Heat and Power (CHP) units are established with three scheduling modes, which are tracking the total generation scheduling mode, tracking steady output scheduling mode and tracking peaking curve scheduling mode. In order to reduce the solution difficulty, based on the principles of modern algebraic integers, linearizing techniques are developed to handle complex nonlinear constrains of the variable conditions, and the <span class="hlt">optimized</span> operation problem of CHP units is converted into a <span class="hlt">mixed-integer</span> linear programming problem. Finally, with specific examples, the 96 points day ahead, heat and power supply plans of the systems are <span class="hlt">optimized</span>. The results show that, the proposed models and methods can develop appropriate coordination heat and power <span class="hlt">optimization</span> programs according to different grid-connected control.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JIEIB.tmp...32P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JIEIB.tmp...32P"><span>Large Scale Multi-area Static/<span class="hlt">Dynamic</span> Economic Dispatch using Nature Inspired <span class="hlt">Optimization</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pandit, Manjaree; Jain, Kalpana; Dubey, Hari Mohan; Singh, Rameshwar</p> <p>2016-07-01</p> <p>Economic dispatch (ED) ensures that the generation allocation to the power units is carried out such that the total fuel cost is minimized and all the operating equality/inequality constraints are satisfied. Classical ED does not take transmission constraints into consideration, but in the present restructured power systems the tie-line limits play a very important role in deciding operational policies. ED is a <span class="hlt">dynamic</span> problem which is performed on-line in the central load dispatch centre with changing load scenarios. The <span class="hlt">dynamic</span> multi-area ED (MAED) problem is more complex due to the additional tie-line, ramp-rate and area-wise power balance constraints. Nature inspired (NI) heuristic <span class="hlt">optimization</span> methods are gaining popularity over the traditional methods for complex problems. This work presents the modified particle swarm <span class="hlt">optimization</span> (PSO) based techniques where parameter automation is effectively used for improving the search efficiency by avoiding stagnation to a sub-<span class="hlt">optimal</span> result. This work validates the performance of the PSO variants with traditional solver GAMS for single as well as multi-area economic dispatch (MAED) on three test cases of a large 140-unit standard test system having complex constraints.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JChPh.141l4110W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JChPh.141l4110W"><span>Fast <span class="hlt">optimization</span> of binary clusters using a novel <span class="hlt">dynamic</span> lattice searching method</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, Xia; Cheng, Wen</p> <p>2014-09-01</p> <p>Global <span class="hlt">optimization</span> of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual <span class="hlt">dynamic</span> lattices are constructed and a modified <span class="hlt">dynamic</span> lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the <span class="hlt">optimization</span> of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global <span class="hlt">optimization</span> of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd)79 clusters with DFT-fit parameters of Gupta potential.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25273415','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25273415"><span>Fast <span class="hlt">optimization</span> of binary clusters using a novel <span class="hlt">dynamic</span> lattice searching method.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wu, Xia; Cheng, Wen</p> <p>2014-09-28</p> <p>Global <span class="hlt">optimization</span> of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual <span class="hlt">dynamic</span> lattices are constructed and a modified <span class="hlt">dynamic</span> lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the <span class="hlt">optimization</span> of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global <span class="hlt">optimization</span> of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd)79 clusters with DFT-fit parameters of Gupta potential.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22308894','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22308894"><span>Fast <span class="hlt">optimization</span> of binary clusters using a novel <span class="hlt">dynamic</span> lattice searching method</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Wu, Xia Cheng, Wen</p> <p>2014-09-28</p> <p>Global <span class="hlt">optimization</span> of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual <span class="hlt">dynamic</span> lattices are constructed and a modified <span class="hlt">dynamic</span> lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the <span class="hlt">optimization</span> of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global <span class="hlt">optimization</span> of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd){sub 79} clusters with DFT-fit parameters of Gupta potential.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013CNSNS..18.2202P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013CNSNS..18.2202P"><span><span class="hlt">Dynamics</span> of hepatitis C under <span class="hlt">optimal</span> therapy and sampling based analysis</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pachpute, Gaurav; Chakrabarty, Siddhartha P.</p> <p>2013-08-01</p> <p>We examine two models for hepatitis C viral (HCV) <span class="hlt">dynamics</span>, one for monotherapy with interferon (IFN) and the other for combination therapy with IFN and ribavirin. <span class="hlt">Optimal</span> therapy for both the models is determined using the steepest gradient method, by defining an objective functional which minimizes infected hepatocyte levels, virion population and side-effects of the drug(s). The <span class="hlt">optimal</span> therapies for both the models show an initial period of high efficacy, followed by a gradual decline. The period of high efficacy coincides with a significant decrease in the viral load, whereas the efficacy drops after hepatocyte levels are restored. We use the Latin hypercube sampling technique to randomly generate a large number of patient scenarios and study the <span class="hlt">dynamics</span> of each set under the <span class="hlt">optimal</span> therapy already determined. Results show an increase in the percentage of responders (indicated by drop in viral load below detection levels) in case of combination therapy (72%) as compared to monotherapy (57%). Statistical tests performed to study correlations between sample parameters and time required for the viral load to fall below detection level, show a strong monotonic correlation with the death rate of infected hepatocytes, identifying it to be an important factor in deciding individual drug regimens.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5038809','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5038809"><span>Increasing the Lifetime of Mobile WSNs via <span class="hlt">Dynamic</span> <span class="hlt">Optimization</span> of Sensor Node Communication Activity</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Guimarães, Dayan Adionel; Sakai, Lucas Jun; Alberti, Antonio Marcos; de Souza, Rausley Adriano Amaral</p> <p>2016-01-01</p> <p>In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node <span class="hlt">dynamically</span> <span class="hlt">optimizes</span> the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors’ batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the <span class="hlt">optimization</span> problem an even more <span class="hlt">dynamic</span> character. We report large increased lifetimes over the non-<span class="hlt">optimized</span> network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information. PMID:27657075</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011926','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011926"><span>Conceptual Design <span class="hlt">Optimization</span> of an Augmented Stability Aircraft Incorporating <span class="hlt">Dynamic</span> Response and Actuator Constraints</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Welstead, Jason; Crouse, Gilbert L., Jr.</p> <p>2014-01-01</p> <p>Empirical sizing guidelines such as tail volume coefficients have long been used in the early aircraft design phases for sizing stabilizers, resulting in conservatively stable aircraft. While successful, this results in increased empty weight, reduced performance, and greater procurement and operational cost relative to an aircraft with <span class="hlt">optimally</span> sized surfaces. Including flight <span class="hlt">dynamics</span> in the conceptual design process allows the design to move away from empirical methods while implementing modern control techniques. A challenge of flight <span class="hlt">dynamics</span> and control is the numerous design variables, which are changing fluidly throughout the conceptual design process, required to evaluate the system response to some disturbance. This research focuses on addressing that challenge not by implementing higher order tools, such as computational fluid <span class="hlt">dynamics</span>, but instead by linking the lower order tools typically used within the conceptual design process so each discipline feeds into the other. In thisresearch, flight <span class="hlt">dynamics</span> and control was incorporated into the conceptual design process along with the traditional disciplines of vehicle sizing, weight estimation, aerodynamics, and performance. For the controller, a linear quadratic regulator structure with constant gains has been specified to reduce the user input. Coupling all the disciplines in the conceptual design phase allows the aircraft designer to explore larger design spaces where stabilizers are sized according to <span class="hlt">dynamic</span> response constraints rather than historical static margin and volume coefficient guidelines.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMNG33A1575M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMNG33A1575M"><span>Empirical prediction of climate <span class="hlt">dynamics</span>: <span class="hlt">optimal</span> models, derived from time series</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mukhin, D.; Loskutov, E. M.; Gavrilov, A.; Feigin, A. M.</p> <p>2013-12-01</p> <p>The new empirical method for prediction of climate indices by the analysis of climatic fields' time series is suggested. The method is based on construction of prognostic models of evolution operator (EO) in low-dimensional subspaces of system's phase space. One of the main points of suggested analysis is reconstruction of appropriate basis of <span class="hlt">dynamical</span> variables (predictors) from spatially distributed data: different ways of data decomposition are discussed in the report including EOFs, MSSA and other relevant data rotations. We consider the models of different complexity for EO reconstruction, from linear statistical models of particular indices to more complex artificial neural network (ANN) models of climatic patterns <span class="hlt">dynamics</span>, which take the form of discrete random <span class="hlt">dynamical</span> systems [1]. Very important problem, that always arises in empirical modeling approaches, is <span class="hlt">optimal</span> model selection criterium: appropriate regularization procedure is needed to avoid overfitted model. Particulary, it includes finding the <span class="hlt">optimal</span> structural parameters of the model such as dimension of variables vector, i.e. number of principal components used for modeling, number of states used for prediction, and number of parameters determining quality of approximation. In this report the minimal descriptive length (MDL) approach [2] is proposed for this purpose: the model providing most data compression is chosen. Results of application of suggested method to analysis of SST and SLP fields' time series [3] covering last 30-50 years are presented: predictions of different climate indices time series including NINO 3.4, MEI, PDO, NOA are shown. References: 1. Y. I. Molkov, E. M. Loskutov, D. N. Mukhin, and A. M. Feigin, Random <span class="hlt">dynamical</span> models from time series, Phys. Rev. E 85, 036216, 2012 2. Molkov, Ya.I., D.N. Mukhin, E.M. Loskutov, A.M. Feigin, and G.A. Fidelin, Using the minimum description length principle for global reconstruction of <span class="hlt">dynamic</span> systems from noisy time series. Phys</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3864701','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3864701"><span>Inference for <span class="hlt">Optimal</span> <span class="hlt">Dynamic</span> Treatment Regimes using an Adaptive m-out-of-n Bootstrap Scheme</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Chakraborty, Bibhas; Laber, Eric B.; Zhao, Yingqi</p> <p>2013-01-01</p> <p>Summary A <span class="hlt">dynamic</span> treatment regime consists of a set of decision rules that dictate how to individualize treatment to patients based on available treatment and covariate history. A common method for estimating an <span class="hlt">optimal</span> <span class="hlt">dynamic</span> treatment regime from data is Q-learning which involves nonsmooth operations of the data. This nonsmoothness causes standard asymptotic approaches for inference like the bootstrap or Taylor series arguments to breakdown if applied without correction. Here, we consider the m-out-of-n bootstrap for constructing confidence intervals for the parameters indexing the <span class="hlt">optimal</span> <span class="hlt">dynamic</span> regime. We propose an adaptive choice of m and show that it produces asymptotically correct confidence sets under fixed alternatives. Furthermore, the proposed method has the advantage of being conceptually and computationally much more simple than competing methods possessing this same theoretical property. We provide an extensive simulation study to compare the proposed method with currently available inference procedures. The results suggest that the proposed method delivers nominal coverage while being less conservative than alternatives. The proposed methods are implemented in the qLearn R-package and have been made available on the Comprehensive R-Archive Network (http://cran.r-project.org/). Analysis of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study is used as an illustrative example. PMID:23845276</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3141573','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3141573"><span>Design of <span class="hlt">Optimal</span> Treatments for Neuromusculoskeletal Disorders using Patient-Specific Multibody <span class="hlt">Dynamic</span> Models</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Fregly, Benjamin J.</p> <p>2011-01-01</p> <p>Disorders of the human neuromusculoskeletal system such as osteoarthritis, stroke, cerebral palsy, and paraplegia significantly affect mobility and result in a decreased quality of life. Surgical and rehabilitation treatment planning for these disorders is based primarily on static anatomic measurements and <span class="hlt">dynamic</span> functional measurements filtered through clinical experience. While this subjective treatment planning approach works well in many cases, it does not predict accurate functional outcome in many others. This paper presents a vision for how patient-specific multibody <span class="hlt">dynamic</span> models can serve as the foundation for an objective treatment planning approach that identifies <span class="hlt">optimal</span> treatments and treatment parameters on an individual patient basis. First, a computational paradigm is presented for constructing patient-specific multibody <span class="hlt">dynamic</span> models. This paradigm involves a combination of patient-specific skeletal models, muscle-tendon models, neural control models, and articular contact models, with the complexity of the complete model being dictated by the requirements of the clinical problem being addressed. Next, three clinical applications are presented to illustrate how such models could be used in the treatment design process. One application involves the design of patient-specific gait modification strategies for knee osteoarthritis rehabilitation, a second involves the selection of <span class="hlt">optimal</span> patient-specific surgical parameters for a particular knee osteoarthritis surgery, and the third involves the design of patient-specific muscle stimulation patterns for stroke rehabilitation. The paper concludes by discussing important challenges that need to be overcome to turn this vision into reality. PMID:21785529</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PhRvX...6c1005G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PhRvX...6c1005G"><span>Detectability Thresholds and <span class="hlt">Optimal</span> Algorithms for Community Structure in <span class="hlt">Dynamic</span> Networks</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ghasemian, Amir; Zhang, Pan; Clauset, Aaron; Moore, Cristopher; Peel, Leto</p> <p>2016-07-01</p> <p>The detection of communities within a <span class="hlt">dynamic</span> network is a common means for obtaining a coarse-grained view of a complex system and for investigating its underlying processes. While a number of methods have been proposed in the machine learning and physics literature, we lack a theoretical analysis of their strengths and weaknesses, or of the ultimate limits on when communities can be detected. Here, we study the fundamental limits of detecting community structure in <span class="hlt">dynamic</span> networks. Specifically, we analyze the limits of detectability for a <span class="hlt">dynamic</span> stochastic block model where nodes change their community memberships over time, but where edges are generated independently at each time step. Using the cavity method, we derive a precise detectability threshold as a function of the rate of change and the strength of the communities. Below this sharp threshold, we claim that no efficient algorithm can identify the communities better than chance. We then give two algorithms that are <span class="hlt">optimal</span> in the sense that they succeed all the way down to this threshold. The first uses belief propagation, which gives asymptotically <span class="hlt">optimal</span> accuracy, and the second is a fast spectral clustering algorithm, based on linearizing the belief propagation equations. These results extend our understanding of the limits of community detection in an important direction, and introduce new mathematical tools for similar extensions to networks with other types of auxiliary information.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18835500','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18835500"><span>Accurate estimation of cardinal growth temperatures of Escherichia coli from <span class="hlt">optimal</span> <span class="hlt">dynamic</span> experiments.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Van Derlinden, E; Bernaerts, K; Van Impe, J F</p> <p>2008-11-30</p> <p>Prediction of the microbial growth rate as a response to changing temperatures is an important aspect in the control of food safety and food spoilage. Accurate model predictions of the microbial evolution ask for correct model structures and reliable parameter values with good statistical quality. Given the widely accepted validity of the Cardinal Temperature Model with Inflection (CTMI) [Rosso, L., Lobry, J. R., Bajard, S. and Flandrois, J. P., 1995. Convenient model to describe the combined effects of temperature and pH on microbial growth, Applied and Environmental Microbiology, 61: 610-616], this paper focuses on the accurate estimation of its four parameters (T(min), T(opt), T(max) and micro(opt)) by applying the technique of <span class="hlt">optimal</span> experiment design for parameter estimation (OED/PE). This secondary model describes the influence of temperature on the microbial specific growth rate from the minimum to the maximum temperature for growth. <span class="hlt">Dynamic</span> temperature profiles are <span class="hlt">optimized</span> within two temperature regions ([15 degrees C, 43 degrees C] and [15 degrees C, 45 degrees C]), focusing on the minimization of the parameter estimation (co)variance (D-<span class="hlt">optimal</span> design). The <span class="hlt">optimal</span> temperature profiles are implemented in a computer controlled bioreactor, and the CTMI parameters are identified from the resulting experimental data. Approximately equal CTMI parameter values were derived irrespective of the temperature region, except for T(max). The latter could only be estimated accurately from the <span class="hlt">optimal</span> experiments within [15 degrees C, 45 degrees C]. This observation underlines the importance of selecting the upper temperature constraint for OED/PE as close as possible to the true T(max). Cardinal temperature estimates resulting from designs within [15 degrees C, 45 degrees C] correspond with values found in literature, are characterized by a small uncertainty error and yield a good result during validation. As compared to estimates from non-<span class="hlt">optimized</span> <span class="hlt">dynamic</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017MS%26E..166a2028S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MS%26E..166a2028S"><span><span class="hlt">Dynamic</span> <span class="hlt">optimization</span> approach for integrated supplier selection and tracking control of single product inventory system with product discount</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sutrisno; Widowati; Heru Tjahjana, R.</p> <p>2017-01-01</p> <p>In this paper, we propose a mathematical model in the form of <span class="hlt">dynamic</span>/multi-stage <span class="hlt">optimization</span> to solve an integrated supplier selection problem and tracking control problem of single product inventory system with product discount. The product discount will be stated as a piece-wise linear function. We use <span class="hlt">dynamic</span> programming to solve this proposed <span class="hlt">optimization</span> to determine the <span class="hlt">optimal</span> supplier and the <span class="hlt">optimal</span> product volume that will be purchased from the <span class="hlt">optimal</span> supplier for each time period so that the inventory level tracks a reference trajectory given by decision maker with minimal total cost. We give a numerical experiment to evaluate the proposed model. From the result, the <span class="hlt">optimal</span> supplier was determined for each time period and the inventory level follows the given reference well.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080022245&hterms=static+dynamic&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dstatic%2Bdynamic','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080022245&hterms=static+dynamic&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dstatic%2Bdynamic"><span>Mystic: Implementation of the Static <span class="hlt">Dynamic</span> <span class="hlt">Optimal</span> Control Algorithm for High-Fidelity, Low-Thrust Trajectory Design</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Whiffen, Gregory J.</p> <p>2006-01-01</p> <p>Mystic software is designed to compute, analyze, and visualize <span class="hlt">optimal</span> high-fidelity, low-thrust trajectories, The software can be used to analyze inter-planetary, planetocentric, and combination trajectories, Mystic also provides utilities to assist in the operation and navigation of low-thrust spacecraft. Mystic will be used to design and navigate the NASA's Dawn Discovery mission to orbit the two largest asteroids, The underlying <span class="hlt">optimization</span> algorithm used in the Mystic software is called Static/<span class="hlt">Dynamic</span> <span class="hlt">Optimal</span> Control (SDC). SDC is a nonlinear <span class="hlt">optimal</span> control method designed to <span class="hlt">optimize</span> both 'static variables' (parameters) and <span class="hlt">dynamic</span> variables (functions of time) simultaneously. SDC is a general nonlinear <span class="hlt">optimal</span> control algorithm based on Bellman's principal.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012PMB....57N.173E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012PMB....57N.173E"><span>Optical tracking of contrast medium bolus to <span class="hlt">optimize</span> bolus shape and timing in <span class="hlt">dynamic</span> computed tomography</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Eisa, Fabian; Brauweiler, Robert; Peetz, Alexander; Hupfer, Martin; Nowak, Tristan; Kalender, Willi A.</p> <p>2012-05-01</p> <p>One of the biggest challenges in <span class="hlt">dynamic</span> contrast-enhanced CT is the <span class="hlt">optimal</span> synchronization of scan start and duration with contrast medium administration in order to <span class="hlt">optimize</span> image contrast and to reduce the amount of contrast medium. We present a new optically based approach, which was developed to investigate and <span class="hlt">optimize</span> bolus timing and shape. The time-concentration curve of an intravenously injected test bolus of a dye is measured in peripheral vessels with an optical sensor prior to the diagnostic CT scan. The curves can be used to assess bolus shapes as a function of injection protocols and to determine contrast medium arrival times. Preliminary results for phantom and animal experiments showed the expected linear behavior between dye concentration and absorption. The kinetics of the dye was compared to iodinated contrast medium and was found to be in good agreement. The contrast enhancement curves were reliably detected in three mice with individual bolus shapes and delay times of 2.1, 3.5 and 6.1 s, respectively. The optical sensor appears to be a promising approach to <span class="hlt">optimize</span> injection protocols and contrast enhancement timing and is applicable to all modalities without implying any additional radiation dose. Clinical tests are still necessary.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22789811','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22789811"><span><span class="hlt">Optimal</span> investment for enhancing social concern about biodiversity conservation: a <span class="hlt">dynamic</span> approach.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lee, Joung Hun; Iwasa, Yoh</p> <p>2012-11-01</p> <p>To maintain biodiversity conservation areas, we need to invest in activities, such as monitoring the condition of the ecosystem, preventing illegal exploitation, and removing harmful alien species. These require a constant supply of resources, the level of which is determined by the concern of the society about biodiversity conservation. In this paper, we study the <span class="hlt">optimal</span> fraction of the resources to invest in activities for enhancing the social concern y(t) by environmental education, museum displays, publications, and media exposure. We search for the strategy that maximizes the time-integral of the quality of the conservation area x(t) with temporal discounting. Analyses based on <span class="hlt">dynamic</span> programming and Pontryagin's maximum principle show that the <span class="hlt">optimal</span> control consists of two phases: (1) in the first phase, the social concern level approaches to the final <span class="hlt">optimal</span> value y(∗), (2) in the second phase, resources are allocated to both activities, and the social concern level is kept constant y(t) = y(∗). If the social concern starts from a low initial level, the <span class="hlt">optimal</span> path includes a period in which the quality of the conservation area declines temporarily, because all the resources are invested to enhance the social concern. When the support rate increases with the quality of the conservation area itself x(t) as well as with the level of social concern y(t), both variables may increase simultaneously in the second phase. We discuss the implication of the results to good management of biodiversity conservation areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EnOp...48..851Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EnOp...48..851Z"><span>Using support vector machine and <span class="hlt">dynamic</span> parameter encoding to enhance global <span class="hlt">optimization</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zheng, Z.; Chen, X.; Liu, C.; Huang, K.