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1

Optimal Shipboard Power System Management via Mixed Integer Dynamic Programming

Optimal Shipboard Power System Management via Mixed Integer Dynamic Programming Harry G. Kwatny both the discrete and continuous aspects of the power system and show how dynamic programming can) [8], [6] or a modified version that we call the 'mixed integer dynamic program' (MIDP). The action

Kwatny, Harry G.

2

Statistica Sinica 16(2006), 441-457 OPTIMIZING -LEARNING VIA MIXED INTEGER

Statistica Sinica 16(2006), 441-457 OPTIMIZING -LEARNING VIA MIXED INTEGER PROGRAMMING Yufeng Liu of -learning into a mixed integer programming (MIP) problem. This enables us to utilize the state problem of -learning into a mixed integer programming (MIP) problem. We compare the performance

Liu, Yufeng

2006-01-01

3

Designing Networks: A Mixed-Integer Linear Optimization Approach

Designing networks with specified collective properties is useful in a variety of application areas, enabling the study of how given properties affect the behavior of network models, the downscaling of empirical networks to workable sizes, and the analysis of network evolution. Despite the importance of the task, there currently exists a gap in our ability to systematically generate networks that adhere to theoretical guarantees for the given property specifications. In this paper, we propose the use of Mixed-Integer Linear Optimization modeling and solution methodologies to address this Network Generation Problem. We present a number of useful modeling techniques and apply them to mathematically express and constrain network properties in the context of an optimization formulation. We then develop complete formulations for the generation of networks that attain specified levels of connectivity, spread, assortativity and robustness, and we illustrate these via a number of computational case studies.

Gounaris, Chrysanthos E; Kevrekidis, Ioannis G; Floudas, Christodoulos A

2015-01-01

4

NASA Astrophysics Data System (ADS)

Many applications of smart grid can be formulated as constrained optimization problems. Because of the discrete controls involved in power systems, these problems are essentially mixed-integer nonlinear programs. In this paper, we review the Trust-Tech-based methodology for solving mixed-integer nonlinear optimization. Specifically, we have developed a two-stage Trust-Tech-based methodology to systematically compute all the local optimal solutions for constrained mixed-integer nonlinear programming (MINLP) problems. In the first stage, for a given MINLP problem this methodology starts with the construction of a new, continuous, unconstrained problem through relaxation and the penalty function method. A corresponding dynamical system is then constructed to search for a set of local optimal solutions for the unconstrained problem. In the second stage, a reduced constrained NLP is defined for each local optimal solution by determining and fixing the values of integral variables of the MINLP problem. The Trust-Tech-based method is used to compute a set of local optimal solutions for these reduced NLP problems, from which the optimal solution of the original MINLP problem is determined. A numerical simulation of several testing problems is provided to illustrate the effectiveness of our proposed method.

Wang, Bin; Chiang, Hsiao-Dong

5

Mixed-integer programming methods for supply chain optimization Christos Maravelias, University of Wisconsin - Madison Mixedinteger programming methods for supply chain optimization C h r i s t o s T. M July 19-29, 2011, Angra dos Reis, RJ, Brazil #12;Mixed-integer programming methods for supply chain

Grossmann, Ignacio E.

6

Aircraft deconfliction with speed regulation: new models from mixed-integer optimization

given safety distances. Detection and resolution of aircraft conflicts, also referred to as aircraftAircraft deconfliction with speed regulation: new models from mixed-integer optimization Sonia and solving aircraft conflicts, which occur when aircraft sharing the same airspace are too close to each

Boyer, Edmond

7

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

NASA Astrophysics Data System (ADS)

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.