</p> <p>2016-05-01</p> <p>This study presents an approach which combines support vector machine (SVM) and <span class="hlt">dynamic</span> parameter encoding (DPE) to enhance the run-time performance of global <span class="hlt">optimization</span> with time-consuming fitness function evaluations. SVMs are used as surrogate models to partly substitute for fitness evaluations. To reduce the computation time and guarantee correct convergence, this work proposes a novel strategy to adaptively adjust the number of fitness evaluations needed according to the approximate error of the surrogate model. Meanwhile, DPE is employed to compress the solution space, so that it not only accelerates the convergence but also decreases the approximate error. Numerical results of <span class="hlt">optimizing</span> a few benchmark functions and an antenna in a practical application are presented, which verify the feasibility, efficiency and robustness of the proposed approach.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22098427','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22098427"><span><span class="hlt">Optimizing</span> the <span class="hlt">dynamic</span> range extension of a radiochromic film dosimetry system</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Devic, Slobodan; Tomic, Nada; Soares, Christopher G.; Podgorsak, Ervin B.</p> <p>2009-02-15</p> <p>The authors present a radiochromic film dosimetry protocol for a multicolor channel radiochromic film dosimetry system consisting of the external beam therapy (EBT) model GAFCHROMIC film and the Epson Expression 1680 flat-bed document scanner. Instead of extracting only the red color channel, the authors are using all three color channels in the absorption spectrum of the EBT film to extend the <span class="hlt">dynamic</span> dose range of the radiochromic film dosimetry system. By <span class="hlt">optimizing</span> the dose range for each color channel, they obtained a system that has both precision and accuracy below 1.5%, and the <span class="hlt">optimized</span> ranges are 0-4 Gy for the red channel, 4-50 Gy for the green channel, and above 50 Gy for the blue channel.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26764609','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26764609"><span><span class="hlt">Optimal</span> control in nonequilibrium systems: <span class="hlt">Dynamic</span> Riemannian geometry of the Ising model.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Rotskoff, Grant M; Crooks, Gavin E</p> <p>2015-12-01</p> <p>A general understanding of <span class="hlt">optimal</span> control in nonequilibrium systems would illuminate the operational principles of biological and artificial nanoscale machines. Recent work has shown that a system driven out of equilibrium by a linear response protocol is endowed with a Riemannian metric related to generalized susceptibilities, and that geodesics on this manifold are the nonequilibrium control protocols with the lowest achievable dissipation. While this elegant mathematical framework has inspired numerous studies of exactly solvable systems, no description of the thermodynamic geometry yet exists when the metric cannot be derived analytically. Herein, we numerically construct the <span class="hlt">dynamic</span> metric of the two-dimensional Ising model in order to study <span class="hlt">optimal</span> protocols for reversing the net magnetization.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5033865','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5033865"><span><span class="hlt">Dynamic</span> dual-isotope molecular imaging elucidates principles for <span class="hlt">optimizing</span> intrathecal drug delivery</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Wolf, Daniel A.; Hesterman, Jacob Y.; Sullivan, Jenna M.; Orcutt, Kelly D.; Silva, Matthew D.; Lobo, Merryl; Wellman, Tyler; Hoppin, Jack</p> <p>2016-01-01</p> <p>The intrathecal (IT) dosing route offers a seemingly obvious solution for delivering drugs directly to the central nervous system. However, gaps in understanding drug molecule behavior within the anatomically and kinetically unique environment of the mammalian IT space have impeded the establishment of pharmacokinetic principles for <span class="hlt">optimizing</span> regional drug exposure along the neuraxis. Here, we have utilized high-resolution single-photon emission tomography with X-ray computed tomography to study the behavior of multiple molecular imaging tracers following an IT bolus injection, with supporting histology, autoradiography, block-face tomography, and MRI. Using simultaneous dual-isotope imaging, we demonstrate that the regional CNS tissue exposure of molecules with varying chemical properties is affected by IT space anatomy, cerebrospinal fluid (CSF) <span class="hlt">dynamics</span>, CSF clearance routes, and the location and volume of the injected bolus. These imaging approaches can be used across species to <span class="hlt">optimize</span> the safety and efficacy of IT drug therapy for neurological disorders. PMID:27699254</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25635665','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25635665"><span>Fluid <span class="hlt">dynamic</span> analysis of a continuous stirred tank reactor for technical <span class="hlt">optimization</span> of wastewater digestion.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hurtado, F J; Kaiser, A S; Zamora, B</p> <p>2015-03-15</p> <p>Continuous stirred tank reactors (CSTR) are widely used in wastewater treatment plants to reduce the organic matter and microorganism present in sludge by anaerobic digestion. The present study carries out a numerical analysis of the fluid <span class="hlt">dynamic</span> behaviour of a CSTR in order to <span class="hlt">optimize</span> the process energetically. The characterization of the sludge flow inside the digester tank, the residence time distribution and the active volume of the reactor under different criteria are determined. The effects of design and power of the mixing system on the active volume of the CSTR are analyzed. The numerical model is solved under non-steady conditions by examining the evolution of the flow during the stop and restart of the mixing system. An intermittent regime of the mixing system, which kept the active volume between 94% and 99%, is achieved. The results obtained can lead to the eventual energy <span class="hlt">optimization</span> of the mixing system of the CSTR.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20150005628&hterms=CHemistry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DCHemistry','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20150005628&hterms=CHemistry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DCHemistry"><span>Partial Overhaul and Initial Parallel <span class="hlt">Optimization</span> of KINETICS, a Coupled <span class="hlt">Dynamics</span> and Chemistry Atmosphere Model</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nguyen, Howard; Willacy, Karen; Allen, Mark</p> <p>2012-01-01</p> <p>KINETICS is a coupled <span class="hlt">dynamics</span> and chemistry atmosphere model that is data intensive and computationally demanding. The potential performance gain from using a supercomputer motivates the adaptation from a serial version to a parallelized one. Although the initial parallelization had been done, bottlenecks caused by an abundance of communication calls between processors led to an unfavorable drop in performance. Before starting on the parallel <span class="hlt">optimization</span> process, a partial overhaul was required because a large emphasis was placed on streamlining the code for user convenience and revising the program to accommodate the new supercomputers at Caltech and JPL. After the first round of <span class="hlt">optimizations</span>, the partial runtime was reduced by a factor of 23; however, performance gains are dependent on the size of the data, the number of processors requested, and the computer used.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AIPC.1776i0052D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AIPC.1776i0052D"><span>Evaluation of a new parallel numerical parameter <span class="hlt">optimization</span> algorithm for a <span class="hlt">dynamical</span> system</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Duran, Ahmet; Tuncel, Mehmet</p> <p>2016-10-01</p> <p>It is important to have a scalable parallel numerical parameter <span class="hlt">optimization</span> algorithm for a <span class="hlt">dynamical</span> system used in financial applications where time limitation is crucial. We use Message Passing Interface parallel programming and present such a new parallel algorithm for parameter estimation. For example, we apply the algorithm to the asset flow differential equations that have been developed and analyzed since 1989 (see [3-6] and references contained therein). We achieved speed-up for some time series to run up to 512 cores (see [10]). Unlike [10], we consider more extensive financial market situations, for example, in presence of low volatility, high volatility and stock market price at a discount/premium to its net asset value with varying magnitude, in this work. Moreover, we evaluated the convergence of the model parameter vector, the nonlinear least squares error and maximum improvement factor to quantify the success of the <span class="hlt">optimization</span> process depending on the number of initial parameter vectors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/13828','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/13828"><span><span class="hlt">Optimization</span> of Fluid Front <span class="hlt">Dynamics</span> in Porous Media Using Rate Control: I. Equal Mobility Fluids</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Sundaryanto, Bagus; Yortsos, Yanis C.</p> <p>1999-10-18</p> <p>In applications involving this injection of a fluid in a porous medium to displace another fluid, a main objective is the maximization of the displacement efficiency. For a fixed arrangement of injection and production points (sources and sinks), such <span class="hlt">optimization</span> is possible by controlling the injection rate policy. Despite its practical relevance, however, this aspect has received scant attention in the literature. In this paper, a fundamental approach based on <span class="hlt">optimal</span> control theory, for the case when the fluids are miscible, of equal viscosity and in the absence of dispersion and gravity effects. Both homogeneous and heterogeneous porous media are considered. From a fluid <span class="hlt">dynamics</span> viewpoint, this is a problem in the deformation of material lines in porous media, as a function of time-varying injection rates.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20100031269&hterms=moon+colonization&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dmoon%2Bcolonization','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20100031269&hterms=moon+colonization&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dmoon%2Bcolonization"><span><span class="hlt">Dynamic</span> <span class="hlt">Optimization</span> of Multi-Spacecraft Relative Navigation Configurations in the Earth-Moon System</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Villac, Benjamin; Chow, Channing; Lo, Martin; Hintz, Gerald; Nazari, Zahra</p> <p>2010-01-01</p> <p>In this paper, the notion of relative navigation introduced by Hill, Lo and Born is analyzed for a large class of periodic orbits in the Earth-Moon three-body problem, due to its potential in supporting Moon exploration efforts. In particular, a navigation metric is introduced and used as a cost function to <span class="hlt">optimize</span> over a class of periodic orbits. While the problem could be solve locally as an <span class="hlt">optimal</span> control problem, a <span class="hlt">dynamical</span> based approach that allows for a global/systematic view of the problem is proposed. First, the simpler problem of multiple spacecraft placement on a given periodic orbit is solved before the notion of continuation and bifurcation analysis is used to expand the range of solutions thus obtained.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22410419','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22410419"><span>Coherent control of plasma <span class="hlt">dynamics</span> by feedback-<span class="hlt">optimized</span> wavefront manipulation</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>He, Z.-H.; Hou, B.; Gao, G.; Nees, J. A.; Krushelnick, K.; Thomas, A. G. R.; Lebailly, V.; Clarke, R.</p> <p>2015-05-15</p> <p>Plasmas generated by an intense laser pulse can support coherent structures such as large amplitude wakefield that can affect the outcome of an experiment. We investigate the coherent control of plasma <span class="hlt">dynamics</span> by feedback-<span class="hlt">optimized</span> wavefront manipulation using a deformable mirror. The experimental outcome is directly used as feedback in an evolutionary algorithm for <span class="hlt">optimization</span> of the phase front of the driving laser pulse. In this paper, we applied this method to two different experiments: (i) acceleration of electrons in laser driven plasma waves and (ii) self-compression of optical pulses induced by ionization nonlinearity. The manipulation of the laser wavefront leads to orders of magnitude improvement to electron beam properties such as the peak charge, beam divergence, and transverse emittance. The demonstration of coherent control for plasmas opens new possibilities for future laser-based accelerators and their applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhRvE..95b2118L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhRvE..95b2118L"><span>Combinatorial <span class="hlt">optimization</span> using <span class="hlt">dynamical</span> phase transitions in driven-dissipative systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Leleu, Timothée; Yamamoto, Yoshihisa; Utsunomiya, Shoko; Aihara, Kazuyuki</p> <p>2017-02-01</p> <p>The <span class="hlt">dynamics</span> of driven-dissipative systems is shown to be well-fitted for achieving efficient combinatorial <span class="hlt">optimization</span>. The proposed method can be applied to solve any combinatorial <span class="hlt">optimization</span> problem that is equivalent to minimizing an Ising Hamiltonian. Moreover, the <span class="hlt">dynamics</span> considered can be implemented using various physical systems as it is based on generic dynamics—the normal form of the supercritical pitchfork bifurcation. The computational principle of the proposed method relies on an hybrid analog-digital representation of the binary Ising spins by considering the gradient descent of a Lyapunov function that is the sum of an analog Ising Hamiltonian and archetypal single or double-well potentials. By gradually changing the shape of the latter potentials from a single to double well shape, it can be shown that the first nonzero steady states to become stable are associated with global minima of the Ising Hamiltonian, under the approximation that all analog spins have the same amplitude. In the more general case, the heterogeneity in amplitude between analog spins induces the stabilization of local minima, which reduces the quality of solutions to combinatorial <span class="hlt">optimization</span> problems. However, we show that the heterogeneity in amplitude can be reduced by setting the parameters of the driving signal near a regime, called the <span class="hlt">dynamic</span> phase transition, where the analog spins' DC components map more accurately the global minima of the Ising Hamiltonian which, in turn, increases the quality of solutions found. Last, we discuss the possibility of a physical implementation of the proposed method using networks of degenerate optical parametric oscillators.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ChJME..29..124C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ChJME..29..124C"><span><span class="hlt">Dynamic</span> topology multi force particle swarm <span class="hlt">optimization</span> algorithm and its application</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, Dongning; Zhang, Ruixing; Yao, Chengyu; Zhao, Zheyu</p> <p>2016-01-01</p> <p>Particle swarm <span class="hlt">optimization</span> (PSO) algorithm is an effective bio-inspired algorithm but it has shortage of premature convergence. Researchers have made some improvements especially in force rules and population topologies. However, the current algorithms only consider a single kind of force rules and lack consideration of comprehensive improvement in both multi force rules and population topologies. In this paper, a <span class="hlt">dynamic</span> topology multi force particle swarm <span class="hlt">optimization</span> (DTMFPSO) algorithm is proposed in order to get better search performance. First of all, the principle of the presented multi force particle swarm <span class="hlt">optimization</span> (MFPSO) algorithm is that different force rules are used in different search stages, which can balance the ability of global and local search. Secondly, a fitness-driven edge-changing (FE) topology based on the probability selection mechanism of roulette method is designed to cut and add edges between the particles, and the DTMFPSO algorithm is proposed by combining the FE topology with the MFPSO algorithm through concurrent evolution of both algorithm and structure in order to further improve the search accuracy. Thirdly, Benchmark functions are employed to evaluate the performance of the DTMFPSO algorithm, and test results show that the proposed algorithm is better than the well-known PSO algorithms, such as µPSO, MPSO, and EPSO algorithms. Finally, the proposed algorithm is applied to <span class="hlt">optimize</span> the process parameters for ultrasonic vibration cutting on SiC wafer, and the surface quality of the SiC wafer is improved by 12.8% compared with the PSO algorithm in Ref. [25]. This research proposes a DTMFPSO algorithm with multi force rules and <span class="hlt">dynamic</span> population topologies evolved simultaneously, and it has better search performance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1209122','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1209122"><span>Progress on <span class="hlt">optimization</span> of the nonlinear beam <span class="hlt">dynamics</span> in the MEIC collider rings</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Nosochkov, Y. M.; Cai, Y.; Sullivan, M.; Wang, M-H; Wienands, U.; Morozov, V. S.; Derbenev, Ya. S.; Lin, F.; Pilat, F.; Zhang, Y.</p> <p>2015-07-13</p> <p>One of the key design features of the Medium-energy Electron-Ion Collider (MEIC) proposed by Jefferson Lab is a small beta function at the interaction point (IP) allowing one to achieve a high luminosity of up to 10<sup>34</sup> cm<sup>-2</sup>s<sup>-1</sup>. The required strong beam focusing unavoidably causes large chromatic effects such as chromatic tune spread and beam smear at the IP, which need to be compensated. This paper reports recent progress in our development of a chromaticity correction scheme for the ion ring including <span class="hlt">optimization</span> of <span class="hlt">dynamic</span> aperture and momentum acceptance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1223463','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1223463"><span>Progress on <span class="hlt">Optimization</span> of the Nonlinear Beam <span class="hlt">Dynamics</span> in the MEIC Collider Rings</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Morozov, Vasiliy S.; Derbenev, Yaroslav S.; Lin, Fanglei; Pilat, Fulvia; Zhang, Yuhong; Cai, Y.; Nosochkov, Y. M.; Sullivan, Michael; Wang, M.-H.; Wienands, Uli</p> <p>2015-09-01</p> <p>One of the key design features of the Medium-energy Electron-Ion Collider (MEIC) proposed by Jefferson Lab is a small beta function at the interaction point (IP) allowing one to achieve a high luminosity of up to 10<sup>34</sup> cm<sup>-2</sup>s<sup>-1</sup>. The required strong beam focusing unavoidably causes large chromatic effects such as chromatic tune spread and beam smear at the IP, which need to be compensated. This paper reports recent progress in our development of a chromaticity correction scheme for the ion ring including <span class="hlt">optimization</span> of <span class="hlt">dynamic</span> aperture and momentum acceptance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.4050D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.4050D"><span><span class="hlt">Optimizing</span> conjunctive use of surface water and groundwater resources with stochastic <span class="hlt">dynamic</span> programming</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Davidsen, Claus; Liu, Suxia; Mo, Xingguo; Rosbjerg, Dan; Bauer-Gottwein, Peter</p> <p>2014-05-01</p> <p><span class="hlt">Optimal</span> management of conjunctive use of surface water and groundwater has been attempted with different algorithms in the literature. In this study, a hydro-economic modelling approach to <span class="hlt">optimize</span> conjunctive use of scarce surface water and groundwater resources under uncertainty is presented. A stochastic <span class="hlt">dynamic</span> programming (SDP) approach is used to minimize the basin-wide total costs arising from water allocations and water curtailments. <span class="hlt">Dynamic</span> allocation problems with inclusion of groundwater resources proved to be more complex to solve with SDP than pure surface water allocation problems due to head-dependent pumping costs. These <span class="hlt">dynamic</span> pumping costs strongly affect the total costs and can lead to non-convexity of the future cost function. The water user groups (agriculture, industry, domestic) are characterized by inelastic demands and fixed water allocation and water supply curtailment costs. As in traditional SDP approaches, one step-ahead sub-problems are solved to find the <span class="hlt">optimal</span> management at any time knowing the inflow scenario and reservoir/aquifer storage levels. These non-linear sub-problems are solved using a genetic algorithm (GA) that minimizes the sum of the immediate and future costs for given surface water reservoir and groundwater aquifer end storages. The immediate cost is found by solving a simple linear allocation sub-problem, and the future costs are assessed by interpolation in the total cost matrix from the following time step. Total costs for all stages, reservoir states, and inflow scenarios are used as future costs to drive a forward moving simulation under uncertain water availability. The use of a GA to solve the sub-problems is computationally more costly than a traditional SDP approach with linearly interpolated future costs. However, in a two-reservoir system the future cost function would have to be represented by a set of planes, and strict convexity in both the surface water and groundwater dimension cannot be maintained</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012PhPro..33..827M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012PhPro..33..827M"><span><span class="hlt">Optimization</span> for Hub-and-Spoke Port Logistics Network of <span class="hlt">Dynamic</span> Hinterland</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ming-Jun, Ji; Yan-Ling, Chu</p> <p></p> <p>The port logistics and its regional economic react on each other and develop in unison. This paper studies the Hub-and-Spoke port logistics network which is a transportation system between the sea routes and ports hinterland transport routes. An <span class="hlt">optimization</span> model is proposed with the objective of the total transportation cost in the regional port group based on the conditions of <span class="hlt">dynamic</span> hinterland. This paper not only ensures every port in the hub-and spoke port logistics network to achieve its maximum economic benefits, but also makes the entire system get the minimum total transportation cost in the view of quantitative point. In order to illustrate the validity of the model, the example was solved. The results show that the model is feasible. Furthermore, the competitiveness power of the port, the demarcation of hinterland and the traffic capacity are changed <span class="hlt">dynamically</span> in the model, which is closer to the real system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE10153E..0RY','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE10153E..0RY"><span>The <span class="hlt">optimizations</span> of CGH generation algorithms based on multiple GPUs for 3D <span class="hlt">dynamic</span> holographic display</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Dan; Liu, Juan; Zhang, Yingxi; Li, Xin; Wang, Yongtian</p> <p>2016-10-01</p> <p>Holographic display has been considered as a promising display technology. Currently, low-speed generation of holograms with big holographic data is one of crucial bottlenecks for three dimensional (3D) <span class="hlt">dynamic</span> holographic display. To solve this problem, the acceleration method computation platform is presented based on look-up table point source method. The computer generated holograms (CGHs) acquisition is sped up by offline file loading and inline calculation <span class="hlt">optimization</span>, where a pure phase CGH with gigabyte data is encoded to record an object with 10 MB sampling data. Both numerical simulation and optical experiment demonstrate that the CGHs with 1920×1080 resolution by the proposed method can be applied to the 3D objects reconstruction with high quality successfully. It is believed that the CGHs with huge data can be generated by the proposed method with high speed for 3D <span class="hlt">dynamic</span> holographic display in near future.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21517543','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21517543"><span>Riemannian geometric approach to human arm <span class="hlt">dynamics</span>, movement <span class="hlt">optimization</span>, and invariance.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Biess, Armin; Flash, Tamar; Liebermann, Dario G</p> <p>2011-03-01</p> <p>We present a generally covariant formulation of human arm <span class="hlt">dynamics</span> and <span class="hlt">optimization</span> principles in Riemannian configuration space. We extend the one-parameter family of mean-squared-derivative (MSD) cost functionals from Euclidean to Riemannian space, and we show that they are mathematically identical to the corresponding <span class="hlt">dynamic</span> costs when formulated in a Riemannian space equipped with the kinetic energy metric. In particular, we derive the equivalence of the minimum-jerk and minimum-torque change models in this metric space. Solutions of the one-parameter family of MSD variational problems in Riemannian space are given by (reparameterized) geodesic paths, which correspond to movements with least muscular effort. Finally, movement invariants are derived from symmetries of the Riemannian manifold. We argue that the geometrical structure imposed on the arm's configuration space may provide insights into the emerging properties of the movements generated by the motor system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011PhRvE..83c1927B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011PhRvE..83c1927B"><span>Riemannian geometric approach to human arm <span class="hlt">dynamics</span>, movement <span class="hlt">optimization</span>, and invariance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Biess, Armin; Flash, Tamar; Liebermann, Dario G.</p> <p>2011-03-01</p> <p>We present a generally covariant formulation of human arm <span class="hlt">dynamics</span> and <span class="hlt">optimization</span> principles in Riemannian configuration space. We extend the one-parameter family of mean-squared-derivative (MSD) cost functionals from Euclidean to Riemannian space, and we show that they are mathematically identical to the corresponding <span class="hlt">dynamic</span> costs when formulated in a Riemannian space equipped with the kinetic energy metric. In particular, we derive the equivalence of the minimum-jerk and minimum-torque change models in this metric space. Solutions of the one-parameter family of MSD variational problems in Riemannian space are given by (reparametrized) geodesic paths, which correspond to movements with least muscular effort. Finally, movement invariants are derived from symmetries of the Riemannian manifold. We argue that the geometrical structure imposed on the arm’s configuration space may provide insights into the emerging properties of the movements generated by the motor system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.esajournals.org/doi/abs/10.1890/0012-9658(2002)083%5B1357%3ATIOFFI%5D2.0.CO%3B2','USGSPUBS'); return false;" href="http://www.esajournals.org/doi/abs/10.1890/0012-9658(2002)083%5B1357%3ATIOFFI%5D2.0.CO%3B2"><span>The importance of functional form in <span class="hlt">optimal</span> control solutions of problems in population <span class="hlt">dynamics</span></span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Runge, M.C.; Johnson, F.A.</p> <p>2002-01-01</p> <p><span class="hlt">Optimal</span> control theory is finding increased application in both theoretical and applied ecology, and it is a central element of adaptive resource management. One of the steps in an adaptive management process is to develop alternative models of system <span class="hlt">dynamics</span>, models that are all reasonable in light of available data, but that differ substantially in their implications for <span class="hlt">optimal</span> control of the resource. We explored how the form of the recruitment and survival functions in a general population model for ducks affected the patterns in the <span class="hlt">optimal</span> harvest strategy, using a combination of analytical, numerical, and simulation techniques. We compared three relationships between recruitment and population density (linear, exponential, and hyperbolic) and three relationships between survival during the nonharvest season and population density (constant, logistic, and one related to the compensatory harvest mortality hypothesis). We found that the form of the component functions had a dramatic influence on the <span class="hlt">optimal</span> harvest strategy and the ultimate equilibrium state of the system. For instance, while it is commonly assumed that a compensatory hypothesis leads to higher <span class="hlt">optimal</span> harvest rates than an additive hypothesis, we found this to depend on the form of the recruitment function, in part because of differences in the <span class="hlt">optimal</span> steady-state population density. This work has strong direct consequences for those developing alternative models to describe harvested systems, but it is relevant to a larger class of problems applying <span class="hlt">optimal</span> control at the population level. Often, different functional forms will not be statistically distinguishable in the range of the data. Nevertheless, differences between the functions outside the range of the data can have an important impact on the <span class="hlt">optimal</span> harvest strategy. Thus, development of alternative models by identifying a single functional form, then choosing different parameter combinations from extremes on the likelihood</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://eric.ed.gov/?q=memory+AND+limitations&pg=5&id=EJ720501','ERIC'); return false;" href="http://eric.ed.gov/?q=memory+AND+limitations&pg=5&id=EJ720501"><span><span class="hlt">Optimal</span> Least-Squares Unidimensional Scaling: Improved Branch-and-Bound Procedures and Comparison to <span class="hlt">Dynamic</span> Programming</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Brusco, Michael J.; Stahl, Stephanie</p> <p>2005-01-01</p> <p>There are two well-known methods for obtaining a guaranteed globally <span class="hlt">optimal</span> solution to the problem of least-squares unidimensional scaling of a symmetric dissimilarity matrix: (a) <span class="hlt">dynamic</span> programming, and (b) branch-and-bound. <span class="hlt">Dynamic</span> programming is generally more efficient than branch-and-bound, but the former is limited to matrices with…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21106190','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21106190"><span>A synergic simulation-<span class="hlt">optimization</span> approach for analyzing biomolecular <span class="hlt">dynamics</span> in living organisms.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sadegh Zadeh, Kouroush</p> <p>2011-01-01</p> <p>A synergic duo simulation-<span class="hlt">optimization</span> approach was developed and implemented to study protein-substrate <span class="hlt">dynamics</span> and binding kinetics in living organisms. The forward problem is a system of several coupled nonlinear partial differential equations which, with a given set of kinetics and diffusion parameters, can provide not only the commonly used bleached area-averaged time series in fluorescence microscopy experiments but more informative full biomolecular/drug space-time series and can be successfully used to study <span class="hlt">dynamics</span> of both Dirac and Gaussian fluorescence-labeled biomacromolecules in vivo. The incomplete Cholesky preconditioner was coupled with the finite difference discretization scheme and an adaptive time-stepping strategy to solve the forward problem. The proposed approach was validated with analytical as well as reference solutions and used to simulate <span class="hlt">dynamics</span> of GFP-tagged glucocorticoid receptor (GFP-GR) in mouse cancer cell during a fluorescence recovery after photobleaching experiment. Model analysis indicates that the commonly practiced bleach spot-averaged time series is not an efficient approach to extract physiological information from the fluorescence microscopy protocols. It was recommended that experimental biophysicists should use full space-time series, resulting from experimental protocols, to study <span class="hlt">dynamics</span> of biomacromolecules and drugs in living organisms. It was also concluded that in parameterization of biological mass transfer processes, setting the norm of the gradient of the penalty function at the solution to zero is not an efficient stopping rule to end the inverse algorithm. Theoreticians should use multi-criteria stopping rules to quantify model parameters by <span class="hlt">optimization</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25375568','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25375568"><span>Network <span class="hlt">dynamics</span> for <span class="hlt">optimal</span> compressive-sensing input-signal recovery.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Barranca, Victor J; Kovačič, Gregor; Zhou, Douglas; Cai, David</p> <p>2014-10-01</p> <p>By using compressive sensing (CS) theory, a broad class of static signals can be reconstructed through a sequence of very few measurements in the framework of a linear system. For networks with nonlinear and time-evolving <span class="hlt">dynamics</span>, is it similarly possible to recover an unknown input signal from only a small number of network output measurements? We address this question for pulse-coupled networks and investigate the network <span class="hlt">dynamics</span> necessary for successful input signal recovery. Determining the specific network characteristics that correspond to a minimal input reconstruction error, we are able to achieve high-quality signal reconstructions with few measurements of network output. Using various measures to characterize <span class="hlt">dynamical</span> properties of network output, we determine that networks with highly variable and aperiodic output can successfully encode network input information with high fidelity and achieve the most accurate CS input reconstructions. For time-varying inputs, we also find that high-quality reconstructions are achievable by measuring network output over a relatively short time window. Even when network inputs change with time, the same <span class="hlt">optimal</span> choice of network characteristics and corresponding <span class="hlt">dynamics</span> apply as in the case of static inputs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhRvE..90d2908B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhRvE..90d2908B"><span>Network <span class="hlt">dynamics</span> for <span class="hlt">optimal</span> compressive-sensing input-signal recovery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barranca, Victor J.; Kovačič, Gregor; Zhou, Douglas; Cai, David</p> <p>2014-10-01</p> <p>By using compressive sensing (CS) theory, a broad class of static signals can be reconstructed through a sequence of very few measurements in the framework of a linear system. For networks with nonlinear and time-evolving <span class="hlt">dynamics</span>, is it similarly possible to recover an unknown input signal from only a small number of network output measurements? We address this question for pulse-coupled networks and investigate the network <span class="hlt">dynamics</span> necessary for successful input signal recovery. Determining the specific network characteristics that correspond to a minimal input reconstruction error, we are able to achieve high-quality signal reconstructions with few measurements of network output. Using various measures to characterize <span class="hlt">dynamical</span> properties of network output, we determine that networks with highly variable and aperiodic output can successfully encode network input information with high fidelity and achieve the most accurate CS input reconstructions. For time-varying inputs, we also find that high-quality reconstructions are achievable by measuring network output over a relatively short time window. Even when network inputs change with time, the same <span class="hlt">optimal</span> choice of network characteristics and corresponding <span class="hlt">dynamics</span> apply as in the case of static inputs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25820090','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25820090"><span>Adaptive control schemes for improving <span class="hlt">dynamic</span> performance of efficiency-<span class="hlt">optimized</span> induction motor drives.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Kumar, Navneet; Raj Chelliah, Thanga; Srivastava, S P</p> <p>2015-07-01</p> <p>Model Based Control (MBC) is one of the energy <span class="hlt">optimal</span> controllers used in vector-controlled Induction Motor (IM) for controlling the excitation of motor in accordance with torque and speed. MBC offers energy conservation especially at part-load operation, but it creates ripples in torque and speed during load transition, leading to poor <span class="hlt">dynamic</span> performance of the drive. This study investigates the opportunity for improving <span class="hlt">dynamic</span> performance of a three-phase IM operating with MBC and proposes three control schemes: (i) MBC with a low pass filter (ii) torque producing current (iqs) injection in the output of speed controller (iii) Variable Structure Speed Controller (VSSC). The pre and post operation of MBC during load transition is also analyzed. The <span class="hlt">dynamic</span> performance of a 1-hp, three-phase squirrel-cage IM with mine-hoist load diagram is tested. Test results are provided for the conventional field-oriented (constant flux) control and MBC (adjustable excitation) with proposed schemes. The effectiveness of proposed schemes is also illustrated for parametric variations. The test results and subsequent analysis confer that the motor <span class="hlt">dynamics</span> improves significantly with all three proposed schemes in terms of overshoot/undershoot peak amplitude of torque and DC link power in addition to energy saving during load transitions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ArtSa..51..123B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ArtSa..51..123B"><span><span class="hlt">Optimal</span> Estimation of a Subset of Integers with Application to GNSS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brack, A.</p> <p>2016-12-01</p> <p>The problem of integer or <span class="hlt">mixed</span> <span class="hlt">integer</span>/real valued parameter estimation in linear models is considered. It is a well-known result that for zero-mean additive Gaussian measurement noise the integer least-squares estimator is <span class="hlt">optimal</span> in the sense of maximizing the probability of correctly estimating the full vector of integer parameters. In applications such as global navigation satellite system ambiguity resolution, it can be beneficial to resolve only a subset of all integer parameters. We derive the estimator that leads to the highest possible success rate for a given integer subset and compare its performance to suboptimal integer mappings via numerical studies. Implementation aspects of the <span class="hlt">optimal</span> estimator as well as subset selection criteria are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25540814','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25540814"><span><span class="hlt">Optimal</span> control strategy design based on <span class="hlt">dynamic</span> programming for a dual-motor coupling-propulsion system.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zhang, Shuo; Zhang, Chengning; Han, Guangwei; Wang, Qinghui</p> <p>2014-01-01</p> <p>A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its <span class="hlt">optimal</span> control strategy is studied in this paper. The necessary <span class="hlt">dynamic</span> features of energy loss for subsystems is modeled. <span class="hlt">Dynamic</span> programming (DP) technique is applied to find the <span class="hlt">optimal</span> control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Improved control rules are extracted from the DP-based control solution, forming near-<span class="hlt">optimal</span> control strategies. Simulation results demonstrate that a significant improvement in reducing energy loss due to the dual-motor coupling-propulsion system (DMCPS) running is realized without increasing the frequency of the mode switch.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4161121','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4161121"><span><span class="hlt">Optimism</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Carver, Charles S.; Scheier, Michael F.; Segerstrom, Suzanne C.</p> <p>2010-01-01</p> <p><span class="hlt">Optimism</span> is an individual difference variable that reflects the extent to which people hold generalized favorable expectancies for their future. Higher levels of <span class="hlt">optimism</span> have been related prospectively to better subjective well-being in times of adversity or difficulty (i.e., controlling for previous well-being). Consistent with such findings, <span class="hlt">optimism</span> has been linked to higher levels of engagement coping and lower levels of avoidance, or disengagement, coping. There is evidence that <span class="hlt">optimism</span> is associated with taking proactive steps to protect one's health, whereas pessimism is associated with health-damaging behaviors. Consistent with such findings, <span class="hlt">optimism</span> is also related to indicators of better physical health. The energetic, task-focused approach that optimists take to goals also relates to benefits in the socioeconomic world. Some evidence suggests that <span class="hlt">optimism</span> relates to more persistence in educational efforts and to higher later income. Optimists also appear to fare better than pessimists in relationships. Although there are instances in which <span class="hlt">optimism</span> fails to convey an advantage, and instances in which it may convey a disadvantage, those instances are relatively rare. In sum, the behavioral patterns of optimists appear to provide models of living for others to learn from. PMID:20170998</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AdWR...62...90M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AdWR...62...90M"><span><span class="hlt">Optimization</span> of stomatal conductance for maximum carbon gain under <span class="hlt">dynamic</span> soil moisture</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manzoni, Stefano; Vico, Giulia; Palmroth, Sari; Porporato, Amilcare; Katul, Gabriel</p> <p>2013-12-01</p> <p><span class="hlt">Optimization</span> theories explain a variety of forms and functions in plants. At the leaf scale, it is often hypothesized that carbon gain is maximized, thus providing a quantifiable objective for a mathematical definition of <span class="hlt">optimality</span> conditions. Eco-physiological trade-offs and limited resource availability introduce natural bounds to this <span class="hlt">optimization</span> process. In particular, carbon uptake from the atmosphere is inherently linked to water losses from the soil as water is taken up by roots and evaporated. Hence, water availability in soils constrains the amount of carbon that can be taken up and assimilated into new biomass. The problem of maximizing photosynthesis at a given water availability by modifying stomatal conductance, the plant-controlled variable to be <span class="hlt">optimized</span>, has been traditionally formulated for short time intervals over which soil moisture changes can be neglected. This simplification led to a mathematically open solution, where the undefined Lagrange multiplier of the <span class="hlt">optimization</span> (equivalent to the marginal water use efficiency, λ) is then heuristically determined via data fitting. Here, a set of models based on different assumptions that account for soil moisture <span class="hlt">dynamics</span> over an individual dry-down are proposed so as to provide closed analytical expressions for the carbon gain maximization problem. These novel solutions link the observed variability in λ over time, across soil moisture changes, and at different atmospheric CO2 concentrations to water use strategies ranging from intensive, in which all soil water is consumed by the end of the dry-down period, to more conservative, in which water stress is avoided by reducing transpiration.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/7034886','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/7034886"><span>Stochastic <span class="hlt">dynamic</span> <span class="hlt">optimization</span> approach for revegetation of reclaimed mine soils under uncertain weather regime</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Mustafa, G.</p> <p>1989-01-01</p> <p>This study presents a comprehensive physically based stochastic <span class="hlt">dynamic</span> <span class="hlt">optimization</span> model to assist planners in making decisions concerning mine soil depths and soil mixture ratios required to achieve successful revegetation of mine lands at different probability levels of success, subject to an uncertain weather regime. A perennial grass growth model was modified and validated for predicting vegetation growth in reclaimed mine soils. The plant growth model is based on continuous relationships between plant growth, air temperature, dry length, leaf area, photoperiod and plant-soil-moisture stresses. A plant available soil moisture model was adopted to estimate daily soil moisture for mine soils. A general probability model was developed to estimate the probability of successful revegetation in a 5-year bond release period. The probability model considers five possible bond release criteria in mine soil reclamation planning. A stochastic <span class="hlt">dynamic</span> <span class="hlt">optimization</span> model (SDOM) was developed to find the optimum combination of soil depth and soil mixture ratios that met the successful vegetation standard under non-irrigated conditions with weather as the only random element of the system. The SDOM was applied for Wise County, Virginia, and the model found that 2:1 sandstone/siltstone soil mixture required the minimum soil depth to achieve successful revegetation. These results were also supported by field data. The developed model allows the planners to better manage lands drastically disturbed by surface mining.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4215892','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4215892"><span>Fluid-<span class="hlt">Dynamic</span> <span class="hlt">Optimal</span> Design of Helical Vascular Graft for Stenotic Disturbed Flow</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Ha, Hojin; Hwang, Dongha; Choi, Woo-Rak; Baek, Jehyun; Lee, Sang Joon</p> <p>2014-01-01</p> <p>Although a helical configuration of a prosthetic vascular graft appears to be clinically beneficial in suppressing thrombosis and intimal hyperplasia, an <span class="hlt">optimization</span> of a helical design has yet to be achieved because of the lack of a detailed understanding on hemodynamic features in helical grafts and their fluid <span class="hlt">dynamic</span> influences. In the present study, the swirling flow in a helical graft was hypothesized to have beneficial influences on a disturbed flow structure such as stenotic flow. The characteristics of swirling flows generated by helical tubes with various helical pitches and curvatures were investigated to prove the hypothesis. The fluid <span class="hlt">dynamic</span> influences of these helical tubes on stenotic flow were quantitatively analysed by using a particle image velocimetry technique. Results showed that the swirling intensity and helicity of the swirling flow have a linear relation with a modified Germano number (Gn*) of the helical pipe. In addition, the swirling flow generated a beneficial flow structure at the stenosis by reducing the size of the recirculation flow under steady and pulsatile flow conditions. Therefore, the beneficial effects of a helical graft on the flow field can be estimated by using the magnitude of Gn*. Finally, an <span class="hlt">optimized</span> helical design with a maximum Gn* was suggested for the future design of a vascular graft. PMID:25360705</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008PhFl...20c5114B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008PhFl...20c5114B"><span>Development of a <span class="hlt">dynamic</span> model for the subfilter scalar variance using the concept of <span class="hlt">optimal</span> estimators</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Balarac, G.; Pitsch, H.; Raman, V.</p> <p>2008-03-01</p> <p>The concept of <span class="hlt">optimal</span> estimators, recently introduced by Moreau et al. [Phys. Fluids 18, 1 (2006)] is used as an a priori tool to discuss the accuracy of subfilter models. Placed in the framework of large-eddy simulation of combustion problems, this work focuses on the subfilter models used to evaluate the subfilter variance of a conserved scalar, the mixture fraction. The a priori tests are performed using 5123 direct numerical simulation data of forced homogeneous isotropic turbulence. First, the performance of the most commonly used models for the subfilter variance is studied. Using <span class="hlt">optimal</span> estimators, the Smagorinsky-type model [Pierce and Moin, Phys. Fluids 10, 3041 (1998)] is shown to have the best set of parameters. However, the conventional <span class="hlt">dynamic</span> formulation of the model leads to large errors in the variance prediction. It was found that assumptions used in the model formulation are not verified. A new <span class="hlt">dynamic</span> procedure based on a Taylor series expansion is then proposed to improve the predictive accuracy. The a priori tests show that the new model substantially improves predictive accuracy.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26891488','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26891488"><span>Stochastic <span class="hlt">Optimal</span> Regulation of Nonlinear Networked Control Systems by Using Event-Driven Adaptive <span class="hlt">Dynamic</span> Programming.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sahoo, Avimanyu; Jagannathan, Sarangapani</p> <p>2017-02-01</p> <p>In this paper, an event-driven stochastic adaptive <span class="hlt">dynamic</span> programming (ADP)-based technique is introduced for nonlinear systems with a communication network within its feedback loop. A near <span class="hlt">optimal</span> control policy is designed using an actor-critic framework and ADP with event sampled state vector. First, the system <span class="hlt">dynamics</span> are approximated by using a novel neural network (NN) identifier with event sampled state vector. The <span class="hlt">optimal</span> control policy is generated via an actor NN by using the NN identifier and value function approximated by a critic NN through ADP. The stochastic NN identifier, actor, and critic NN weights are tuned at the event sampled instants leading to aperiodic weight tuning laws. Above all, an adaptive event sampling condition based on estimated NN weights is designed by using the Lyapunov technique to ensure ultimate boundedness of all the closed-loop signals along with the approximation accuracy. The net result is event-driven stochastic ADP technique that can significantly reduce the computation and network transmissions. Finally, the analytical design is substantiated with simulation results.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1014686','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1014686"><span>Reduced-order model for <span class="hlt">dynamic</span> <span class="hlt">optimization</span> of pressure swing adsorption processes</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Agarwal, A.; Biegler, L.; Zitney, S.