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

2014-09-01

8

Integer tree-based search and mixed-integer optimal control of distribution chains

The use of integer tree-based search and mixed-integer programming is investigated for the purpose of control of multi-item multi-echelon distribution chains. A discrete-time model is considered to describe the dynamics of a generic distribution chain. The decisions on the amounts of goods to transfer are made by referring to a performance index that accounts for transportation, storage, and backlog costs

A. Alessandri; M. Gaggero; F. Tonelli

2011-01-01

9

Current inverse treatment planning methods that optimize both catheter positions and dwell times in prostate HDR brachytherapy use surrogate linear or quadratic objective functions that have no direct interpretation in terms of dose-volume histogram (DVH) criteria, do not result in an optimum or have long solution times. We decrease the solution time of existing linear and quadratic dose-based programming models (LP and QP, respectively) to allow optimizing over potential catheter positions using mixed integer programming. An additional average speed-up of 75% can be obtained by stopping the solver at an early stage, without deterioration of the plan quality. For a fixed catheter configuration, the dwell time optimization model LP solves to optimality in less than 15 seconds, which confirms earlier results. We propose an iterative procedure for QP that allows to prescribe the target dose as an interval, while retaining independence between the solution time and the number of dose calculation points. This iter...

Gorissen, Bram L; Hoffmann, Aswin L

2014-01-01

10

NASA Astrophysics Data System (ADS)

In this paper thermo-chemical simulation of the pultrusion process of a composite rod is first used as a validation case to ensure that the utilized numerical scheme is stable and converges to results given in literature. Following this validation case, a cylindrical die block with heaters is added to the pultrusion domain of a composite part and thermal contact resistance (TCR) regions at the die-part interface are defined. Two optimization case studies are performed on this new configuration. In the first one, optimal die radius and TCR values are found by using a hybrid genetic algorithm based on a sequential combination of a genetic algorithm (GA) and a local search technique to fit the centerline temperature of the composite with the one calculated in the validation case. In the second optimization study, the productivity of the process is improved by using a mixed integer genetic algorithm (MIGA) such that the total number of heaters is minimized while satisfying the constraints for the maximum composite temperature, the mean of the cure degree at the die exit and the pulling speed.

Baran, Ismet; Tutum, Cem C.; Hattel, Jesper H.

2013-08-01

11

NASA Astrophysics Data System (ADS)

Current inverse treatment planning methods that optimize both catheter positions and dwell times in prostate HDR brachytherapy use surrogate linear or quadratic objective functions that have no direct interpretation in terms of dose-volume histogram (DVH) criteria, do not result in an optimum or have long solution times. We decrease the solution time of the existing linear and quadratic dose-based programming models (LP and QP, respectively) to allow optimizing over potential catheter positions using mixed integer programming. An additional average speed-up of 75% can be obtained by stopping the solver at an early stage, without deterioration of the plan quality. For a fixed catheter configuration, the dwell time optimization model LP solves to optimality in less than 15 s, which confirms earlier results. We propose an iterative procedure for QP that allows us to prescribe the target dose as an interval, while retaining independence between the solution time and the number of dose calculation points. This iterative procedure is comparable in speed to the LP model and produces better plans than the non-iterative QP. We formulate a new dose-volume-based model that maximizes V100% while satisfying pre-set DVH criteria. This model optimizes both catheter positions and dwell times within a few minutes depending on prostate volume and number of catheters, optimizes dwell times within 35 s and gives better DVH statistics than dose-based models. The solutions suggest that the correlation between the objective value and the clinical plan quality is weak in the existing dose-based models.

Gorissen, Bram L.; den Hertog, Dick; Hoffmann, Aswin L.

2013-02-01

12

Current inverse treatment planning methods that optimize both catheter positions and dwell times in prostate HDR brachytherapy use surrogate linear or quadratic objective functions that have no direct interpretation in terms of dose-volume histogram (DVH) criteria, do not result in an optimum or have long solution times. We decrease the solution time of the existing linear and quadratic dose-based programming models (LP and QP, respectively) to allow optimizing over potential catheter positions using mixed integer programming. An additional average speed-up of 75% can be obtained by stopping the solver at an early stage, without deterioration of the plan quality. For a fixed catheter configuration, the dwell time optimization model LP solves to optimality in less than 15 s, which confirms earlier results. We propose an iterative procedure for QP that allows us to prescribe the target dose as an interval, while retaining independence between the solution time and the number of dose calculation points. This iterative procedure is comparable in speed to the LP model and produces better plans than the non-iterative QP. We formulate a new dose-volume-based model that maximizes V(100%) while satisfying pre-set DVH criteria. This model optimizes both catheter positions and dwell times within a few minutes depending on prostate volume and number of catheters, optimizes dwell times within 35 s and gives better DVH statistics than dose-based models. The solutions suggest that the correlation between the objective value and the clinical plan quality is weak in the existing dose-based models. PMID:23363622