</p> <p>2007-01-01</p> <p>Over the past decades, pressure swing adsorption (PSA) processes have been widely used as energy-efficient gas and liquid separation techniques, especially for high purity hydrogen purification from refinery gases. The separation processes are based on solid-gas equilibrium and operate under periodic transient conditions. Models for PSA processes are therefore multiple instances of partial differential equations (PDEs) in time and space with periodic boundary conditions that link the processing steps together. The solution of this coupled stiff PDE system is governed by steep concentrations and temperature fronts moving with time. As a result, the <span class="hlt">optimization</span> of such systems for either design or operation represents a significant computational challenge to current differential algebraic equation (DAE) <span class="hlt">optimization</span> techniques and nonlinear programming algorithms. Model reduction is one approach to generate cost-efficient low-order models which can be used as surrogate models in the <span class="hlt">optimization</span> problems. The study develops a reduced-order model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a <span class="hlt">dynamic</span> PDE-based model. Initially, a representative ensemble of solutions of the <span class="hlt">dynamic</span> PDE system is constructed by solving a higher-order discretization of the model using the method of lines, a two-stage approach that discretizes the PDEs in space and then integrates the resulting DAEs over time. Next, the ROM method applies the Karhunen-Loeve expansion to derive a small set of empirical eigenfunctions (POD modes) which are used as basis functions within a Galerkin's projection framework to derive a low-order DAE system that accurately describes the dominant <span class="hlt">dynamics</span> of the PDE system. The proposed method leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization before and making <span class="hlt">optimization</span> problem computationally-efficient. The method has been applied to the <span class="hlt">dynamic</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010LNCS.6466..727P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010LNCS.6466..727P"><span>Particle Swarm <span class="hlt">Optimization</span> and Varying Chemotactic Step-Size Bacterial Foraging <span class="hlt">Optimization</span> Algorithms Based <span class="hlt">Dynamic</span> Economic Dispatch with Non-smooth Fuel Cost Functions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Praveena, P.; Vaisakh, K.; Rama Mohana Rao, S.</p> <p></p> <p>The <span class="hlt">Dynamic</span> economic dispatch (DED) problem is an <span class="hlt">optimization</span> problem with an objective to determine the <span class="hlt">optimal</span> combination of power outputs for all generating units over a certain period of time in order to minimize the total fuel cost while satisfying <span class="hlt">dynamic</span> operational constraints and load demand in each interval. Recently social foraging behavior of Escherichia coli bacteria has been explored to develop a novel algorithm for distributed <span class="hlt">optimization</span> and control. The Bacterial Foraging <span class="hlt">Optimization</span> Algorithm (BFOA) is currently gaining popularity in the community of researchers, for its effectiveness in solving certain difficult real-world <span class="hlt">optimization</span> problems. This article comes up with a hybrid approach involving Particle Swarm <span class="hlt">Optimization</span> (PSO) and BFO algorithms with varying chemo tactic step size for solving the DED problem of generating units considering valve-point effects. The proposed hybrid algorithm has been extensively compared with those methods reported in the literature. The new method is shown to be statistically significantly better on two test systems consisting of five and ten generating units.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JSV...344..416H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JSV...344..416H"><span>A parameters <span class="hlt">optimization</span> method for planar joint clearance model and its application for <span class="hlt">dynamics</span> simulation of reciprocating compressor</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li</p> <p>2015-05-01</p> <p>In order to improve the accuracy of <span class="hlt">dynamics</span> response simulation for mechanism with joint clearance, a parameter <span class="hlt">optimization</span> method for planar joint clearance contact force model was presented in this paper, and the <span class="hlt">optimized</span> parameters were applied to the <span class="hlt">dynamics</span> response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the <span class="hlt">dynamic</span> equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body <span class="hlt">dynamic</span> model built in ADAMS software was used to solve this equation. To obtain a simulated <span class="hlt">dynamic</span> response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were <span class="hlt">optimized</span> by genetic algorithms approach. Finally, the <span class="hlt">optimized</span> parameters were applied to simulate the <span class="hlt">dynamics</span> response of model with oversized joint clearance fault according to the concluded parameter relation. The <span class="hlt">dynamics</span> response of experimental test verified the effectiveness of this application.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012IEITI..95..374L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012IEITI..95..374L"><span>Date Flow <span class="hlt">Optimization</span> of <span class="hlt">Dynamically</span> Coarse Grain Reconfigurable Architecture for Multimedia Applications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Xinning; Mei, Chen; Cao, Peng; Zhu, Min; Shi, Longxing</p> <p></p> <p>This paper proposes a novel sub-architecture to <span class="hlt">optimize</span> the data flow of REMUS-II (REconfigurable MUltimedia System 2), a <span class="hlt">dynamically</span> coarse grain reconfigurable architecture. REMUS-II consists of a µPU (Micro-Processor Unit) and two RPUs (Reconfigurable Processor Unit), which are used to speeds up control-intensive tasks and data-intensive tasks respectively. The parallel computing capability and flexibility of REMUS-II makes itself an excellent candidate to process multimedia applications, which require a large amount of memory accesses. In this paper, we specifically <span class="hlt">optimize</span> the data flow to deal with those performance-hazard and energy-hungry memory accessing in order to meet the bandwidth requirement of parallel computing. The RPU internal memory could work in multiple modes, like 2D-access mode and transformation mode, according to different multimedia access patterns. This novel design can improve the performance up to 26% compared to traditional on-chip memory. Meanwhile, the block buffer is implemented to <span class="hlt">optimize</span> the off-chip data flow through reducing off-chip memory accesses, which reducing up to 43% compared to direct DDR access. Based on RTL simulation, REMUS-II can achieve 1080p@30fps of H.264 High Profile@ Level 4 and High Level MPEG2 at 200MHz clock frequency. The REMUS-II is implemented into 23.7mm2 silicon on TSMC 65nm logic process with a 400MHz maximum working frequency.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EnOp...45.1489A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EnOp...45.1489A"><span>Pareto archived <span class="hlt">dynamically</span> dimensioned search with hypervolume-based selection for multi-objective <span class="hlt">optimization</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Asadzadeh, Masoud; Tolson, Bryan</p> <p>2013-12-01</p> <p>Pareto archived <span class="hlt">dynamically</span> dimensioned search (PA-DDS) is a parsimonious multi-objective <span class="hlt">optimization</span> algorithm with only one parameter to diminish the user's effort for fine-tuning algorithm parameters. This study demonstrates that hypervolume contribution (HVC) is a very effective selection metric for PA-DDS and Monte Carlo sampling-based HVC is very effective for higher dimensional problems (five objectives in this study). PA-DDS with HVC performs comparably to algorithms commonly applied to water resources problems (ɛ-NSGAII and AMALGAM under recommended parameter values). Comparisons on the CEC09 competition show that with sufficient computational budget, PA-DDS with HVC performs comparably to 13 benchmark algorithms and shows improved relative performance as the number of objectives increases. Lastly, it is empirically demonstrated that the total <span class="hlt">optimization</span> runtime of PA-DDS with HVC is dominated (90% or higher) by solution evaluation runtime whenever evaluation exceeds 10 seconds/solution. Therefore, <span class="hlt">optimization</span> algorithm runtime associated with the unbounded archive of PA-DDS is negligible in solving computationally intensive problems.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19880000630','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19880000630"><span>Integration of <span class="hlt">dynamic</span>, aerodynamic and structural <span class="hlt">optimization</span> of helicopter rotor blades</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Peters, David A.</p> <p>1987-01-01</p> <p>The purpose of the research is to study the integration of structural, <span class="hlt">dynamic</span>, and aerodynamic considerations in the design-<span class="hlt">optimization</span> process for helicopter rotorblades. This is to be done in three phases. Task 1 is to bring on-line computer codes that could perform the finite-element frequency analyses of rotor blades. The major features of this program are summarized. The second task was to bring on-line an <span class="hlt">optimization</span> code for the work. Several were tried and it was decided to use CONMIN. Explicit volume constraints on the thicknesses and lumped masses used in the <span class="hlt">optimization</span> were added. The specific aeroelastic constraint that the center of mass must be forward of the quarter chord in order to prevent flutter was applied. The bending-torsion coupling due to cg-ea offset within the blade cross section was included. Also included were some very simple stress constraints. The first three constraints are completed, and the fourth constraint is being completed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19129037','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19129037"><span>Lattice <span class="hlt">dynamical</span> wavelet neural networks implemented using particle swarm <span class="hlt">optimization</span> for spatio-temporal system identification.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wei, Hua-Liang; Billings, Stephen A; Zhao, Yifan; Guo, Lingzhong</p> <p>2009-01-01</p> <p>In this brief, by combining an efficient wavelet representation with a coupled map lattice model, a new family of adaptive wavelet neural networks, called lattice <span class="hlt">dynamical</span> wavelet neural networks (LDWNNs), is introduced for spatio-temporal system identification. A new orthogonal projection pursuit (OPP) method, coupled with a particle swarm <span class="hlt">optimization</span> (PSO) algorithm, is proposed for augmenting the proposed network. A novel two-stage hybrid training scheme is developed for constructing a parsimonious network model. In the first stage, by applying the OPP algorithm, significant wavelet neurons are adaptively and successively recruited into the network, where adjustable parameters of the associated wavelet neurons are <span class="hlt">optimized</span> using a particle swarm <span class="hlt">optimizer</span>. The resultant network model, obtained in the first stage, however, may be redundant. In the second stage, an orthogonal least squares algorithm is then applied to refine and improve the initially trained network by removing redundant wavelet neurons from the network. An example for a real spatio-temporal system identification problem is presented to demonstrate the performance of the proposed new modeling framework.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016WRR....52.4151R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016WRR....52.4151R"><span>Using stochastic dual <span class="hlt">dynamic</span> programming in problems with multiple near-<span class="hlt">optimal</span> solutions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rougé, Charles; Tilmant, Amaury</p> <p>2016-05-01</p> <p>Stochastic dual <span class="hlt">dynamic</span> programming (SDDP) is one of the few algorithmic solutions available to <span class="hlt">optimize</span> large-scale water resources systems while explicitly considering uncertainty. This paper explores the consequences of, and proposes a solution to, the existence of multiple near-<span class="hlt">optimal</span> solutions (MNOS) when using SDDP for mid or long-term river basin management. These issues arise when the <span class="hlt">optimization</span> problem cannot be properly parametrized due to poorly defined and/or unavailable data sets. This work shows that when MNOS exists, (1) SDDP explores more than one solution trajectory in the same run, suggesting different decisions in distinct simulation years even for the same point in the state-space, and (2) SDDP is shown to be very sensitive to even minimal variations of the problem setting, e.g., initial conditions—we call this "algorithmic chaos." Results that exhibit such sensitivity are difficult to interpret. This work proposes a reoptimization method, which simulates system decisions by periodically applying cuts from one given year from the SDDP run. Simulation results obtained through this reoptimization approach are steady state solutions, meaning that their probability distributions are stable from year to year.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014OcDyn..64.1373L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014OcDyn..64.1373L"><span>Time-<span class="hlt">optimal</span> path planning in <span class="hlt">dynamic</span> flows using level set equations: theory and schemes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lolla, Tapovan; Lermusiaux, Pierre F. J.; Ueckermann, Mattheus P.; Haley, Patrick J.</p> <p>2014-10-01</p> <p>We develop an accurate partial differential equation-based methodology that predicts the time-<span class="hlt">optimal</span> paths of autonomous vehicles navigating in any continuous, strong, and <span class="hlt">dynamic</span> ocean currents, obviating the need for heuristics. The goal is to predict a sequence of steering directions so that vehicles can best utilize or avoid currents to minimize their travel time. Inspired by the level set method, we derive and demonstrate that a modified level set equation governs the time-<span class="hlt">optimal</span> path in any continuous flow. We show that our algorithm is computationally efficient and apply it to a number of experiments. First, we validate our approach through a simple benchmark application in a Rankine vortex flow for which an analytical solution is available. Next, we apply our methodology to more complex, simulated flow fields such as unsteady double-gyre flows driven by wind stress and flows behind a circular island. These examples show that time-<span class="hlt">optimal</span> paths for multiple vehicles can be planned even in the presence of complex flows in domains with obstacles. Finally, we present and support through illustrations several remarks that describe specific features of our methodology.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26895721','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26895721"><span>A <span class="hlt">dynamic</span> simulation/<span class="hlt">optimization</span> model for scheduling restoration of degraded military training lands.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Önal, Hayri; Woodford, Philip; Tweddale, Scott A; Westervelt, James D; Chen, Mengye; Dissanayake, Sahan T M; Pitois, Gauthier</p> <p>2016-04-15</p> <p>Intensive use of military vehicles on Department of Defense training installations causes deterioration in ground surface quality. Degraded lands restrict the scheduled training activities and jeopardize personnel and equipment safety. We present a simulation-<span class="hlt">optimization</span> approach and develop a discrete <span class="hlt">dynamic</span> <span class="hlt">optimization</span> model to determine an optimum land restoration for a given training schedule and availability of financial resources to minimize the adverse effects of training on military lands. The model considers weather forecasts, scheduled maneuver exercises, and unique qualities and importance of the maneuver areas. An application of this approach to Fort Riley, Kansas, shows that: i) starting with natural conditions, the total amount of training damages would increase almost linearly and exceed a quarter of the training area and 228 gullies would be formed (mostly in the intensive training areas) if no restoration is carried out over 10 years; ii) assuming an initial state that resembles the present conditions, sustaining the landscape requires an annual restoration budget of $957 thousand; iii) targeting a uniform distribution of maneuver damages would increase the total damages and adversely affect the overall landscape quality, therefore a selective restoration strategy may be preferred; and iv) a proactive restoration strategy would be <span class="hlt">optimal</span> where land degradations are repaired before they turn into more severe damages that are more expensive to repair and may pose a higher training risk. The last finding can be used as a rule-of-thumb for land restoration efforts in other installations with similar characteristics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4121257','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4121257"><span><span class="hlt">Dynamic</span> Response and <span class="hlt">Optimal</span> Design of Curved Metallic Sandwich Panels under Blast Loading</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Yang, Shu; Han, Shou-Hong; Lu, Zhen-Hua</p> <p>2014-01-01</p> <p>It is important to understand the effect of curvature on the blast response of curved structures so as to seek the <span class="hlt">optimal</span> configurations of such structures with improved blast resistance. In this study, the <span class="hlt">dynamic</span> response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA) steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a “soft” outer face and a “hard” inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD) and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA) and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN) metamodels, multiobjective <span class="hlt">optimization</span> designs of the panel were carried out. The <span class="hlt">optimization</span> results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances. PMID:25126606</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3421875','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3421875"><span><span class="hlt">Optimal</span> Control Strategies for Disinfection of Bacterial Populations with Persister and Susceptible <span class="hlt">Dynamics</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Brown, Jason; Darres, Kyle; Petty, Katherine</p> <p>2012-01-01</p> <p>It is increasingly clear that bacteria manage to evade killing by antibiotics and antimicrobials in a variety of ways, including mutation, phenotypic variations, and formation of biofilms. With recent advances in understanding the <span class="hlt">dynamics</span> of the tolerance mechanisms, there have been subsequent advances in understanding how to manipulate the bacterial environments to eradicate the bacteria. This study focuses on using mathematical techniques to find the <span class="hlt">optimal</span> disinfection strategy to eliminate the bacteria while managing the load of antibiotic that is applied. In this model, the bacterial population is separated into those that are tolerant to the antibiotic and those that are susceptible to disinfection. There are transitions between the two populations whose rates depend on the chemical environment. Our results extend previous mathematical studies to include more realistic methods of applying the disinfectant. The goal is to provide experimentally testable predictions that have been lacking in previous mathematical studies. In particular, we provide the <span class="hlt">optimal</span> disinfection protocol under a variety of assumptions within the model that can be used to validate or invalidate our simplifying assumptions and the experimental hypotheses that we used to develop the model. We find that constant dosing is not the <span class="hlt">optimal</span> method for disinfection. Rather, cycling between application and withdrawal of the antibiotic yields the fastest killing of the bacteria. PMID:22751538</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010638','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010638"><span>Adaptive Control for Linear Uncertain Systems with Unmodeled <span class="hlt">Dynamics</span> Revisited via <span class="hlt">Optimal</span> Control Modification</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nguyen, Nhan</p> <p>2013-01-01</p> <p>This paper presents the <span class="hlt">optimal</span> control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The <span class="hlt">optimal</span> control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled <span class="hlt">dynamics</span>. An analytical approach is developed to compute exactly the modification parameter for the <span class="hlt">optimal</span> control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011JChPh.134c4511R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011JChPh.134c4511R"><span>Resolution of strongly competitive product channels with <span class="hlt">optimal</span> <span class="hlt">dynamic</span> discrimination: Application to flavins</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roslund, Jonathan; Roth, Matthias; Guyon, Laurent; Boutou, Véronique; Courvoisier, Francois; Wolf, Jean-Pierre; Rabitz, Herschel</p> <p>2011-01-01</p> <p>Fundamental molecular selectivity limits are probed by exploiting laser-controlled quantum interferences for the creation of distinct spectral signatures in two flavin molecules, erstwhile nearly indistinguishable via steady-state methods. <span class="hlt">Optimal</span> <span class="hlt">dynamic</span> discrimination (ODD) uses <span class="hlt">optimally</span> shaped laser fields to transiently amplify minute molecular variations that would otherwise go unnoticed with linear absorption and fluorescence techniques. ODD is experimentally demonstrated by combining an <span class="hlt">optimally</span> shaped UV pump pulse with a time-delayed, fluorescence-depleting IR pulse for discrimination amongst riboflavin and flavin mononucleotide in aqueous solution, which are structurally and spectroscopically very similar. Closed-loop, adaptive pulse shaping discovers a set of UV pulses that induce disparate responses from the two flavins and allows for concomitant flavin discrimination of ˜16σ. Additionally, attainment of ODD permits quantitative, analytical detection of the individual constituents in a flavin mixture. The successful implementation of ODD on quantum systems of such high complexity bodes well for the future development of the field and the use of ODD techniques in a variety of demanding practical applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JPS...336..261D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JPS...336..261D"><span><span class="hlt">Optimization</span> of a new flow design for solid oxide cells using computational fluid <span class="hlt">dynamics</span> modelling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Duhn, Jakob Dragsbæk; Jensen, Anker Degn; Wedel, Stig; Wix, Christian</p> <p>2016-12-01</p> <p>Design of a gas distributor to distribute gas flow into parallel channels for Solid Oxide Cells (SOC) is <span class="hlt">optimized</span>, with respect to flow distribution, using Computational Fluid <span class="hlt">Dynamics</span> (CFD) modelling. The CFD model is based on a 3d geometric model and the <span class="hlt">optimized</span> structural parameters include the width of the channels in the gas distributor and the area in front of the parallel channels. The flow of the <span class="hlt">optimized</span> design is found to have a flow uniformity index value of 0.978. The effects of deviations from the assumptions used in the modelling (isothermal and non-reacting flow) are evaluated and it is found that a temperature gradient along the parallel channels does not affect the flow uniformity, whereas a temperature difference between the channels does. The impact of the flow distribution on the maximum obtainable conversion during operation is also investigated and the obtainable overall conversion is found to be directly proportional to the flow uniformity. Finally the effect of manufacturing errors is investigated. The design is shown to be robust towards deviations from design dimensions of at least ±0.1 mm which is well within obtainable tolerances.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25323319','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25323319"><span>On <span class="hlt">dynamically</span> generating relevant elementary flux modes in a metabolic network using <span class="hlt">optimization</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Oddsdóttir, Hildur Æsa; Hagrot, Erika; Chotteau, Véronique; Forsgren, Anders</p> <p>2015-10-01</p> <p>Elementary flux modes (EFMs) are pathways through a metabolic reaction network that connect external substrates to products. Using EFMs, a metabolic network can be transformed into its macroscopic counterpart, in which the internal metabolites have been eliminated and only external metabolites remain. In EFMs-based metabolic flux analysis (MFA) experimentally determined external fluxes are used to estimate the flux of each EFM. It is in general prohibitive to enumerate all EFMs for complex networks, since the number of EFMs increases rapidly with network complexity. In this work we present an <span class="hlt">optimization</span>-based method that <span class="hlt">dynamically</span> generates a subset of EFMs and solves the EFMs-based MFA problem simultaneously. The obtained subset contains EFMs that contribute to the <span class="hlt">optimal</span> solution of the EFMs-based MFA problem. The usefulness of our method was examined in a case-study using data from a Chinese hamster ovary cell culture and two networks of varied complexity. It was demonstrated that the EFMs-based MFA problem could be solved at a low computational cost, even for the more complex network. Additionally, only a fraction of the total number of EFMs was needed to compute the <span class="hlt">optimal</span> solution.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_22 --> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24808319','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24808319"><span>Stochastic <span class="hlt">optimal</span> controller design for uncertain nonlinear networked control system via neuro <span class="hlt">dynamic</span> programming.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Xu, Hao; Jagannathan, Sarangapani</p> <p>2013-03-01</p> <p>The stochastic <span class="hlt">optimal</span> controller design for the nonlinear networked control system (NNCS) with uncertain system <span class="hlt">dynamics</span> is a challenging problem due to the presence of both system nonlinearities and communication network imperfections, such as random delays and packet losses, which are not unknown a priori. In the recent literature, neuro <span class="hlt">dynamic</span> programming (NDP) techniques, based on value and policy iterations, have been widely reported to solve the <span class="hlt">optimal</span> control of general affine nonlinear systems. However, for realtime control, value and policy iterations-based methodology are not suitable and time-based NDP techniques are preferred. In addition, output feedback-based controller designs are preferred for implementation. Therefore, in this paper, a novel NNCS representation incorporating the system uncertainties and network imperfections is introduced first by using input and output measurements for facilitating output feedback. Then, an online neural network (NN) identifier is introduced to estimate the control coefficient matrix, which is subsequently utilized for the controller design. Subsequently, the critic and action NNs are employed along with the NN identifier to determine the forward-in-time, time-based stochastic <span class="hlt">optimal</span> control of NNCS without using value and policy iterations. Here, the value function and control inputs are updated once a sampling instant. By using novel NN weight update laws, Lyapunov theory is used to show that all the closed-loop signals and NN weights are uniformly ultimately bounded in the mean while the approximated control input converges close to its target value with time. Simulation results are included to show the effectiveness of the proposed scheme.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.S31C..07W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.S31C..07W"><span>Identifying active faults in Switzerland using relocated earthquake catalogs and <span class="hlt">optimal</span> anisotropic <span class="hlt">dynamic</span> clustering</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wagner, M.; Wang, Y.; Husen, S.; Woessner, J.; Kissling, E. H.; Ouillon, G.; Giardini, D.; Sornette, D.</p> <p>2010-12-01</p> <p>Active fault zones are the causal locations of most earthquakes, which release tectonic stresses. Yet, identification and association of faults and earthquakes is not straightforward. On the one hand, many earthquakes occur on faults that are unknown. On the other hand, systematic biases and uncertainties in earthquake locations hamper the association of earthquakes and known faults. We tackle the problem of linking earthquakes to faults by relocating them in a non-linear probabilistic manner and by applying a three-dimensional <span class="hlt">optimal</span> anisotropic <span class="hlt">dynamic</span> clustering approach to the relocated events to map fault networks. Non-linear probabilistic earthquake location allows to compute probability density functions that provide the complete probabilistic solution to the earthquake hypocenter location problem, including improved information on location uncertainties. To improve absolute earthquake locations we use a newly developed combined controlled-source seismology and local earthquake tomography model, which allows the use of secondary phases, such as PmP. <span class="hlt">Dynamic</span> clustering is a very general image processing technique that allows partitioning a set of data points. Our improved <span class="hlt">optimal</span> anisotropic <span class="hlt">dynamic</span> clustering technique accounts for uncertainties in earthquake locations by the use of probability density functions, as provided by non-linear probabilistic earthquake location. Hence, number and size of the reconstructed faults is controlled by earthquake location uncertainty. We apply our approach to seismicity in Switzerland to identify active faults in the region. Relocated earthquake catalogs and associated fault networks will be compared to already existing information on faults, such as geological and seismotectonic maps, to derive a more complete picture of active faulting in Switzerland.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/895073','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/895073"><span>DAKOTA, a multilevel parallel object-oriented framework for design <span class="hlt">optimization</span>, parameter estimation, uncertainty quantification, and sensitivity analysis:version 4.0 reference manual</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Griffin, Joshua D. (Sandai National Labs, Livermore, CA); Eldred, Michael Scott; Martinez-Canales, Monica L.; Watson, Jean-Paul; Kolda, Tamara Gibson; Adams, Brian M.; Swiler, Laura Painton; Williams, Pamela J.; Hough, Patricia Diane; Gay, David M.; Dunlavy, Daniel M.; Eddy, John P.; Hart, William Eugene; Guinta, Anthony A.; Brown, Shannon L.</p> <p>2006-10-01</p> <p>The DAKOTA (Design Analysis Kit for <span class="hlt">Optimization</span> and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for <span class="hlt">optimization</span> with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based <span class="hlt">optimization</span>, <span class="hlt">mixed</span> <span class="hlt">integer</span> nonlinear programming, or <span class="hlt">optimization</span> under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a reference manual for the commands specification for the DAKOTA software, providing input overviews, option descriptions, and example specifications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/991841','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/991841"><span>DAKOTA : a multilevel parallel object-oriented framework for design <span class="hlt">optimization</span>, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's reference manual.</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Eldred, Michael Scott; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Hough, Patricia Diane; Gay, David M.; Eddy, John P.; Haskell, Karen H.</p> <p>2010-05-01</p> <p>The DAKOTA (Design Analysis Kit for <span class="hlt">Optimization</span> and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for <span class="hlt">optimization</span> with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based <span class="hlt">optimization</span>, <span class="hlt">mixed</span> <span class="hlt">integer</span> nonlinear programming, or <span class="hlt">optimization</span> under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a reference manual for the commands specification for the DAKOTA software, providing input overviews, option descriptions, and example specifications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NatSR...631461C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NatSR...631461C"><span>Export <span class="hlt">dynamics</span> as an <span class="hlt">optimal</span> growth problem in the network of global economy</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Caraglio, Michele; Baldovin, Fulvio; Stella, Attilio L.</p> <p>2016-08-01</p> <p>We analyze export data aggregated at world global level of 219 classes of products over a period of 39 years. Our main goal is to set up a <span class="hlt">dynamical</span> model to identify and quantify plausible mechanisms by which the evolutions of the various exports affect each other. This is pursued through a stochastic differential description, partly inspired by approaches used in population <span class="hlt">dynamics</span> or directed polymers in random media. We outline a complex network of transfer rates which describes how resources are shifted between different product classes, and determines how casual favorable conditions for one export can spread to the other ones. A calibration procedure allows to fit four free model-parameters such that the <span class="hlt">dynamical</span> evolution becomes consistent with the average growth, the fluctuations, and the ranking of the export values observed in real data. Growth crucially depends on the balance between maintaining and shifting resources to different exports, like in an explore-exploit problem. Remarkably, the calibrated parameters warrant a close-to-maximum growth rate under the transient conditions realized in the period covered by data, implying an <span class="hlt">optimal</span> self organization of the global export. According to the model, major structural changes in the global economy take tens of years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27530505','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27530505"><span>Export <span class="hlt">dynamics</span> as an <span class="hlt">optimal</span> growth problem in the network of global economy.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Caraglio, Michele; Baldovin, Fulvio; Stella, Attilio L</p> <p>2016-08-17</p> <p>We analyze export data aggregated at world global level of 219 classes of products over a period of 39 years. Our main goal is to set up a <span class="hlt">dynamical</span> model to identify and quantify plausible mechanisms by which the evolutions of the various exports affect each other. This is pursued through a stochastic differential description, partly inspired by approaches used in population <span class="hlt">dynamics</span> or directed polymers in random media. We outline a complex network of transfer rates which describes how resources are shifted between different product classes, and determines how casual favorable conditions for one export can spread to the other ones. A calibration procedure allows to fit four free model-parameters such that the <span class="hlt">dynamical</span> evolution becomes consistent with the average growth, the fluctuations, and the ranking of the export values observed in real data. Growth crucially depends on the balance between maintaining and shifting resources to different exports, like in an explore-exploit problem. Remarkably, the calibrated parameters warrant a close-to-maximum growth rate under the transient conditions realized in the period covered by data, implying an <span class="hlt">optimal</span> self organization of the global export. According to the model, major structural changes in the global economy take tens of years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4987627','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4987627"><span>Export <span class="hlt">dynamics</span> as an <span class="hlt">optimal</span> growth problem in the network of global economy</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Caraglio, Michele; Baldovin, Fulvio; Stella, Attilio L.</p> <p>2016-01-01</p> <p>We analyze export data aggregated at world global level of 219 classes of products over a period of 39 years. Our main goal is to set up a <span class="hlt">dynamical</span> model to identify and quantify plausible mechanisms by which the evolutions of the various exports affect each other. This is pursued through a stochastic differential description, partly inspired by approaches used in population <span class="hlt">dynamics</span> or directed polymers in random media. We outline a complex network of transfer rates which describes how resources are shifted between different product classes, and determines how casual favorable conditions for one export can spread to the other ones. A calibration procedure allows to fit four free model-parameters such that the <span class="hlt">dynamical</span> evolution becomes consistent with the average growth, the fluctuations, and the ranking of the export values observed in real data. Growth crucially depends on the balance between maintaining and shifting resources to different exports, like in an explore-exploit problem. Remarkably, the calibrated parameters warrant a close-to-maximum growth rate under the transient conditions realized in the period covered by data, implying an <span class="hlt">optimal</span> self organization of the global export. According to the model, major structural changes in the global economy take tens of years. PMID:27530505</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2869351','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2869351"><span><span class="hlt">Optimal</span> Identification of Semi-Rigid Domains in Macromolecules from Molecular <span class="hlt">Dynamics</span> Simulation</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Bernhard, Stefan; Noé, Frank</p> <p>2010-01-01</p> <p>Biological function relies on the fact that biomolecules can switch between different conformations and aggregation states. Such transitions involve a rearrangement of parts of the biomolecules involved that act as <span class="hlt">dynamic</span> domains. The reliable identification of such domains is thus a key problem in biophysics. In this work we present a method to identify semi-rigid domains based on <span class="hlt">dynamical</span> data that can be obtained from molecular <span class="hlt">dynamics</span> simulations or experiments. To this end the average inter-atomic distance-deviations are computed. The resulting matrix is then clustered by a constrained quadratic <span class="hlt">optimization</span> problem. The reliability and performance of the method are demonstrated for two artificial peptides. Furthermore we correlate the mechanical properties with biological malfunction in three variants of amyloidogenic transthyretin protein, where the method reveals that a pathological mutation destabilizes the natural dimer structure of the protein. Finally the method is used to identify functional domains of the GroEL-GroES chaperone, thus illustrating the efficiency of the method for large biomolecular machines. PMID:20498702</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PhDT........21A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PhDT........21A"><span>Observability-Based Approach to Design, Analysis and <span class="hlt">Optimization</span> of <span class="hlt">Dynamical</span> Systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alaeddini, Atiye</p> <p></p> <p>The present dissertation aims to use the coupling between actuation and sensing in nonlinear systems to alternatively design a set of feasible control policies, to find the minimum number of sensors, or to find an <span class="hlt">optimal</span> sensors configuration. Feasibility, here, means a combination of sensory system and control policy which guarantees observability. In some cases the <span class="hlt">optimality</span> of the obtained solution is also considered. In some nonlinear systems, full observability requires active sensing, and will be shown how control policies that guarantee observability can be obtained by considering the geometry of the system <span class="hlt">dynamics</span>. The observability matrix is used to test observability, whereas for the <span class="hlt">optimization</span> problem observability Gramian matrix is used. This dissertation also considers the stability in designing controllers. The problem of designing a stabilizing control policy for a control-affine nonlinear system is addressed. The effect of time-varying control on the observability is investigated and shown to potentially improve the system observability. A particular application of the techniques considered here is the problem of designing network sensing and topology based on the observability criteria. The goal is to develop a protocol for the network which guarantees privacy. Furthermore, given a network of connected agents, we would like to determine which nodes should be observed to maximize information about the entire network. This dissertation begins with theoretical basis then moves towards applications of the theory. The first application is navigation of an autonomous ground robot with limited inertial sensing, motivated by the visuomotor system of insects. The second application is the problem of detecting an epidemic disease, which demonstrates design of an observability-based <span class="hlt">optimal</span> network.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PMB....58.8163S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PMB....58.8163S"><span>Trajectory <span class="hlt">optimization</span> for <span class="hlt">dynamic</span> couch rotation during volumetric modulated arc radiotherapy</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Smyth, Gregory; Bamber, Jeffrey C.; Evans, Philip M.; Bedford, James L.</p> <p>2013-11-01</p> <p>Non-coplanar radiation beams are often used in three-dimensional conformal and intensity modulated radiotherapy to reduce dose to organs at risk (OAR) by geometric avoidance. In volumetric modulated arc radiotherapy (VMAT) non-coplanar geometries are generally achieved by applying patient couch rotations to single or multiple full or partial arcs. This paper presents a trajectory <span class="hlt">optimization</span> method for a non-coplanar technique, <span class="hlt">dynamic</span> couch rotation during VMAT (DCR-VMAT), which combines ray tracing with a graph search algorithm. Four clinical test cases (partial breast, brain, prostate only, and prostate and pelvic nodes) were used to evaluate the potential OAR sparing for trajectory-<span class="hlt">optimized</span> DCR-VMAT plans, compared with standard coplanar VMAT. In each case, ray tracing was performed and a cost map reflecting the number of OAR voxels intersected for each potential source position was generated. The least-cost path through the cost map, corresponding to an <span class="hlt">optimal</span> DCR-VMAT trajectory, was determined using Dijkstra’s algorithm. Results show that trajectory <span class="hlt">optimization</span> can reduce dose to specified OARs for plans otherwise comparable to conventional coplanar VMAT techniques. For the partial breast case, the mean heart dose was reduced by 53%. In the brain case, the maximum lens doses were reduced by 61% (left) and 77% (right) and the globes by 37% (left) and 40% (right). Bowel mean dose was reduced by 15% in the prostate only case. For the prostate and pelvic nodes case, the bowel V50 Gy and V60 Gy were reduced by 9% and 45% respectively. Future work will involve further development of the algorithm and assessment of its performance over a larger number of cases in site-specific cohorts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JSV...351...43R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JSV...351...43R"><span>Passive vibration control in rotor <span class="hlt">dynamics</span>: <span class="hlt">Optimization</span> of composed support using viscoelastic materials</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ribeiro, Eduardo Afonso; Pereira, Jucélio Tomás; Alberto Bavastri, Carlos</p> <p>2015-09-01</p> <p>One of the major reasons for inserting damping into bearings is that rotating machines are often requested in critical functioning conditions having sometimes to function under <span class="hlt">dynamic</span> instability or close to critical speeds. Hydrodynamic and magnetic bearings have usually been used for this purpose, but they present limitations regarding costs and operation, rendering the use of viscoelastic supports a feasible solution for vibration control in rotating machines. Most papers in the area use simple analytic or single degree of freedom models for the rotor as well as classic mechanical models of linear viscoelasticity for the support - like Maxwell, Kelvin-Voigt, Zenner, four-element, GHM models and even frequency independent models - but they lack the accuracy of fractional models in a large range of frequency and temperature regarding the same number of coefficients. Even in those works, the need to consider the addition of degrees of freedom to the support is evident. However, so far no paper has been published focusing on a methodology to determine the <span class="hlt">optimal</span> constructive form for any viscoelastic support in which the rotor is discretized by finite elements associated to an accurate model for characterizing the viscoelastic material. In general, the support is meant to be a simple isolation system, and the fact the stiffness matrix is complex and frequency-temperature dependent - due to its viscoelastic properties - forces the traditional methods to require an extremely long computing time, thus rendering them too time consuming in an <span class="hlt">optimization</span> environment. The present work presents a robust methodology based mainly on generalized equivalent parameters (GEP) - for an <span class="hlt">optimal</span> design of viscoelastic supports for rotating machinery - aiming at minimizing the unbalance frequency response of the system using a hybrid <span class="hlt">optimization</span> technique (genetic algorithms and Nelder-Mead method). The rotor is modeled based on the finite element method using Timoshenko's thick</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009PhDT........50C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009PhDT........50C"><span><span class="hlt">Dynamic</span> simulation and <span class="hlt">optimal</span> real-time operation of CHP systems for buildings</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cho, Hee Jin</p> <p></p> <p>Combined Cooling, Heating, and Power (CHP) systems have been widely recognized as a key alternative for electric and thermal energy generation because of their outstanding energy efficiency, reduced environmental emissions, and relative independence from centralized power grids. The systems provide simultaneous onsite or near-site electric and thermal energy generation in a single, integrated package. As CHP becomes increasingly popular worldwide and its total capacity increases rapidly, the research on the topics of CHP performance assessment, design, and operational strategy become increasingly important. Following this trend of research activities to improve energy efficiency, environmental emissions, and operational cost, this dissertation focuses on the following aspects: (a) performance evaluation of a CHP system using a transient simulation model; (b) development of a <span class="hlt">dynamic</span> simulation model of a power generation unit that can be effectively used in transient simulations of CHP systems; (c) investigation of real-time operation of CHP systems based on <span class="hlt">optimization</span> with respect to operational cost, primary energy consumption, and carbon dioxide emissions; and (d) development of <span class="hlt">optimal</span> supervisory feed-forward control that can provide realistic real-time operation of CHP systems with electric and thermal energy storages using short-term weather forecasting. The results from a transient simulation of a CHP system show that technical and economical performance can be readily evaluated using the transient model and that the design, component selection, and control of a CHP system can be improved using this model. The results from the case studies using <span class="hlt">optimal</span> real-time operation strategies demonstrate that CHP systems with an energy dispatch algorithm have the potential to yield savings in operational cost, primary energy consumption, and carbon dioxide emissions with respect to a conventional HVAC system. Finally, the results from the case study using a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/17306310','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/17306310"><span>Chemotherapy for tumors: an analysis of the <span class="hlt">dynamics</span> and a study of quadratic and linear <span class="hlt">optimal</span> controls.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>de Pillis, L G; Gu, W; Fister, K R; Head, T; Maples, K; Murugan, A; Neal, T; Yoshida, K</p> <p>2007-09-01</p> <p>We investigate a mathematical model of tumor-immune interactions with chemotherapy, and strategies for <span class="hlt">optimally</span> administering treatment. In this paper we analyze the <span class="hlt">dynamics</span> of this model, characterize the <span class="hlt">optimal</span> controls related to drug therapy, and discuss numerical results of the <span class="hlt">optimal</span> strategies. The form of the model allows us to test and compare various <span class="hlt">optimal</span> control strategies, including a quadratic control, a linear control, and a state-constraint. We establish the existence of the <span class="hlt">optimal</span> control, and solve for the control in both the quadratic and linear case. In the linear control case, we show that we cannot rule out the possibility of a singular control. An interesting aspect of this paper is that we provide a graphical representation of regions on which the singular control is <span class="hlt">optimal</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3369909','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3369909"><span>Structural and <span class="hlt">Dynamic</span> Requirements for <span class="hlt">Optimal</span> Activity of the Essential Bacterial Enzyme Dihydrodipicolinate Synthase</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Reboul, C. F.; Porebski, B. T.; Griffin, M. D. W.; Dobson, R. C. J.; Perugini, M. A.; Gerrard, J. A.; Buckle, A. M.</p> <p>2012-01-01</p> <p>Dihydrodipicolinate synthase (DHDPS) is an essential enzyme involved in the lysine biosynthesis pathway. DHDPS from E. coli is a homotetramer consisting of a ‘dimer of dimers’, with the catalytic residues found at the tight-dimer interface. Crystallographic and biophysical evidence suggest that the dimers associate to stabilise the active site configuration, and mutation of a central dimer-dimer interface residue destabilises the tetramer, thus increasing the flexibility and reducing catalytic efficiency and substrate specificity. This has led to the hypothesis that the tetramer evolved to optimise the <span class="hlt">dynamics</span> within the tight-dimer. In order to gain insights into DHDPS flexibility and its relationship to quaternary structure and function, we performed comparative Molecular <span class="hlt">Dynamics</span> simulation studies of native tetrameric and dimeric forms of DHDPS from E. coli and also the native dimeric form from methicillin-resistant Staphylococcus aureus (MRSA). These reveal a striking contrast between the <span class="hlt">dynamics</span> of tetrameric and dimeric forms. Whereas the E. coli DHDPS tetramer is relatively rigid, both the E. coli and MRSA DHDPS dimers display high flexibility, resulting in monomer reorientation within the dimer and increased flexibility at the tight-dimer interface. The mutant E. coli DHDPS dimer exhibits disorder within its active site with deformation of critical catalytic residues and removal of key hydrogen bonds that render it inactive, whereas the similarly flexible MRSA DHDPS dimer maintains its catalytic geometry and is thus fully functional. Our data support the hypothesis that in both bacterial species <span class="hlt">optimal</span> activity is achieved by fine tuning protein <span class="hlt">dynamics</span> in different ways: E. coli DHDPS buttresses together two dimers, whereas MRSA dampens the motion using an extended tight-dimer interface. PMID:22685390</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012PhDT.......262K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012PhDT.......262K"><span>Combinatorial <span class="hlt">Optimization</span> Algorithms for <span class="hlt">Dynamic</span> Multiple Fault Diagnosis in Automotive and Aerospace Applications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kodali, Anuradha</p> <p></p> <p>In this thesis, we develop <span class="hlt">dynamic</span> multiple fault diagnosis (DMFD) algorithms to diagnose faults that are sporadic and coupled. Firstly, we formulate a coupled factorial hidden Markov model-based (CFHMM) framework to diagnose dependent faults occurring over time (<span class="hlt">dynamic</span> case). Here, we implement a mixed memory Markov coupling model to determine the most likely sequence of (dependent) fault states, the one that best explains the observed test outcomes over time. An iterative Gauss-Seidel coordinate ascent <span class="hlt">optimization</span> method is proposed for solving the problem. A soft Viterbi algorithm is also implemented within the framework for decoding dependent fault states over time. We demonstrate the algorithm on simulated and real-world systems with coupled faults; the results show that this approach improves the correct isolation rate as compared to the formulation where independent fault states are assumed. Secondly, we formulate a generalization of set-covering, termed <span class="hlt">dynamic</span> set-covering (DSC), which involves a series of coupled set-covering problems over time. The objective of the DSC problem is to infer the most probable time sequence of a parsimonious set of failure sources that explains the observed test outcomes over time. The DSC problem is NP-hard and intractable due to the fault-test dependency matrix that couples the failed tests and faults via the constraint matrix, and the temporal dependence of failure sources over time. Here, the DSC problem is motivated from the viewpoint of a <span class="hlt">dynamic</span> multiple fault diagnosis problem, but it has wide applications in operations research, for e.g., facility location problem. Thus, we also formulated the DSC problem in the context of a <span class="hlt">dynamically</span> evolving facility location problem. Here, a facility can be opened, closed, or can be temporarily unavailable at any time for a given requirement of demand points. These activities are associated with costs or penalties, viz., phase-in or phase-out for the opening or closing of a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JOM....67g1451Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JOM....67g1451Z"><span>Process <span class="hlt">Optimization</span> of Seed Precipitation Tank with Multiple Impellers Using Computational Fluid <span class="hlt">Dynamics</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Hong-Liang; Lv, Chao; Liu, Yan; Zhang, Ting-An</p> <p>2015-07-01</p> <p>The complex fluid flow in a large-scale tank stirred with multiple Ekato Intermig impellers used in the seed precipitation process was numerically analyzed by the computational fluid <span class="hlt">dynamics</span> method. The flow field, liquid-solid mixing, and power consumption were simulated by adopting the Eulerian granular multiphase model and standard k- ɛ turbulence model. A steady multiple reference frame approach was used to represent impeller rotation. The simulated results showed that the five-stage multiple Intermig impeller coupled with sloped baffles could generate circulation loops in axial, which is good for solid uniform mixing. The fluid is overmixed under the current industrial condition. Compared with the current process conditions, a three-stage impeller with L/ D of 1.25 not only could meet the industrial requirements, but also more than 20% power could be saved. The results have important implications for reliable design and <span class="hlt">optimal</span> performance for industry.