Gorissen, Bram L; den Hertog, Dick; Hoffmann, Aswin L

2013-02-21

13

Background The majority of curative health care is organized in hospitals. As in most other countries, the current 94 hospital locations in the Netherlands offer almost all treatments, ranging from rather basic to very complex care. Recent studies show that concentration of care can lead to substantial quality improvements for complex conditions and that dispersion of care for chronic conditions may increase quality of care. In previous studies on allocation of hospital infrastructure, the allocation is usually only based on accessibility and/or efficiency of hospital care. In this paper, we explore the possibilities to include a quality function in the objective function, to give global directions to how the ‘optimal’ hospital infrastructure would be in the Dutch context. Methods To create optimal societal value we have used a mathematical mixed integer programming (MIP) model that balances quality, efficiency and accessibility of care for 30 ICD-9 diagnosis groups. Typical aspects that are taken into account are the volume-outcome relationship, the maximum accepted travel times for diagnosis groups that may need emergency treatment and the minimum use of facilities. Results The optimal number of hospital locations per diagnosis group varies from 12-14 locations for diagnosis groups which have a strong volume-outcome relationship, such as neoplasms, to 150 locations for chronic diagnosis groups such as diabetes and chronic obstructive pulmonary disease (COPD). Conclusions In conclusion, our study shows a new approach for allocating hospital infrastructure over a country or certain region that includes quality of care in relation to volume per provider that can be used in various countries or regions. In addition, our model shows that within the Dutch context chronic care may be too concentrated and complex and/or acute care may be too dispersed. Our approach can relatively easily be adopted towards other countries or regions and is very suitable to perform a ‘what-if’ analysis. PMID:23768234

2013-01-01

14

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

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 to draw up the requirements of a public tender. The authors advocate this approach to address similar problems within the field of Health Services to improve the efficiency and the effectiveness of the processes involved. Problems such as those in operation rooms or emergency rooms, where the availability of a large amount of material is critical are eligible to be dealt with in a simmilar manner. PMID:19995438

2009-01-01

15

NASA Astrophysics Data System (ADS)

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.

Sakakibara, Kazutoshi; Tian, Yajie; Nishikawa, Ikuko

16

Duality for Mixed-Integer Linear Programs

Keywords: Duality, Mixed-Integer Linear Programming, Value Function, Branch and Cut. ... possible to develop not only direct solution algorithms for solving LPs but also sophisticated dynamic ...... dual functions of potential interest in practice.

2007-04-05

17

Optimizing well-stimulation treatment size using mixed integer linear programming

This thesis presents a model for optimum sizing of well stimulation treatments. The optimization scheme is based on a combination of a well stimulation type selection and treatment size, therefore determining the optimum type of stimulation...

Picon Aranguren, Oscar

2002-01-01

18

Recently, a model for drug interactions considering also side effects has been proposed. According to this model, the effect compartment concentration range maximizing the global well-being of the patient can be identified. This optimal range represents the set which should be targeted by drug infusion. In this work, we apply this novel model to the clinically relevant combination of intravenous

Valentina Sartori; Eleonora Zanderigo; Michal Kvasnica; Manfred Morari

2005-01-01

19

Two competing methods for assigning intensities to radiation treatment beams were tested. One method was derived from mixed integer programming and the other was based on simulated annealing. The methods faced a common objective and identical constraints. The goal was to maximize the minimum tumor dose while keeping the dose in required fractions of normal organ volumes below a threshold for damage. The minimum tumor doses of the two methods were compared when all the dose-volume constraints were satisfied. A mixed integer linear program gave a minimum tumor dose that was at least 1.8 Gy higher than that given by simulated annealing in 7 of 19 trials. The difference was > or = 5.4 Gy in 4 of 19 trials. In no case was the mixed integer solution one fraction size (1.8 Gy) worse than that of simulated annealing. The better solution provided by the mixed integer program allows tumor dose to increase without violating the dose-volume limits of normal tissues. PMID:8798166

Langer, M; Morrill, S; Brown, R; Lee, O; Lane, R

1996-06-01

20

Canalizing structure of genetic network dynamics: modelling and identification via mixed as hierarchically canalizing functions. We introduce a class of kinetic models for the concentration of the proteins in the network built on a family of canalizing functions that has been shown to capture the vast majority

Ferrari-Trecate, Giancarlo

21

Mixed-integer programming for control

The article describes how mixed-integer programming (MIP) can be employed for feedback control. MIP can be used to find optimal trajectories subject to integer constraints, which can encode discrete decisions or nonconvexity, for example. This optimization can be performed online within model predictive control (MPC) to implement a feedback control law. The article discusses how to model systems using MIP,

Arthur Richards

2005-01-01

22

A MIXED INTEGER DISJUNCTIVE MODEL FOR TRANSMISSION ...

the transmission network expansion problem cannot guarantee finding the optimal .... For each iteration, a trial expansion proposal x is obtained by solving a mixed integer ..... The greedy randomized adaptive search procedure [11] is a metaheuristic ... the RCL size is controlled by the parameter ?, where 0 ? ? ?. 1.

Laura

2001-10-26

23

Online trajectory planning for UAVs using mixed integer linear programming

This thesis presents a improved path planner using mixed-integer linear programming (MILP) to solve a receding horizon optimization problem for unmanned aerial vehicles (UAV's). Using MILP, hard constraints for obstacle ...

Culligan, Kieran Forbes

2006-01-01

24

Semidefinite Relaxations for Non-Convex Quadratic Mixed-Integer ...

Most algorithms and software tools for quadratic mixed-integer optimization ... cutting planes yields a very fast algorithm for solving the maximum cut prob- .... In our evaluation, we are also interested in the dependance of performance on.

2011-11-08

25

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

NASA Technical Reports Server (NTRS)

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.

Cheung, Kar-Ming; Lee, Charles H.

2012-01-01

26

This paper provides a method for planning fuel-optimal trajectories for multiple unmanned aerial vehicles to reconfigure and traverse between goal points in a dynamic environment in real-time. Recent developments in robot motion planning have shown that trajectory optimization of linear vehicle systems including collision avoidance can be written as a linear program subject to mixed integer constraints, known as a

Yongxing Hao; A. Davari; A. Manesh

2005-01-01

27

This paper focuses on the optimization of the design and operation of combined heat and power plants (cogeneration plants).\\u000a Due to the complexity of such an optimization task, conventional optimization methods consider only one operation point that\\u000a is usually the full-load case. However, the frequent changes in demand lead to operation in several partial-load conditions.\\u000a To guarantee a technically feasible

Marc Jüdes; Stefan Vigerske; George Tsatsaronis

28

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. PMID:17395362

Ko, Andi Setiady; Chang, Ni-Bin

2008-07-01

29

Mixed Integer Programming and Heuristic Scheduling for Space Communication

NASA Technical Reports Server (NTRS)

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.

Lee, Charles H.; Cheung, Kar-Ming

2013-01-01

30

Optimal design applications are often modeled by using categorical variables to express discrete design decisions, such as material types. A disadvantage of using categorical variables is the lack of continuous relaxations, which precludes the use of modern integer programming techniques. We show how to express categorical variables with standard integer modeling techniques, and we illustrate this approach on a load-bearing thermal insulation system. The system consists of a number of insulators of different materials and intercepts that minimize the heat flow from a hot surface to a cold surface. Our new model allows us to employ black-box modeling languages and solvers and illustrates the interplay between integer and nonlinear modeling techniques. We present numerical experience that illustrates the advantage of the standard integer model.

Abhishek, K.; Leyffer, S.; Linderoth, J. T.; Mathematics and Computer Science; Lehigh Univ.