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22528264','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22528264"><span><span class="hlt">Optimization</span> of the molecular <span class="hlt">dynamics</span> method for simulations of DNA and ion transport through biological nanopores.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wells, David B; Bhattacharya, Swati; Carr, Rogan; Maffeo, Christopher; Ho, Anthony; Comer, Jeffrey; Aksimentiev, Aleksei</p> <p>2012-01-01</p> <p>Molecular <span class="hlt">dynamics</span> (MD) simulations have become a standard method for the rational design and interpretation of experimental studies of DNA translocation through nanopores. The MD method, however, offers a multitude of algorithms, parameters, and other protocol choices that can affect the accuracy of the resulting data as well as computational efficiency. In this chapter, we examine the most popular choices offered by the MD method, seeking an <span class="hlt">optimal</span> set of parameters that enable the most computationally efficient and accurate simulations of DNA and ion transport through biological nanopores. In particular, we examine the influence of short-range cutoff, integration timestep and force field parameters on the temperature and concentration dependence of bulk ion conductivity, ion pairing, ion solvation energy, DNA structure, DNA-ion interactions, and the ionic current through a nanopore.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27125654','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27125654"><span>Model of Prey-Predator <span class="hlt">Dynamics</span> with Reflexive Spatial Behaviour of Species Based on <span class="hlt">Optimal</span> Migration.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sadovsky, Michael; Senashova, Mariya</p> <p>2016-04-01</p> <p>We consider the model of spatially distributed community consisting of two species with "predator-prey" interaction; each of the species occupies two stations. Transfer of individuals between the stations (migration) is not random, and migration stipulates the maximization of net reproduction of each species. The spatial distribution pattern is provided by discrete stations, and the <span class="hlt">dynamics</span> runs in discrete time. For each time moment, firstly a redistribution of individuals between the stations is carried out to maximize the net reproduction, and then the reproduction takes place, with the upgraded abundances. Besides, three versions of the basic model are implemented where each species implements reflexive behaviour strategy to determine the <span class="hlt">optimal</span> migration flow. It was found that reflexivity gives an advantage to the species realizing such strategy, for some specific sets of parameters. Nevertheless, the regular scanning of the parameters area shows that non-reflexive behaviour yields an advantage in the great majority of parameters combinations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012PhDT.......167W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012PhDT.......167W"><span>Sequentially <span class="hlt">Optimized</span> Meshfree Approximation as a New Computational Fluid <span class="hlt">Dynamics</span> Solver</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wilkinson, Matthew</p> <p></p> <p>This thesis presents the Sequentially <span class="hlt">Optimized</span> Meshfree Approximation (SOMA) method, a new and powerful Computational Fluid <span class="hlt">Dynamics</span> (CFD) solver. While standard computational methods can be faster and cheaper that physical experimentation, both in cost and work time, these methods do have some time and user interaction overhead which SOMA eliminates. As a meshfree method which could use adaptive domain refinement methods, SOMA avoids the need for user generated and/or analyzed grids, volumes, and meshes. Incremental building of a feed-forward artificial neural network through machine learning to solve the flow problem significantly reduces user interaction and reduces computational cost. This is done by avoiding the creation and inversion of possibly dense block diagonal matrices and by focusing computational work on regions where the flow changes and ignoring regions where no changes occur.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26512855','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26512855"><span>Hydrodynamic <span class="hlt">optimization</span> of membrane bioreactor by horizontal geometry modification using computational fluid <span class="hlt">dynamics</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Yan, Xiaoxu; Wu, Qing; Sun, Jianyu; Liang, Peng; Zhang, Xiaoyuan; Xiao, Kang; Huang, Xia</p> <p>2016-01-01</p> <p>Geometry property would affect the hydrodynamics of membrane bioreactor (MBR), which was directly related to membrane fouling rate. The simulation of a bench-scale MBR by computational fluid <span class="hlt">dynamics</span> (CFD) showed that the shear stress on membrane surface could be elevated by 74% if the membrane was sandwiched between two baffles (baffled MBR), compared with that without baffles (unbaffled MBR). The effects of horizontal geometry characteristics of a bench-scale membrane tank were discussed (riser length index Lr, downcomer length index Ld, tank width index Wt). Simulation results indicated that the average cross flow of the riser was negatively correlated to the ratio of riser and downcomer cross-sectional area. A relatively small tank width would also be preferable in promoting shear stress on membrane surface. The <span class="hlt">optimized</span> MBR had a shear elevation of 21.3-91.4% compared with unbaffled MBR under same aeration intensity.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_23 --> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AcAau.117..209B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AcAau.117..209B"><span>Rapid maneuvering of multi-body <span class="hlt">dynamic</span> systems with <span class="hlt">optimal</span> motion compensation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bishop, B.; Gargano, R.; Sears, A.; Karpenko, M.</p> <p>2015-12-01</p> <p>Rapid maneuvering of multi-body <span class="hlt">dynamical</span> systems is an important, yet challenging, problem in many applications. Even in the case of rigid bodies, it can be difficult to maintain precise control over nominally stationary links if it is required to move some of the other links quickly because of the various nonlinearities and coupled interactions that occur between the bodies. Typical control concepts treat the multi-body motion control problem in two-stages. First, the nonlinear and coupling terms are treated as disturbances and a trajectory tracking control law is designed in order to attenuate their effects. Next, motion profiles are designed, based on kinematics parameterizations, and these are used as inputs to the closed loop system to move the links. This paper describes an approach for rapid maneuvering of multi-body systems that uses <span class="hlt">optimal</span> control theory to account for <span class="hlt">dynamic</span> nonlinearities and coupling as part of the motion trajectory design. Incorporating appropriate operational constraints automatically compensates for these multi-body effects so that motion time can be reduced while simultaneously achieving other objectives such as reducing the excitation of selected links. Since the compensatory effect is embedded within the <span class="hlt">optimal</span> motion trajectories, the performance improvement can be obtained even when using simple closed-loop architectures for maneuver implementation. Simulation results for minimum time control of a two-axis gimbal system and for rapid maneuvering of a TDRS single-access antenna, wherein it is desired to limit the excitation of the satellite body to which the antenna is attached, are presented to illustrate the concepts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010cosp...38.3385H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010cosp...38.3385H"><span>Design and construction of miniature artificial ecosystem based on <span class="hlt">dynamic</span> response <span class="hlt">optimization</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hu, Dawei; Liu, Hong; Tong, Ling; Li, Ming; Hu, Enzhu</p> <p></p> <p>The miniature artificial ecosystem (MAES) is a combination of man, silkworm, salad and mi-croalgae to partially regenerate O2 , sanitary water and food, simultaneously dispose CO2 and wastes, therefore it have a fundamental life support function. In order to enhance the safety and reliability of MAES and eliminate the influences of internal variations and external dis-turbances, it was necessary to configure MAES as a closed-loop control system, and it could be considered as a prototype for future bioregenerative life support system. However, MAES is a complex system possessing large numbers of parameters, intricate nonlinearities, time-varying factors as well as uncertainties, hence it is difficult to perfectly design and construct a prototype through merely conducting experiments by trial and error method. Our research presented an effective way to resolve preceding problem by use of <span class="hlt">dynamic</span> response <span class="hlt">optimiza-tion</span>. Firstly the mathematical model of MAES with first-order nonlinear ordinary differential equations including parameters was developed based on relevant mechanisms and experimental data, secondly simulation model of MAES was derived on the platform of MatLab/Simulink to perform model validation and further digital simulations, thirdly reference trajectories of de-sired <span class="hlt">dynamic</span> response of system outputs were specified according to prescribed requirements, and finally <span class="hlt">optimization</span> for initial values, tuned parameter and independent parameters was carried out using the genetic algorithm, the advanced direct search method along with parallel computing methods through computer simulations. The result showed that all parameters and configurations of MAES were determined after a series of computer experiments, and its tran-sient response performances and steady characteristics closely matched the reference curves. Since the prototype is a physical system that represents the mathematical model with reason-able accuracy, so the process of designing and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26319376','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26319376"><span>Custom-tailored adsorbers: A molecular <span class="hlt">dynamics</span> study on <span class="hlt">optimal</span> design of ion exchange chromatography material.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lang, Katharina M H; Kittelmann, Jörg; Pilgram, Florian; Osberghaus, Anna; Hubbuch, Jürgen</p> <p>2015-09-25</p> <p>The performance of functionalized materials, e.g., ion exchange resins, depends on multiple resin characteristics, such as type of ligand, ligand density, the pore accessibility for a molecule, and backbone characteristics. Therefore, the screening and identification process for <span class="hlt">optimal</span> resin characteristics for separation is very time and material consuming. Previous studies on the influence of resin characteristics have focused on an experimental approach and to a lesser extent on the mechanistic understanding of the adsorption mechanism. In this in silico study, a previously developed molecular <span class="hlt">dynamics</span> (MD) tool is used, which simulates any given biomolecule on resins with varying ligand densities. We describe a set of simulations and experiments with four proteins and six resins varying in ligand density, and show that simulations and experiments correlate well in a wide range of ligand density. With this new approach simulations can be used as pre-experimental screening for <span class="hlt">optimal</span> adsorber characteristics, reducing the actual number of screening experiments, which results in a faster and more knowledge-based development of custom-tailored adsorbers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PhRvB..92f0301F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PhRvB..92f0301F"><span><span class="hlt">Optimizing</span> a <span class="hlt">dynamical</span> decoupling protocol for solid-state electronic spin ensembles in diamond</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Farfurnik, D.; Jarmola, A.; Pham, L. M.; Wang, Z. H.; Dobrovitski, V. V.; Walsworth, R. L.; Budker, D.; Bar-Gill, N.</p> <p>2015-08-01</p> <p>We demonstrate significant improvements of the spin coherence time of a dense ensemble of nitrogen-vacancy (NV) centers in diamond through <span class="hlt">optimized</span> <span class="hlt">dynamical</span> decoupling (DD). Cooling the sample down to 77 K suppresses longitudinal spin relaxation T1 effects and DD microwave pulses are used to increase the transverse coherence time T2 from ˜0.7 ms up to ˜30 ms . We extend previous work of single-axis (Carr-Purcell-Meiboom-Gill) DD towards the preservation of arbitrary spin states. Following a theoretical and experimental characterization of pulse and detuning errors, we compare the performance of various DD protocols. We identify that the <span class="hlt">optimal</span> control scheme for preserving an arbitrary spin state is a recursive protocol, the concatenated version of the XY8 pulse sequence. The improved spin coherence might have an immediate impact on improvements of the sensitivities of ac magnetometry. Moreover, the protocol can be used on denser diamond samples to increase coherence times up to NV-NV interaction time scales, a major step towards the creation of quantum collective NV spin states.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1227415','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1227415"><span><span class="hlt">Optimizing</span> a <span class="hlt">dynamical</span> decoupling protocol for solid-state electronic spin ensembles in diamond</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Farfurnik, D.; Jarmola, A.; Pham, L. M.; Wang, Z. H.; Dobrovitski, V. V.; Walsworth, R. L.; Budker, D.; Bar-Gill, N.</p> <p>2015-08-24</p> <p>In this study, we demonstrate significant improvements of the spin coherence time of a dense ensemble of nitrogen-vacancy (NV) centers in diamond through <span class="hlt">optimized</span> <span class="hlt">dynamical</span> decoupling (DD). Cooling the sample down to 77 K suppresses longitudinal spin relaxation T<sub>1</sub> effects and DD microwave pulses are used to increase the transverse coherence time T<sub>2</sub> from ~0.7ms up to ~30ms. Furthermore, we extend previous work of single-axis (Carr-Purcell-Meiboom-Gill) DD towards the preservation of arbitrary spin states. Following a theoretical and experimental characterization of pulse and detuning errors, we compare the performance of various DD protocols. We also identify that the <span class="hlt">optimal</span> control scheme for preserving an arbitrary spin state is a recursive protocol, the concatenated version of the XY8 pulse sequence. The improved spin coherence might have an immediate impact on improvements of the sensitivities of ac magnetometry. Moreover, the protocol can be used on denser diamond samples to increase coherence times up to NV-NV interaction time scales, a major step towards the creation of quantum collective NV spin states.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18303812','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18303812"><span><span class="hlt">Dynamic</span> stability of spine using stability-based <span class="hlt">optimization</span> and muscle spindle reflex.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zeinali-Davarani, Shahrokh; Hemami, Hooshang; Barin, Kamran; Shirazi-Adl, Aboulfazl; Parnianpour, Mohamad</p> <p>2008-02-01</p> <p>A computational method for simulation of 3-D movement of the trunk under the control of 48 anatomically oriented muscle actions was developed. Neural excitation of muscles was set based on inverse <span class="hlt">dynamics</span> approach along with the stability-based <span class="hlt">optimization</span>. The effect of muscle spindle reflex response on the trunk movement stability was evaluated upon the application of a perturbation moment. The method was used to simulate the trunk movement from the upright standing to 60 degrees of flexion. Incorporation of the stability condition as an additional constraint in the <span class="hlt">optimization</span> resulted in an increase in antagonistic activities demonstrating that the antagonistic co-activation acts to increase the trunk stability in response to self-induced postural internal perturbation. In presence of a 30 Nm flexion perturbation moment, muscle spindles decreased the induced deviation of the position and velocity profiles from the desired ones. The stability-generated co-activation decreased the reflexive response of muscle spindles to the perturbation demonstrating that the rise in muscle co-activation can ameliorate the corruption of afferent neural sensory system at the expense of higher loading of the spine.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008EnOp...40.1137V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008EnOp...40.1137V"><span>Implementation of an ANCF beam finite element for <span class="hlt">dynamic</span> response <span class="hlt">optimization</span> of elastic manipulators</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vohar, B.; Kegl, M.; Ren, Z.</p> <p>2008-12-01</p> <p>Theoretical and practical aspects of an absolute nodal coordinate formulation (ANCF) beam finite element implementation are considered in the context of <span class="hlt">dynamic</span> transient response <span class="hlt">optimization</span> of elastic manipulators. The proposed implementation is based on the introduction of new nodal degrees of freedom, which is achieved by an adequate nonlinear mapping between the original and new degrees of freedom. This approach preserves the mechanical properties of the ANCF beam, but converts it into a conventional finite element so that its nodal degrees of freedom are initially always equal to zero and never depend explicitly on the design variables. Consequently, the sensitivity analysis formulas can be derived in the usual manner, except that the introduced nonlinear mapping has to be taken into account. Moreover, the adjusted element can also be incorporated into general finite element analysis and <span class="hlt">optimization</span> software in the conventional way. The introduced design variables are related to the cross-section of the beam, to the shape of the (possibly) skeletal structure of the manipulator and to the drive functions. The layered cross-section approach and the design element technique are utilized to parameterize the shape of individual elements and the whole structure. A family of implicit time integration methods is adopted for the response and sensitivity analysis. Based on this assumption, the corresponding sensitivity formulas are derived. Two numerical examples illustrate the performance of the proposed element implementation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ChJOL..34..683S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ChJOL..34..683S"><span>Discussion of skill improvement in marine ecosystem <span class="hlt">dynamic</span> models based on parameter <span class="hlt">optimization</span> and skill assessment</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shen, Chengcheng; Shi, Honghua; Liu, Yongzhi; Li, Fen; Ding, Dewen</p> <p>2016-07-01</p> <p>Marine ecosystem <span class="hlt">dynamic</span> models (MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter <span class="hlt">optimization</span> (PO), which is an important step in model calibration. An efficient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the efficiency of model calibration by analyzing and estimating the goodness-of-fit of the <span class="hlt">optimized</span> model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confidence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientific and normative technical framework for the improvement of MEDM skill.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26552103','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26552103"><span>Value Iteration Adaptive <span class="hlt">Dynamic</span> Programming for <span class="hlt">Optimal</span> Control of Discrete-Time Nonlinear Systems.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wei, Qinglai; Liu, Derong; Lin, Hanquan</p> <p>2016-03-01</p> <p>In this paper, a value iteration adaptive <span class="hlt">dynamic</span> programming (ADP) algorithm is developed to solve infinite horizon undiscounted <span class="hlt">optimal</span> control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the <span class="hlt">optimal</span> performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1227415-optimizing-dynamical-decoupling-protocol-solid-state-electronic-spin-ensembles-diamond','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1227415-optimizing-dynamical-decoupling-protocol-solid-state-electronic-spin-ensembles-diamond"><span><span class="hlt">Optimizing</span> a <span class="hlt">dynamical</span> decoupling protocol for solid-state electronic spin ensembles in diamond</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Farfurnik, D.; Jarmola, A.; Pham, L. M.; ...</p> <p>2015-08-24</p> <p>In this study, we demonstrate significant improvements of the spin coherence time of a dense ensemble of nitrogen-vacancy (NV) centers in diamond through <span class="hlt">optimized</span> <span class="hlt">dynamical</span> decoupling (DD). Cooling the sample down to 77 K suppresses longitudinal spin relaxation T1 effects and DD microwave pulses are used to increase the transverse coherence time T2 from ~0.7ms up to ~30ms. Furthermore, we extend previous work of single-axis (Carr-Purcell-Meiboom-Gill) DD towards the preservation of arbitrary spin states. Following a theoretical and experimental characterization of pulse and detuning errors, we compare the performance of various DD protocols. We also identify that the <span class="hlt">optimal</span> controlmore » scheme for preserving an arbitrary spin state is a recursive protocol, the concatenated version of the XY8 pulse sequence. The improved spin coherence might have an immediate impact on improvements of the sensitivities of ac magnetometry. Moreover, the protocol can be used on denser diamond samples to increase coherence times up to NV-NV interaction time scales, a major step towards the creation of quantum collective NV spin states.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017813','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017813"><span>Applying <span class="hlt">Dynamical</span> Systems Theory to <span class="hlt">Optimize</span> Libration Point Orbit Stationkeeping Maneuvers for WIND</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Brown, Jonathan M.; Petersen, Jeremy D.</p> <p>2014-01-01</p> <p>NASA's WIND mission has been operating in a large amplitude Lissajous orbit in the vicinity of the interior libration point of the Sun-Earth/Moon system since 2004. Regular stationkeeping maneuvers are required to maintain the orbit due to the instability around the collinear libration points. Historically these stationkeeping maneuvers have been performed by applying an incremental change in velocity, or (delta)v along the spacecraft-Sun vector as projected into the ecliptic plane. Previous studies have shown that the magnitude of libration point stationkeeping maneuvers can be minimized by applying the (delta)v in the direction of the local stable manifold found using <span class="hlt">dynamical</span> systems theory. This paper presents the analysis of this new maneuver strategy which shows that the magnitude of stationkeeping maneuvers can be decreased by 5 to 25 percent, depending on the location in the orbit where the maneuver is performed. The implementation of the <span class="hlt">optimized</span> maneuver method into operations is discussed and results are presented for the first two <span class="hlt">optimized</span> stationkeeping maneuvers executed by WIND.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJT....37..115B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJT....37..115B"><span>Determination of the <span class="hlt">Optimal</span> Fourier Number on the <span class="hlt">Dynamic</span> Thermal Transmission</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bruzgevičius, P.; Burlingis, A.; Norvaišienė, R.</p> <p>2016-12-01</p> <p>This article represents the result of experimental research on transient heat transfer in a multilayered (heterogeneous) wall. Our non-steady thermal transmission simulation is based on a finite-difference calculation method. The value of a Fourier number shows the similarity of thermal variation in conditional layers of an enclosure. Most scientists recommend using no more than a value of 0.5 for the Fourier number when performing calculations on <span class="hlt">dynamic</span> (transient) heat transfer. The value of the Fourier number is determined in order to acquire reliable calculation results with <span class="hlt">optimal</span> accuracy. To compare the results of simulation with experimental research, a transient heat transfer calculation spreadsheet was created. Our research has shown that a Fourier number of around 0.5 or even 0.32 is not sufficient ({≈ }17 % of oscillation amplitude) for calculations of transient heat transfer in a multilayered wall. The least distorted calculation results were obtained when the multilayered enclosure was divided into conditional layers with almost equal Fourier number values and when the value of the Fourier number was around 1/6, i.e., approximately 0.17. Statistical deviation analysis using the Statistical Analysis System was applied to assess the accuracy of the spreadsheet calculation and was developed on the basis of our established methodology. The mean and median absolute error as well as their confidence intervals has been estimated by the two methods with <span class="hlt">optimal</span> accuracy ({F}_{oMDF}= 0.177 and F_{oEPS}= 0.1633 values).