2010-06-01

31

Aircraft trajectory planning with collision avoidance using mixed integer linear programming

Describes a method for finding optimal trajectories for multiple aircraft avoiding collisions. Developments in spacecraft path-planning have shown that trajectory optimization including collision avoidance can be written as a linear program subject to mixed integer constraints, known as a mixed-integer linear program (MILP). This can be solved using commercial software written for the operations research community. In the paper, an

Arthur Richards

2002-01-01

32

Antenna Design With a Mixed Integer Genetic Algorithm

Antenna design variables, such as size, have continuous values while others, such as permittivity, have a finite number of values. Having both variable types in one problem requires a mixed integer optimization algorithm. This paper describes a genetic algorithm (GA) that works with real and\\/or binary values in the same chromosome. The algorithm is demonstrated on designing low side-lobe phase

Randy L. Haupt

2007-01-01

33

Mixed Integer Linear Programming Formulation Techniques

A wide range of problems can be modeled as Mixed Integer Linear Programming (MIP) problems using standard formulation techniques. However, in some cases the resulting MIP can be either too weak or too large to be effectively ...

Vielma, Juan Pablo

34

convex segmentation and mixed-integer footstep planning for a walking robot

This work presents a novel formulation of the footstep planning problem as a mixed-integer convex optimization. The footstep planning problem involves choosing a set of footstep locations which a walking robot can follow ...

Deits, Robin L. H. (Robin Lloyd Henderson)

2014-01-01

35

A conic integer program is an integer programming problem with conic constraints. Many problems in nance, engineering, statistical learning, and probabilistic optimization are modeled using conic constraints. Here we study mixed-integer sets dened by second-order conic constraints. We introduce general-purpose cuts for conic mixed-integer programming based on polyhedral conic substructures of second-order conic sets. These cuts can be readily incorporated

ALPER ATAMT; VISHNU NARAYANAN

36

Network Formulations of Mixed-Integer Programs

We consider mixed-integer sets of the type MIXTU = {x : Ax ? b; xi integer, i ? I}, where A is a totally unimodular matrix, b is an arbitrary vector and I is a nonempty subset of the column indices of A. We show that the problem of checking nonemptiness of a set MIXTU is NP-complete when A contains

Michele Conforti; Marco Di Summa; Friedrich Eisenbrand; Laurence A. Wolsey

2009-01-01

37

A Mixed Integer Programming Approach for Allocating Operating Room Capacity

1 A Mixed Integer Programming Approach for Allocating Operating Room Capacity Bo Zhang, Pavankumar methodology consists of a finite-horizon mixed integer programming (MIP) model which determines a weekly of stay pertaining to surgery can be reduced. KEYWORDS Mixed Integer Programming, Surgery, Operating Room

Dessouky, Maged

38

Solving the Quorumcast Routing Problem as a Mixed Integer Program

Solving the Quorumcast Routing Problem as a Mixed Integer Program Quoc Trung BUI1 , Quang Dung PHAM on a given undirected weighted graph. In this paper, we solve this problem as a mixed integer program In this paper, we propose four mathematical formulations for QRP and use them to solve QRP as a mixed integer

Deville, Yves

39

Cross decomposition for mixed integer programming

Many methods for solving mixed integer programming problems are based either on primal or on dual decomposition, which yield,\\u000a respectively, a Benders decomposition algorithm and an implicit enumeration algorithm with bounds computed via Lagrangean\\u000a relaxation. These methods exploit either the primal or the dual structure of the problem. We propose a new approach, cross\\u000a decomposition, which allows exploiting simultaneously both

Tony J. Van Roy

1983-01-01

40

Solid Waste Management System Analysis by Multiobjective Mixed Integer Programming Model

The conflict between economic optimization and environmental protection has received wide attention in recent research programs for solid waste management system planning. The purpose of this analysis is to apply multiobjective mixed integer programming techniques for reasoning the potential conflict between environmental and economic goals and for evaluating sustainable strategies for waste management in a metropolitan region. The information incorporated

Ni-Bin Chang; S. F. Wang

1996-01-01

41

Mixed-Integer Nonlinear Programming Models and Algorithms for Large-Scale Supply Chain Design with

-1- Mixed-Integer Nonlinear Programming Models and Algorithms for Large-Scale Supply Chain Design companies is to simultaneously consider inventory optimization and supply chain network design under demand, 2 A key challenge to achieve this goal is to integrate inventory management with supply chain

Grossmann, Ignacio E.