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9900E..0NF','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9900E..0NF"><span>Improving the coherence properties of solid-state spin ensembles via <span class="hlt">optimized</span> <span class="hlt">dynamical</span> decoupling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Farfurnik, D.; Jarmola, A.; Pham, L. M.; Wang, Z. H.; Dobrovitski, V. V.; Walsworth, R. L.; Budker, D.; Bar-Gill, N.</p> <p>2016-04-01</p> <p>In this work, we <span class="hlt">optimize</span> a <span class="hlt">dynamical</span> decoupling (DD) protocol to improve the spin coherence properties of a dense ensemble of nitrogen-vacancy (NV) centers in diamond. Using liquid nitrogen-based cooling and DD microwave pulses, we increase the transverse coherence time T2 from ˜ 0.7 ms up to ˜ 30 ms. We extend previous work of single-axis (Carr-Purcell-Meiboom-Gill) DD towards the preservation of arbitrary spin states. After performing a detailed analysis of pulse and detuning errors, we compare the performance of various DD protocols. We identify that the concatenated XY8 pulse sequences serves as the <span class="hlt">optimal</span> control scheme for preserving an arbitrary spin state. Finally, we use the concatenated sequences to demonstrate an immediate improvement of the AC magnetic sensitivity up to a factor of two at 250 kHz. For future work, similar protocols may be used to increase coherence times up to NV-NV interaction time scales, a major step toward the creation of quantum collective NV spin states.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27598161','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27598161"><span><span class="hlt">Dynamic</span> Aberration Correction for Conformal Window of High-Speed Aircraft Using <span class="hlt">Optimized</span> Model-Based Wavefront Sensorless Adaptive Optics.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Dong, Bing; Li, Yan; Han, Xin-Li; Hu, Bin</p> <p>2016-09-02</p> <p>For high-speed aircraft, a conformal window is used to <span class="hlt">optimize</span> the aerodynamic performance. However, the local shape of the conformal window leads to large amounts of <span class="hlt">dynamic</span> aberrations varying with look angle. In this paper, deformable mirror (DM) and model-based wavefront sensorless adaptive optics (WSLAO) are used for <span class="hlt">dynamic</span> aberration correction of an infrared remote sensor equipped with a conformal window and scanning mirror. In model-based WSLAO, aberration is captured using Lukosz mode, and we use the low spatial frequency content of the image spectral density as the metric function. Simulations show that aberrations induced by the conformal window are dominated by some low-order Lukosz modes. To <span class="hlt">optimize</span> the <span class="hlt">dynamic</span> correction, we can only correct dominant Lukosz modes and the image size can be minimized to reduce the time required to compute the metric function. In our experiment, a 37-channel DM is used to mimic the <span class="hlt">dynamic</span> aberration of conformal window with scanning rate of 10 degrees per second. A 52-channel DM is used for correction. For a 128 × 128 image, the mean value of image sharpness during <span class="hlt">dynamic</span> correction is 1.436 × 10(-5) in <span class="hlt">optimized</span> correction and is 1.427 × 10(-5) in un-<span class="hlt">optimized</span> correction. We also demonstrated that model-based WSLAO can achieve convergence two times faster than traditional stochastic parallel gradient descent (SPGD) method.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5038692','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5038692"><span><span class="hlt">Dynamic</span> Aberration Correction for Conformal Window of High-Speed Aircraft Using <span class="hlt">Optimized</span> Model-Based Wavefront Sensorless Adaptive Optics</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Dong, Bing; Li, Yan; Han, Xin-li; Hu, Bin</p> <p>2016-01-01</p> <p>For high-speed aircraft, a conformal window is used to <span class="hlt">optimize</span> the aerodynamic performance. However, the local shape of the conformal window leads to large amounts of <span class="hlt">dynamic</span> aberrations varying with look angle. In this paper, deformable mirror (DM) and model-based wavefront sensorless adaptive optics (WSLAO) are used for <span class="hlt">dynamic</span> aberration correction of an infrared remote sensor equipped with a conformal window and scanning mirror. In model-based WSLAO, aberration is captured using Lukosz mode, and we use the low spatial frequency content of the image spectral density as the metric function. Simulations show that aberrations induced by the conformal window are dominated by some low-order Lukosz modes. To <span class="hlt">optimize</span> the <span class="hlt">dynamic</span> correction, we can only correct dominant Lukosz modes and the image size can be minimized to reduce the time required to compute the metric function. In our experiment, a 37-channel DM is used to mimic the <span class="hlt">dynamic</span> aberration of conformal window with scanning rate of 10 degrees per second. A 52-channel DM is used for correction. For a 128 × 128 image, the mean value of image sharpness during <span class="hlt">dynamic</span> correction is 1.436 × 10−5 in <span class="hlt">optimized</span> correction and is 1.427 × 10−5 in un-<span class="hlt">optimized</span> correction. We also demonstrated that model-based WSLAO can achieve convergence two times faster than traditional stochastic parallel gradient descent (SPGD) method. PMID:27598161</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005SPIE.5892...52L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005SPIE.5892...52L"><span><span class="hlt">Optimizing</span> performance of hybrid FSO/RF networks in realistic <span class="hlt">dynamic</span> scenarios</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Llorca, Jaime; Desai, Aniket; Baskaran, Eswaran; Milner, Stuart; Davis, Christopher</p> <p>2005-08-01</p> <p>Hybrid Free Space Optical (FSO) and Radio Frequency (RF) networks promise highly available wireless broadband connectivity and quality of service (QoS), particularly suitable for emerging network applications involving extremely high data rate transmissions such as high quality video-on-demand and real-time surveillance. FSO links are prone to atmospheric obscuration (fog, clouds, snow, etc) and are difficult to align over long distances due the use of narrow laser beams and the effect of atmospheric turbulence. These problems can be mitigated by using adjunct directional RF links, which provide backup connectivity. In this paper, methodologies for modeling and simulation of hybrid FSO/RF networks are described. Individual link propagation models are derived using scattering theory, as well as experimental measurements. MATLAB is used to generate realistic atmospheric obscuration scenarios, including moving cloud layers at different altitudes. These scenarios are then imported into a network simulator (OPNET) to emulate mobile hybrid FSO/RF networks. This framework allows accurate analysis of the effects of node mobility, atmospheric obscuration and traffic demands on network performance, and precise evaluation of topology reconfiguration algorithms as they react to <span class="hlt">dynamic</span> changes in the network. Results show how topology reconfiguration algorithms, together with enhancements to TCP/IP protocols which reduce the network response time, enable the network to rapidly detect and act upon link state changes in highly <span class="hlt">dynamic</span> environments, ensuring <span class="hlt">optimized</span> network performance and availability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhDT........17S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhDT........17S"><span>Multidisciplinary <span class="hlt">optimization</span> for the design and control of uncertain <span class="hlt">dynamical</span> systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sridharan, Srikanth</p> <p></p> <p>This dissertation considers an integrated approach to system design and controller design based on analyzing limits of system performance. Historically, plant design methodologies have not incorporated control relevant considerations. Such an approach could result in a system that might not meet its specifications (or one that requires a complex control architecture to do so). System and controller designers often go through several iterations in order to converge to an acceptable plant and controller design. The focus of this dissertation is on the design and control an air-breathing hypersonic vehicle using such an integrated system-control design framework. The goal is to reduce the number of system-control design iterations (by explicitly incorporate control considerations in the system design process), as well as to influence the guidance/trajectory specifications for the system. Due to the high computational costs associated with obtaining a <span class="hlt">dynamic</span> model for each plant configuration considered, approximations to the system <span class="hlt">dynamics</span> are used in the control design process. By formulating the control design problem using bilinear and polynomial matrix inequalities, several common control and system design constraints can be simultaneously incorporated into a vehicle design <span class="hlt">optimization</span>. Several design problems are examined to illustrate the effectiveness of this approach (and to compare the computational burden of this methodology against more traditional approaches).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27493445','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27493445"><span>A Multi-Cycle Q-Modulation for <span class="hlt">Dynamic</span> <span class="hlt">Optimization</span> of Inductive Links.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lee, Byunghun; Yeon, Pyungwoo; Ghovanloo, Maysam</p> <p>2016-08-01</p> <p>This paper presents a new method, called multi-cycle Q-modulation, which can be used in wireless power transmission (WPT) to modulate the quality factor (Q) of the receiver (Rx) coil and <span class="hlt">dynamically</span> <span class="hlt">optimize</span> the load impedance to maximize the power transfer efficiency (PTE) in two-coil links. A key advantage of the proposed method is that it can be easily implemented using off-the-shelf components without requiring fast switching at or above the carrier frequency, which is more suitable for integrated circuit design. Moreover, the proposed technique does not need any sophisticated synchronization between the power carrier and Q-modulation switching pulses. The multi-cycle Q-modulation is analyzed theoretically by a lumped circuit model, and verified in simulation and measurement using an off-the-shelf prototype. Automatic resonance tuning (ART) in the Rx, combined with multi-cycle Q-modulation helped maximizing PTE of the inductive link <span class="hlt">dynamically</span> in the presence of environmental and loading variations, which can otherwise significantly degrade the PTE in multi-coil settings. In the prototype conventional 2-coil link, the proposed method increased the power amplifier (PA) plus inductive link efficiency from 4.8% to 16.5% at (RL = 1 kΩ, d23 = 3 cm), and from 23% to 28.2% at (RL = 100 Ω, d23 = 3 cm) after 11% change in the resonance capacitance, while delivering 168.1 mW to the load (PDL).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007EnGeo..51..953U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007EnGeo..51..953U"><span>A <span class="hlt">dynamic</span> programming model for <span class="hlt">optimal</span> planning of aquifer storage and recovery facility operations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Uddameri, V.</p> <p>2007-01-01</p> <p>Aquifer storage recovery (ASR) is an innovative technology with the potential to augment dwindling water resources in regions experiencing rapid growth and development. Planning and design of ASR systems requires quantifying how much water should be stored and appropriate times for storage and withdrawals within a planning period. A monthly scale planning model has been developed in this study to derive <span class="hlt">optimal</span> (least cost) long-term policies for operating ASR systems and is solved using a recursive deterministic <span class="hlt">dynamic</span> programming approach. The outputs of the model include annual costs of operation, the amount of water to be imported each month as well as the schedule for storage and extraction. A case study modeled after a proposed ASR system for Mustang Island and Padre Island service areas of the city of Corpus Christi is used to illustrate the utility of the developed model. The results indicate that for the assumed baseline demands, the ASR system is to be kept operational for a period of 4 months starting from May through August. Model sensitivity analysis indicated that increased seasonal shortages can be met using ASR with little additional costs. For the assumed cost structure, a 16% shortage increased the costs by 1.6%. However, the operation time of ASR increased from 4 to 8 months. The developed <span class="hlt">dynamic</span> programming model is a useful tool to assess the feasibility of evaluating the use of ASR systems during regional-scale water resources planning endeavors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009SPIE.7437E..0EC','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009SPIE.7437E..0EC"><span><span class="hlt">Optimization</span> of detectors positioning with respect to flying <span class="hlt">dynamics</span> for future formation flight missions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Civitani, Marta; Djalal, Sophie; Chipaux, Remi</p> <p>2009-08-01</p> <p>In a X-ray telescope in formation flight configuration, the optics and the focal-plane detectors reside in two different spacecraft. The <span class="hlt">dynamics</span> of the detector spacecraft (DSC) with respect to the mirror spacecraft (MSC, carrying the mirrors of the telescope) changes continuously the arrival positions of the photons on the detectors. In this paper we analyze this issue for the case of the SIMBOL-X hard X-ray mission, extensively studied by CNES and ASI until 2009 spring. Due to the existing gaps between pixels and between detector modules, the <span class="hlt">dynamics</span> of the system may produce a relevant photometric effect. The aim of this work is to present the <span class="hlt">optimization</span> study of the control-law algorithm with respect to the detector's geometry. As the photometric effect may vary depending upon position of the source image on the detector, the analysis-carried out using the simuLOS (INAF, CNES, CEA) simulation tool-is extended over the entire SIMBOL-X field of view.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_24 --> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26011881','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26011881"><span>High <span class="hlt">dynamic</span> range image compression by <span class="hlt">optimizing</span> tone mapped image quality index.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ma, Kede; Yeganeh, Hojatollah; Zeng, Kai; Wang, Zhou</p> <p>2015-10-01</p> <p>Tone mapping operators (TMOs) aim to compress high <span class="hlt">dynamic</span> range (HDR) images to low <span class="hlt">dynamic</span> range (LDR) ones so as to visualize HDR images on standard displays. Most existing TMOs were demonstrated on specific examples without being thoroughly evaluated using well-designed and subject-validated image quality assessment models. A recently proposed tone mapped image quality index (TMQI) made one of the first attempts on objective quality assessment of tone mapped images. Here, we propose a substantially different approach to design TMO. Instead of using any predefined systematic computational structure for tone mapping (such as analytic image transformations and/or explicit contrast/edge enhancement), we directly navigate in the space of all images, searching for the image that <span class="hlt">optimizes</span> an improved TMQI. In particular, we first improve the two building blocks in TMQI—structural fidelity and statistical naturalness components—leading to a TMQI-II metric. We then propose an iterative algorithm that alternatively improves the structural fidelity and statistical naturalness of the resulting image. Numerical and subjective experiments demonstrate that the proposed algorithm consistently produces better quality tone mapped images even when the initial images of the iteration are created by the most competitive TMOs. Meanwhile, these results also validate the superiority of TMQI-II over TMQI.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25530750','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25530750"><span>Study of the bus <span class="hlt">dynamic</span> coscheduling <span class="hlt">optimization</span> method under urban rail transit line emergency.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wang, Yun; Yan, Xuedong; Zhou, Yu; Wang, Jiaxi; Chen, Shasha</p> <p>2014-01-01</p> <p>As one of the most important urban commuter transportation modes, urban rail transit (URT) has been acting as a key solution for supporting mobility needs in high-density urban areas. However, in recent years, high frequency of unexpected events has caused serious service disruptions in URT system, greatly harming passenger safety and resulting in severe traffic delays. Therefore, there is an urgent need to study emergency evacuation problem in URT. In this paper, a method of bus <span class="hlt">dynamic</span> coscheduling is proposed and two models are built based on different evacuation destinations including URT stations and surrounding bus parking spots. A <span class="hlt">dynamic</span> coscheduling scheme for buses can be obtained by the models. In the model solution process, a new concept-the equivalent parking spot-is proposed to transform the nonlinear model into an integer linear programming (ILP) problem. A case study is conducted to verify the feasibility of models. Also, sensitivity analysis of two vital factors is carried out to analyze their effects on the total evacuation time. The results reveal that the designed capacity of buses has a negative influence on the total evacuation time, while an increase in the number of passengers has a positive effect. Finally, some significant <span class="hlt">optimizing</span> strategies are proposed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4235110','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4235110"><span>Study of the Bus <span class="hlt">Dynamic</span> Coscheduling <span class="hlt">Optimization</span> Method under Urban Rail Transit Line Emergency</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Yan, Xuedong; Wang, Jiaxi; Chen, Shasha</p> <p>2014-01-01</p> <p>As one of the most important urban commuter transportation modes, urban rail transit (URT) has been acting as a key solution for supporting mobility needs in high-density urban areas. However, in recent years, high frequency of unexpected events has caused serious service disruptions in URT system, greatly harming passenger safety and resulting in severe traffic delays. Therefore, there is an urgent need to study emergency evacuation problem in URT. In this paper, a method of bus <span class="hlt">dynamic</span> coscheduling is proposed and two models are built based on different evacuation destinations including URT stations and surrounding bus parking spots. A <span class="hlt">dynamic</span> coscheduling scheme for buses can be obtained by the models. In the model solution process, a new concept—the equivalent parking spot—is proposed to transform the nonlinear model into an integer linear programming (ILP) problem. A case study is conducted to verify the feasibility of models. Also, sensitivity analysis of two vital factors is carried out to analyze their effects on the total evacuation time. The results reveal that the designed capacity of buses has a negative influence on the total evacuation time, while an increase in the number of passengers has a positive effect. Finally, some significant <span class="hlt">optimizing</span> strategies are proposed. PMID:25530750</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AdWR...67....1L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AdWR...67....1L"><span>A parallel <span class="hlt">dynamic</span> programming algorithm for multi-reservoir system <span class="hlt">optimization</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Xiang; Wei, Jiahua; Li, Tiejian; Wang, Guangqian; Yeh, William W.-G.</p> <p>2014-05-01</p> <p>This paper develops a parallel <span class="hlt">dynamic</span> programming algorithm to <span class="hlt">optimize</span> the joint operation of a multi-reservoir system. First, a multi-dimensional <span class="hlt">dynamic</span> programming (DP) model is formulated for a multi-reservoir system. Second, the DP algorithm is parallelized using a peer-to-peer parallel paradigm. The parallelization is based on the distributed memory architecture and the message passing interface (MPI) protocol. We consider both the distributed computing and distributed computer memory in the parallelization. The parallel paradigm aims at reducing the computation time as well as alleviating the computer memory requirement associated with running a multi-dimensional DP model. Next, we test the parallel DP algorithm on the classic, benchmark four-reservoir problem on a high-performance computing (HPC) system with up to 350 cores. Results indicate that the parallel DP algorithm exhibits good performance in parallel efficiency; the parallel DP algorithm is scalable and will not be restricted by the number of cores. Finally, the parallel DP algorithm is applied to a real-world, five-reservoir system in China. The results demonstrate the parallel efficiency and practical utility of the proposed methodology.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009PMB....54..285B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009PMB....54..285B"><span>A pseudo-<span class="hlt">dynamic</span> sub-<span class="hlt">optimal</span> filter for elastography under static loading and measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Banerjee, B.; Roy, D.; Vasu, R. M.</p> <p>2009-01-01</p> <p>We propose a pseudo-<span class="hlt">dynamic</span> form of a sub-<span class="hlt">optimal</span> Kalman filter for elastography of plane-strain models of soft tissues under strictly static deformations and partial measurements. Since the tissue material is nearly incompressible and is thus prone to volumetric locking via standard displacement-based finite element formulations, we use a Cosserat point approach for deriving the static equilibrium equations. A pseudo-<span class="hlt">dynamical</span> form of the equilibrium equations, with added noise and appropriate augmentation by the discretized shear modulus as additional states, is then adopted as the process equation such that its steady-state solution approaches the static response of the plane-strain model. A fictitious noise of small intensity is also added to the measurement equation and, following linearization of the process equation, a Kalman filter is applied to reconstruct the shear modulus profile. We present several numerical experiments, some of which also bring forth the relative advantages of the proposed approach over a deterministic reconstruction based on a quasi-Newton search.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/15264257','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/15264257"><span><span class="hlt">Optimization</span> and <span class="hlt">dynamics</span> of protein-protein complexes using B-splines.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gillilan, Richard E; Lilien, Ryan H</p> <p>2004-10-01</p> <p>A moving-grid approach for <span class="hlt">optimization</span> and <span class="hlt">dynamics</span> of protein-protein complexes is introduced, which utilizes cubic B-spline interpolation for rapid energy and force evaluation. The method allows for the efficient use of full electrostatic potentials joined smoothly to multipoles at long distance so that multiprotein simulation is possible. Using a recently published benchmark of 58 protein complexes, we examine the performance and quality of the grid approximation, refining cocrystallized complexes to within 0.68 A RMSD of interface atoms, close to the optimum 0.63 A produced by the underlying MMFF94 force field. We quantify the theoretical statistical advantage of using minimization in a stochastic search in the case of two rigid bodies, and contrast it with the underlying cost of conjugate gradient minimization using B-splines. The volumes of conjugate gradient minimization basins of attraction in cocrystallized systems are generally orders of magnitude larger than well volumes based on energy thresholds needed to discriminate native from nonnative states; nonetheless, computational cost is significant. Molecular <span class="hlt">dynamics</span> using B-splines is doubly efficient due to the combined advantages of rapid force evaluation and large simulation step sizes. Large basins localized around the native state and other possible binding sites are identifiable during simulations of protein-protein motion. In addition to providing increased modeling detail, B-splines offer new algorithmic possibilities that should be valuable in refining docking candidates and studying global complex behavior.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016OcMod.106..104P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016OcMod.106..104P"><span><span class="hlt">Optimizing</span> <span class="hlt">dynamic</span> downscaling in one-way nesting using a regional ocean model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pham, Van Sy; Hwang, Jin Hwan; Ku, Hyeyun</p> <p>2016-10-01</p> <p><span class="hlt">Dynamical</span> downscaling with nested regional oceanographic models has been demonstrated to be an effective approach for both operationally forecasted sea weather on regional scales and projections of future climate change and its impact on the ocean. However, when nesting procedures are carried out in <span class="hlt">dynamic</span> downscaling from a larger-scale model or set of observations to a smaller scale, errors are unavoidable due to the differences in grid sizes and updating intervals. The present work assesses the impact of errors produced by nesting procedures on the downscaled results from Ocean Regional Circulation Models (ORCMs). Errors are identified and evaluated based on their sources and characteristics by employing the Big-Brother Experiment (BBE). The BBE uses the same model to produce both nesting and nested simulations; so it addresses those error sources separately (i.e., without combining the contributions of errors from different sources). Here, we focus on discussing errors resulting from the spatial grids' differences, the updating times and the domain sizes. After the BBE was separately run for diverse cases, a Taylor diagram was used to analyze the results and recommend an <span class="hlt">optimal</span> combination of grid size, updating period and domain sizes. Finally, suggested setups for the downscaling were evaluated by examining the spatial correlations of variables and the relative magnitudes of variances between the nested model and the original data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010021133','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010021133"><span>A Bell-Curved Based Algorithm for Mixed Continuous and Discrete Structural <span class="hlt">Optimization</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kincaid, Rex K.; Weber, Michael; Sobieszczanski-Sobieski, Jaroslaw</p> <p>2001-01-01</p> <p>An evolutionary based strategy utilizing two normal distributions to generate children is developed to solve <span class="hlt">mixed</span> <span class="hlt">integer</span> nonlinear programming problems. This Bell-Curve Based (BCB) evolutionary algorithm is similar in spirit to (mu + mu) evolutionary strategies and evolutionary programs but with fewer parameters to adjust and no mechanism for self adaptation. First, a new version of BCB to solve purely discrete <span class="hlt">optimization</span> problems is described and its performance tested against a tabu search code for an actuator placement problem. Next, the performance of a combined version of discrete and continuous BCB is tested on 2-dimensional shape problems and on a minimum weight hub design problem. In the latter case the discrete portion is the choice of the underlying beam shape (I, triangular, circular, rectangular, or U).