42

Reduceandsplit cuts: Improving the performance of mixed integer Gomory cuts 1

such as for the National Football League (Optimal Planning Solutions) and Major League Baseball (The Sports Scheduling plane, split cut, mixed integer Gomory cut, reduceÂandÂsplit cut 1 Introduction Many management problems combinatorial auctions (CombineNet), finanÂ cial engineering (Axioma) and sports scheduling

Cornuejols, Gerard P.

43

An algorithmic framework for convex mixed integer nonlinear programs

This paper is motivated by the fact that mixed integer nonlinear programming is an important and dicult area for which there is a need for developing new methods and soft- ware for solving large-scale problems. Moreover, both fundamental building blocks, namely mixed integer linear programming and nonlinear programming, have seen considerable and steady progress in recent years. Wishing to exploit

Pierre Bonami; Lorenz T. Biegler; Andrew R. Conn; Gérard Cornuéjols; Ignacio E. Grossmann; Carl D. Laird; Jon Lee; Andrea Lodi; François Margot; Nicolas Sawaya; Andreas Wächter

2008-01-01

44

Mixed Integer Linear Programming Method for Absolute Value Equations

We formulate the NP-hard absolute value equation as linear complementary problem when the singular values of A exceed one, and we proposed a mixed integer linear programming method to absolute value equation problem. The effectiveness of the method is demonstrated by its ability to solve random problems. Index Terms—absolute value equation; linear complementary problem; mixed integer linear programming. The basic

Longquan Yong

2009-01-01

45

Dynamic Resource Allocation for Optimizing Population Diffusion Shan Xue Alan Fern Daniel Sheldon

Dynamic Resource Allocation for Optimizing Population Diffusion Shan Xue Alan Fern Daniel Sheldon policies based on mixed-integer programming and dual de- composition. Our experiments on synthetic and real future budgets, and a combinatorial action space (the set of possible investment combinations). Generic

46

This paper addresses the problem of inventory management of a refinery that imports several types of crude oil which are delivered by different vessels. This problem involves optimal operation of crude oil unloading, its transfer from storage tanks to charging tanks, and the charging schedule for each crude oil distillation unit. A mixed-integer optimization model is developed which relies on

Heeman Lee; J. M. Pinto; I. E. Grossmann

1996-01-01

47

Orbital rendezvous mission planning using mixed integer nonlinear programming

NASA Astrophysics Data System (ADS)

The rendezvous and docking mission is usually divided into several phases, and the mission planning is performed phase by phase. A new planning method using mixed integer nonlinear programming, which investigates single phase parameters and phase connecting parameters simultaneously, is proposed to improve the rendezvous mission's overall performance. The design variables are composed of integers and continuous-valued numbers. The integer part consists of the parameters for station-keeping and sensor-switching, the number of maneuvers in each rendezvous phase and the number of repeating periods to start the rendezvous mission. The continuous part consists of the orbital transfer time and the station-keeping duration. The objective function is a combination of the propellant consumed, the sun angle which represents the power available, and the terminal precision of each rendezvous phase. The operational requirements for the spacecraft-ground communication, sun illumination and the sensor transition are considered. The simple genetic algorithm, which is a combination of the integer-coded and real-coded genetic algorithm, is chosen to obtain the optimal solution. A practical rendezvous mission planning problem is solved by the proposed method. The results show that the method proposed can solve the integral rendezvous mission planning problem effectively, and the solution obtained can satisfy the operational constraints and has a good overall performance.

Zhang, Jin; Tang, Guo-jin; Luo, Ya-Zhong; Li, Hai-yang

2011-04-01

48

Parametric Mixed Integer Programming: An Application to Solid Waste Management

A method is developed for carrying out parametric analysis on a mixed integer linear program (MILP) as either objective function coefficients or right-hand-side values of the constraints are varied continuously. The method involves solving MILPs at point values of the parameters of variation and joining the results by LP parametric analysis. The procedure for parametric analysis on the objective function

Larry Jenkins

1982-01-01

49

Radiation Treatment Planning: Mixed Integer Programming Formulations and Approaches

Radiation Treatment Planning: Mixed Integer Programming Formulations and Approaches Michael C. Ferris Robert R. Meyer Warren D'Souza October 2002 Abstract Radiation therapy is extensively used diagnosed with cancer in the U.S will undergo treatment with radiation therapy. This form of therapy has

Ferris, Michael C.