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1340307','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1340307"><span>The impact of short-term stochastic variability in solar irradiance on <span class="hlt">optimal</span> microgrid design</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Schittekatte, Tim; Stadler, Michael; Cardoso, Gonçalo; Mashayekh, Salman; Narayanan, Sankar</p> <p>2016-07-01</p> <p>This paper proposes a new methodology to capture the impact of fast moving clouds on utility power demand charges observed in microgrids with photovoltaic (PV) arrays, generators, and electrochemical energy storage. It consists of a statistical approach to introduce sub-hourly events in the hourly economic accounting process. The methodology is implemented in the Distributed Energy Resources Customer Adoption Model (DER-CAM), a state of the art <span class="hlt">mixed</span> <span class="hlt">integer</span> linear model used to <span class="hlt">optimally</span> size DER in decentralized energy systems. Results suggest that previous iterations of DER-CAM could undersize battery capacities. The improved model depicts more accurately the economic value of PV as well as the synergistic benefits of pairing PV with storage.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27847232','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27847232"><span>Robust <span class="hlt">optimization</span> on sustainable biodiesel supply chain produced from waste cooking oil under price uncertainty.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zhang, Yong; Jiang, Yunjian</p> <p>2017-02-01</p> <p>Waste cooking oil (WCO)-for-biodiesel conversion is regarded as the "waste-to-wealthy" industry. This paper addresses the design of a WCO-for-biodiesel supply chain at both strategic and tactical levels. The supply chain of this problem is studied, which is based on a typical mode of the waste collection (from restaurants' kitchen) and conversion in the cities. The supply chain comprises three stakeholders: WCO supplier, integrated bio-refinery and demand zone. Three key problems should be addressed for the <span class="hlt">optimal</span> design of the supply chain: (1) the number, sizes and locations of bio-refinery; (2) the sites and amount of WCO collected; (3) the transportation plans of WCO and biodiesel. A robust <span class="hlt">mixed</span> <span class="hlt">integer</span> linear model with muti-objective (economic, environmental and social objectives) is proposed for these problems. Finally, a large-scale practical case study is adopted based on Suzhou, a city in the east of China, to verify the proposed models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24951713','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24951713"><span>A <span class="hlt">dynamic</span> multiarmed bandit-gene expression programming hyper-heuristic for combinatorial <span class="hlt">optimization</span> problems.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sabar, Nasser R; Ayob, Masri; Kendall, Graham; Qu, Rong</p> <p>2015-02-01</p> <p>Hyper-heuristics are search methodologies that aim to provide high-quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain. A traditional hyper-heuristic framework has two levels, namely, the high level strategy (heuristic selection mechanism and the acceptance criterion) and low level heuristics (a set of problem specific heuristics). Due to the different landscape structures of different problem instances, the high level strategy plays an important role in the design of a hyper-heuristic framework. In this paper, we propose a new high level strategy for a hyper-heuristic framework. The proposed high-level strategy utilizes a <span class="hlt">dynamic</span> multiarmed bandit-extreme value-based reward as an online heuristic selection mechanism to select the appropriate heuristic to be applied at each iteration. In addition, we propose a gene expression programming framework to automatically generate the acceptance criterion for each problem instance, instead of using human-designed criteria. Two well-known, and very different, combinatorial <span class="hlt">optimization</span> problems, one static (exam timetabling) and one <span class="hlt">dynamic</span> (<span class="hlt">dynamic</span> vehicle routing) are used to demonstrate the generality of the proposed framework. Compared with state-of-the-art hyper-heuristics and other bespoke methods, empirical results demonstrate that the proposed framework is able to generalize well across both domains. We obtain competitive, if not better results, when compared to the best known results obtained from other methods that have been presented in the scientific literature. We also compare our approach against the recently released hyper-heuristic competition test suite. We again demonstrate the generality of our approach when we compare against other methods that have utilized the same six benchmark datasets from this test suite.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22472538','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22472538"><span><span class="hlt">Optimization</span> of municipal solid waste collection and transportation routes</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Das, Swapan Bhattacharyya, Bidyut Kr.</p> <p>2015-09-15</p> <p>Graphical abstract: Display Omitted - Highlights: • Profitable integrated solid waste management system. • <span class="hlt">Optimal</span> municipal waste collection scheme between the sources and waste collection centres. • <span class="hlt">Optimal</span> path calculation between waste collection centres and transfer stations. • <span class="hlt">Optimal</span> waste routing between the transfer stations and processing plants. - Abstract: <span class="hlt">Optimization</span> of municipal solid waste (MSW) collection and transportation through source separation becomes one of the major concerns in the MSW management system design, due to the fact that the existing MSW management systems suffer by the high collection and transportation cost. Generally, in a city different waste sources scatter throughout the city in heterogeneous way that increase waste collection and transportation cost in the waste management system. Therefore, a shortest waste collection and transportation strategy can effectively reduce waste collection and transportation cost. In this paper, we propose an <span class="hlt">optimal</span> MSW collection and transportation scheme that focus on the problem of minimizing the length of each waste collection and transportation route. We first formulize the MSW collection and transportation problem into a <span class="hlt">mixed</span> <span class="hlt">integer</span> program. Moreover, we propose a heuristic solution for the waste collection and transportation problem that can provide an <span class="hlt">optimal</span> way for waste collection and transportation. Extensive simulations and real testbed results show that the proposed solution can significantly improve the MSW performance. Results show that the proposed scheme is able to reduce more than 30% of the total waste collection path length.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PMB....58.7391K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PMB....58.7391K"><span><span class="hlt">Dynamic</span> whole-body PET parametric imaging: I. Concept, acquisition protocol <span class="hlt">optimization</span> and clinical application</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Karakatsanis, Nicolas A.; Lodge, Martin A.; Tahari, Abdel K.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman</p> <p>2013-10-01</p> <p>Static whole-body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving <span class="hlt">dynamic</span> acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer <span class="hlt">dynamics</span>, an important capability for tumor characterization and treatment response monitoring. Nonetheless, <span class="hlt">dynamic</span> protocols have been confined to single-bed-coverage limiting the axial field-of-view to ˜15-20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to <span class="hlt">dynamic</span> whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed <span class="hlt">dynamic</span> PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of <span class="hlt">dynamic</span> frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel <span class="hlt">dynamic</span> (4D) whole-body PET acquisition protocol of ˜45 min total length is presented, composed of (i) an initial 6 min <span class="hlt">dynamic</span> PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (six passes × seven bed positions, each scanned for 45 s). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to <span class="hlt">optimize</span> the acquisition protocol from a range of ten different clinically</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EnOp...47..550B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EnOp...47..550B"><span>Extension of the hybrid linear programming method to <span class="hlt">optimize</span> simultaneously the design and operation of groundwater utilization systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bostan, Mohamad; Hadi Afshar, Mohamad; Khadem, Majed</p> <p>2015-04-01</p> <p>This article proposes a hybrid linear programming (LP-LP) methodology for the simultaneous <span class="hlt">optimal</span> design and operation of groundwater utilization systems. The proposed model is an extension of an earlier LP-LP model proposed by the authors for the <span class="hlt">optimal</span> operation of a set of existing wells. The proposed model can be used to <span class="hlt">optimally</span> determine the number, configuration and pumping rates of the operational wells out of potential wells with fixed locations to minimize the total cost of utilizing a two-dimensional confined aquifer under steady-state flow conditions. The model is able to take into account the well installation, piping and pump installation costs in addition to the operational costs, including the cost of energy and maintenance. The solution to the problem is defined by well locations and their pumping rates, minimizing the total cost while satisfying a downstream demand, lower/upper bound on the pumping rates, and lower/upper bound on the water level drawdown at the wells. A discretized version of the differential equation governing the flow is first embedded into the model formulation as a set of additional constraints. The resulting <span class="hlt">mixed-integer</span> highly constrained nonlinear <span class="hlt">optimization</span> problem is then decomposed into two subproblems with different sets of decision variables, one with a piezometric head and the other with the operational well locations and the corresponding pumping rates. The binary variables representing the well locations are approximated by a continuous variable leading to two LP subproblems. Having started with a random value for all decision variables, the two subproblems are solved iteratively until convergence is achieved. The performance and ability of the proposed method are tested against a hypothetical problem from the literature and the results are presented and compared with those obtained using a <span class="hlt">mixed-integer</span> nonlinear programming method. The results show the efficiency and effectiveness of the proposed method for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1126436','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1126436"><span>TAS: 89 0227: TAS Recovery Act - <span class="hlt">Optimization</span> and Control of Electric Power Systems: ARRA</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Chiang, Hsiao-Dong</p> <p>2014-02-01</p> <p>The name SuperOPF is used to refer several projects, problem formulations and soft-ware tools intended to extend, improve and re-define some of the standard methods of <span class="hlt">optimizing</span> electric power systems. Our work included applying primal-dual interior point methods to standard AC <span class="hlt">optimal</span> power flow problems of large size, as well as extensions of this problem to include co-<span class="hlt">optimization</span> of multiple scenarios. The original SuperOPF problem formulation was based on co-<span class="hlt">optimizing</span> a base scenario along with multiple post-contingency scenarios, where all AC power flow models and constraints are enforced for each, to find <span class="hlt">optimal</span> energy contracts, endogenously determined locational reserves and appropriate nodal energy prices for a single period <span class="hlt">optimal</span> power flow problem with uncertainty. This led to example non-linear programming problems on the order of 1 million constraints and half a million variables. The second generation SuperOPF formulation extends this by adding multiple periods and multiple base scenarios per period. It also incorporates additional variables and constraints to model load following reserves, ramping costs, and storage resources. A third generation of the multi-period SuperOPF, adds both integer variables and a receding horizon framework in which the problem type is more challenging (<span class="hlt">mixed</span> <span class="hlt">integer</span>), the size is even larger, and it must be solved more frequently, pushing the limits of currently available algorithms and solvers. The consideration of transient stability constraints in <span class="hlt">optimal</span> power flow (OPF) problems has become increasingly important in modern power systems. Transient stability constrained OPF (TSCOPF) is a nonlinear <span class="hlt">optimization</span> problem subject to a set of algebraic and differential equations. Solving a TSCOPF problem can be challenging due to (i) the differential-equation constraints in an <span class="hlt">optimization</span> problem, (ii) the lack of a true analytical expression for transient stability in OPF. To handle the <span class="hlt">dynamics</span> in TSCOPF, the set</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4142329','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4142329"><span><span class="hlt">Optimal</span> Control Strategy Design Based on <span class="hlt">Dynamic</span> Programming for a Dual-Motor Coupling-Propulsion System</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Zhang, Shuo; Zhang, Chengning; Han, Guangwei; Wang, Qinghui</p> <p>2014-01-01</p> <p>A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its <span class="hlt">optimal</span> control strategy is studied in this paper. The necessary <span class="hlt">dynamic</span> features of energy loss for subsystems is modeled. <span class="hlt">Dynamic</span> programming (DP) technique is applied to find the <span class="hlt">optimal</span> control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Improved control rules are extracted from the DP-based control solution, forming near-<span class="hlt">optimal</span> control strategies. Simulation results demonstrate that a significant improvement in reducing energy loss due to the dual-motor coupling-propulsion system (DMCPS) running is realized without increasing the frequency of the mode switch. PMID:25540814</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25855209','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25855209"><span>Analysis of green algal growth via <span class="hlt">dynamic</span> model simulation and process <span class="hlt">optimization</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zhang, Dongda; Chanona, Ehecatl Antonio Del-Rio; Vassiliadis, Vassilios S; Tamburic, Bojan</p> <p>2015-10-01</p> <p>Chlamydomonas reinhardtii is a green microalga with the potential to generate sustainable biofuels for the future. Process simulation models are required to predict the impact of laboratory-scale growth experiments on future scaled-up system operation. Two <span class="hlt">dynamic</span> models were constructed to simulate C. reinhardtii photo-autotrophic and photo-mixotrophic growth. A novel parameter estimation methodology was applied to determine the values of key parameters in both models, which were then verified using experimental results. The photo-mixotrophic model was used to accurately predict C. reinhardtii growth under different light intensities and in different photobioreactor configurations. The <span class="hlt">optimal</span> dissolved CO2 concentration for C. reinhardtii photo-autotrophic growth was determined to be 0.0643 g·L(-1) , and the <span class="hlt">optimal</span> light intensity for algal growth was 47 W·m(-2) . Sensitivity analysis revealed that the primary factor limiting C. reinhardtii growth was its intrinsic cell decay rate rather than light attenuation, regardless of the growth mode. The photo-mixotrophic growth model was also applied to predict the maximum biomass concentration at different flat-plate photobioreactors scales. A double-exposure-surface photobioreactor with a lower light intensity (less than 50 W·m(-2) ) was the best configuration for scaled-up C. reinhardtii cultivation. Three different short-term (30-day) C. reinhardtii photo-mixotrophic cultivation processes were simulated and optimised. The maximum biomass productivity was 0.053 g·L(-1) ·hr(-1) , achieved under continuous photobioreactor operation. The continuous stirred-tank reactor was the best operating mode, as it provides both the highest biomass productivity and lowest electricity cost of pump operation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080043872','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080043872"><span>Using Maximal Isometric Force to Determine the <span class="hlt">Optimal</span> Load for Measuring <span class="hlt">Dynamic</span> Muscle Power</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Spiering, Barry A.; Lee, Stuart M. C.; Mulavara, Ajitkumar P.; Bentley, Jason R.; Nash, Roxanne E.; Sinka, Joseph; Bloomberg, Jacob J.</p> <p>2009-01-01</p> <p>Maximal power output occurs when subjects perform ballistic exercises using loads of 30-50% of one-repetition maximum (1-RM). However, performing 1-RM testing prior to power measurement requires considerable time, especially when testing involves multiple exercises. Maximal isometric force (MIF), which requires substantially less time to measure than 1-RM, might be an acceptable alternative for determining the <span class="hlt">optimal</span> load for power testing. PURPOSE: To determine the <span class="hlt">optimal</span> load based on MIF for maximizing <span class="hlt">dynamic</span> power output during leg press and bench press exercises. METHODS: Twenty healthy volunteers (12 men and 8 women; mean +/- SD age: 31+/-6 y; body mass: 72 +/- 15 kg) performed isometric leg press and bench press movements, during which MIF was measured using force plates. Subsequently, subjects performed ballistic leg press and bench press exercises using loads corresponding to 20%, 30%, 40%, 50%, and 60% of MIF presented in randomized order. Maximal instantaneous power was calculated during the ballistic exercise tests using force plates and position transducers. Repeated-measures ANOVA and Fisher LSD post hoc tests were used to determine the load(s) that elicited maximal power output. RESULTS: For the leg press power test, six subjects were unable to be tested at 20% and 30% MIF because these loads were less than the lightest possible load (i.e., the weight of the unloaded leg press sled assembly [31.4 kg]). For the bench press power test, five subjects were unable to be tested at 20% MIF because these loads were less than the weight of the unloaded aluminum bar (i.e., 11.4 kg). Therefore, these loads were excluded from analysis. A trend (p = 0.07) for a main effect of load existed for the leg press exercise, indicating that the 40% MIF load tended to elicit greater power output than the 60% MIF load (effect size = 0.38). A significant (p . 0.05) main effect of load existed for the bench press exercise; post hoc analysis indicated that the effect of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1155115','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1155115"><span>REopt: A Platform for Energy System Integration and <span class="hlt">Optimization</span>: Preprint</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Simpkins, T.; Cutler, D.; Anderson, K.; Olis, D.; Elgqvist, E.; Callahan, M.; Walker, A.</p> <p>2014-08-01</p> <p>REopt is NREL's energy planning platform offering concurrent, multi-technology integration and <span class="hlt">optimization</span> capabilities to help clients meet their cost savings and energy performance goals. The REopt platform provides techno-economic decision-support analysis throughout the energy planning process, from agency-level screening and macro planning to project development to energy asset operation. REopt employs an integrated approach to <span class="hlt">optimizing</span> a site?s energy costs by considering electricity and thermal consumption, resource availability, complex tariff structures including time-of-use, demand and sell-back rates, incentives, net-metering, and interconnection limits. Formulated as a <span class="hlt">mixed</span> <span class="hlt">integer</span> linear program, REopt recommends an <span class="hlt">optimally</span>-sized mix of conventional and renewable energy, and energy storage technologies; estimates the net present value associated with implementing those technologies; and provides the cost-<span class="hlt">optimal</span> dispatch strategy for operating them at maximum economic efficiency. The REopt platform can be customized to address a variety of energy <span class="hlt">optimization</span> scenarios including policy, microgrid, and operational energy applications. This paper presents the REopt techno-economic model along with two examples of recently completed analysis projects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26085713','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26085713"><span><span class="hlt">Optimization</span> Model for Web Based Multimodal Interactive Simulations.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Halic, Tansel; Ahn, Woojin; De, Suvranu</p> <p>2015-07-15</p> <p>This paper presents a technique for <span class="hlt">optimizing</span> the performance of web based multimodal interactive simulations. For such applications where visual quality and the performance of simulations directly influence user experience, overloading of hardware resources may result in unsatisfactory reduction in the quality of the simulation and user satisfaction. However, <span class="hlt">optimization</span> of simulation performance on individual hardware platforms is not practical. Hence, we present a <span class="hlt">mixed</span> <span class="hlt">integer</span> programming model to <span class="hlt">optimize</span> the performance of graphical rendering and simulation performance while satisfying application specific constraints. Our approach includes three distinct phases: identification, <span class="hlt">optimization</span> and update. In the identification phase, the computing and rendering capabilities of the client device are evaluated using an exploratory proxy code. This data is utilized in conjunction with user specified design requirements in the <span class="hlt">optimization</span> phase to ensure best possible computational resource allocation. The optimum solution is used for rendering (e.g. texture size, canvas resolution) and simulation parameters (e.g. simulation domain) in the update phase. Test results are presented on multiple hardware platforms with diverse computing and graphics capabilities to demonstrate the effectiveness of our approach.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_25 --> <center> <div class="footer-extlink text-muted"><small>Some links on this page may take you to non-federal websites. Their policies may differ from this site.</small> </div> </center> <div id="footer-wrapper"> <div class="footer-content"> <div id="footerOSTI" class=""> <div class="row"> <div class="col-md-4 text-center col-md-push-4 footer-content-center"><small><a href="http://www.science.gov/disclaimer.html">Privacy and Security</a></small> <div class="visible-sm visible-xs push_footer"></div> </div> <div class="col-md-4 text-center col-md-pull-4 footer-content-left"> <img src="https://www.osti.gov/images/DOE_SC31.png" alt="U.S. Department of Energy" usemap="#doe" height="31" width="177"><map style="display:none;" name="doe" id="doe"><area shape="rect" coords="1,3,107,30" href="http://www.energy.gov" alt="U.S. Deparment of Energy"><area shape="rect" coords="114,3,165,30" href="http://www.science.energy.gov" alt="Office of Science"></map> <a ref="http://www.osti.gov" style="margin-left: 15px;"><img src="https://www.osti.gov/images/footerimages/ostigov53.png" alt="Office of Scientific and Technical Information" height="31" width="53"></a> <div class="visible-sm visible-xs push_footer"></div> </div> <div class="col-md-4 text-center footer-content-right"> <a href="http://www.science.gov"><img src="https://www.osti.gov/images/footerimages/scigov77.png" alt="science.gov" height="31" width="98"></a> <a href="http://worldwidescience.org"><img src="https://www.osti.gov/images/footerimages/wws82.png" alt="WorldWideScience.org" height="31" width="90"></a> </div> </div> </div> </div> </div> <p><br></p> </div><!-- container --> <script type="text/javascript"><!-- // var lastDiv = ""; function showDiv(divName) { // hide last div if (lastDiv) { document.getElementById(lastDiv).className = "hiddenDiv"; } //if value of the box is not nothing and an object with that name exists, then change the class if (divName && document.getElementById(divName)) { document.getElementById(divName).className = "visibleDiv"; lastDiv = divName; } } //--> </script> <script> /** * Function that tracks a click on an outbound link in Google Analytics. * This function takes a valid URL string as an argument, and uses that URL string * as the event label. */ var trackOutboundLink = function(url,collectionCode) { try { h = window.open(url); setTimeout(function() { ga('send', 'event', 'topic-page-click-through', collectionCode, url); }, 1000); } catch(err){} }; </script> <!-- Google Analytics --> <script> (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) })(window,document,'script','//www.google-analytics.com/analytics.js','ga'); ga('create', 'UA-1122789-34', 'auto'); ga('send', 'pageview'); </script> <!-- End Google Analytics --> <script> showDiv('page_1') </script> </body> </html>