50

SOLVING MIXED INTEGER BILINEAR PROBLEMS USING MILP ...

Key words. bilinear problems, McCormick envelopes, binary expansion, ...... However, we found no performance gain with this approach. ...... [22] R. Karuppiah and I.E. Grossmann, Global optimization for the synthesis of integrated water.

2013-01-29

51

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. PMID:19800164

Guo, P; Huang, G H

2009-01-01

52

A stochastic mixed-integer programming approach to the energy-technology management problem

A stochastic mixed-integer programming approach to the energy-technology management problem be introduced in energy generation. The approach involves a Stochastic Mixed-Integer Program (SMIP programming, Mixed-integer programming 1 Introduction With current population growth, economic development

Dessouky, Maged

53

Mixed integer nonlinear programming using interior-point methods

In this paper, we outline an algorithm for solving mixed integer nonlinear programming (MINLP) problems. The approach uses a branch-and-bound framework for handling the integer variables and an infeasible interior-point method for solving the resulting nonlinear subproblems. We report on the details of the implementation, including the efficient pruning of the branch-and-bound tree via equilibrium constraints, warmstart strategies for interior-point

Hande Y. Benson

2010-01-01

54

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

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.

Woodruff, David L. (University of California, Davis); Watson, Jean-Paul

2010-08-01

55

NASA Technical Reports Server (NTRS)

We distinguish static and dynamic optimization of programs: whereas static optimization modifies a program before runtime and is based only on its syntactical structure, dynamic optimization is based on the statistical properties of the input source and examples of program execution. Explanation-based generalization is a commonly used dynamic optimization method, but its effectiveness as a speedup-learning method is limited, in part because it fails to separate the learning process from the program transformation process. This paper describes a dynamic optimization technique called a learn-optimize cycle that first uses a learning element to uncover predictable patterns in the program execution and then uses an optimization algorithm to map these patterns into beneficial transformations. The technique has been used successfully for dynamic optimization of pure Prolog.

Laird, Philip

1992-01-01

56

This paper reports on an integration of multi-criteria decision analysis (MCDA) and inexact mixed integer linear programming (IMILP) methods to support selection of an optimal landfill site and a waste-flow-allocation pattern such that the total system cost can be minimized. Selection of a landfill site involves both qualitative and quantitative criteria and heuristics. In order to select the best landfill

S. Cheng; C. W. Chan; G. H. Huang

2003-01-01

57

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.

Linderoth, Jeff T. [University of Wisconsin-Madison] [University of Wisconsin-Madison; Luedtke, James R. [University of Wisconsin-Madison] [University of Wisconsin-Madison

2013-05-30

58

Sequential pairing of mixed integer inequalities Yongpei Guan, Shabbir Ahmed, George L. Nemhauser

Sequential pairing of mixed integer inequalities Yongpei Guan, Shabbir Ahmed, George L. Nemhauser integer programs by taking pair- wise combinations of existing valid inequalities. Our scheme is related to mixed integer rounding and mixing. The scheme is in general sequence-dependent and therefore leads

Ahmed, Shabbir

59

Outer approximation algorithms for separable nonconvex mixed-integer nonlinear programs

A rigorous decomposition approach to solve separable mixed-integer nonlinear programs where the participating functions are nonconvex is presented. The proposed algorithms consist of solving an alternating sequence of Relaxed Master Problems (mixed-integer linear program) and two nonlinear programming problems (NLPs). A sequence of valid nondecreasing lower bounds and upper bounds is generated by the algorithms which converge in a finite

Padmanaban Kesavan; Russell J. Allgor; Edward P. Gatzke; Paul I. Barton

2004-01-01

60

LP formulations for mixed-integer polynomial optimization problems ...

formulation, and one may question the utility of relying on the general form GB. ...... of Handbooks in Operations Research and Management Science, Elsevier, 1995 .... dissertation, University of Wisconsin-Madison Department of Electrical and.

2015-02-06

61

Error bounds for mixed integer linear optimization problems

Nov 25, 2013 ... on the construction of a so-called grid relaxation retract. Relations to ... ities of discrete decision variables is modeled as when y is a vector of, for example ..... of a global error bound for the system of inequalities describing ?.

2013-11-25

62

Learning Oncogenetic Networks by Reducing to Mixed Integer Linear Programming

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. PMID:23799047

Shahrabi Farahani, Hossein; Lagergren, Jens

2013-01-01

63

NASA Astrophysics Data System (ADS)

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.

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

64

Planning Investments in Water Resources by Mixed-Integer Programming: The Vardar-Axios River Basin

A mixed integer programming model for planning water resources investments is presented. The model is a sequencing model applied to the Vardar-Axios river basin in Yugoslavia and Greece. The structure of the model is ...

Elliot, Dorothy P.

65

CONCRETE STRUCTURE DESIGN USING MIXED-INTEGER NONLINEAR PROGRAMMING WITH COMPLEMENTARITY

CONCRETE STRUCTURE DESIGN USING MIXED-INTEGER NONLINEAR PROGRAMMING WITH COMPLEMENTARITY programming (MINLP) formulation to achieve mini- mum-cost designs for reinforced concrete (RC) structures for concrete, steel reinforcing bars, and formwork according to typical contractor methods. Restrictions

66

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

NASA Technical Reports Server (NTRS)

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.

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

2010-01-01

67

A Mixed Integer Linear Program for Airport Departure Scheduling

NASA Technical Reports Server (NTRS)

Aircraft departing from an airport are subject to numerous constraints while scheduling departure times. These constraints include wake-separation constraints for successive departures, miles-in-trail separation for aircraft bound for the same departure fixes, and time-window or prioritization constraints for individual flights. Besides these, emissions as well as increased fuel consumption due to inefficient scheduling need to be included. Addressing all the above constraints in a single framework while allowing for resequencing of the aircraft using runway queues is critical to the implementation of the Next Generation Air Transport System (NextGen) concepts. Prior work on airport departure scheduling has addressed some of the above. However, existing methods use pre-determined runway queues, and schedule aircraft from these departure queues. The source of such pre-determined queues is not explicit, and could potentially be a subjective controller input. Determining runway queues and scheduling within the same framework would potentially result in better scheduling. This paper presents a mixed integer linear program (MILP) for the departure-scheduling problem. The program takes as input the incoming sequence of aircraft for departure from a runway, along with their earliest departure times and an optional prioritization scheme based on time-window of departure for each aircraft. The program then assigns these aircraft to the available departure queues and schedules departure times, explicitly considering wake separation and departure fix restrictions to minimize total delay for all aircraft. The approach is generalized and can be used in a variety of situations, and allows for aircraft prioritization based on operational as well as environmental considerations. We present the MILP in the paper, along with benefits over the first-come-first-serve (FCFS) scheme for numerous randomized problems based on real-world settings. The MILP results in substantially reduced delays as compared to FCFS, and the magnitude of the savings depends on the queue and departure fix structure. The MILP assumes deterministic aircraft arrival times at the runway queues. However, due to taxi time uncertainty, aircraft might arrive either earlier or later than these deterministic times. Thus, to incorporate this uncertainty, we present a method for using the MILP with "overlap discounted rolling planning horizon". The approach is based on valuing near-term decision results more than future ones. We develop a model of taxitime uncertainty based on real-world data, and then compare the baseline FCFS delays with delays using the above MILP in a simple rolling-horizon method and in the overlap discounted scheme.

Gupta, Gautam; Jung, Yoon Chul

2009-01-01

68

A Two-Stage Stochastic Mixed-Integer Programming Approach to the Smart House Scheduling Problem

NASA Astrophysics Data System (ADS)

A “Smart House” is a highly energy-optimized house equipped with photovoltaic systems (PV systems), electric battery systems, fuel cell cogeneration systems (FC systems), electric vehicles (EVs) and so on. Smart houses are attracting much attention recently thanks to their enhanced ability to save energy by making full use of renewable energy and by achieving power grid stability despite an increased power draw for installed PV systems. Yet running a smart house's power system, with its multiple power sources and power storages, is no simple task. In this paper, we consider the problem of power scheduling for a smart house with a PV system, an FC system and an EV. We formulate the problem as a mixed integer programming problem, and then extend it to a stochastic programming problem involving recourse costs to cope with uncertain electricity demand, heat demand and PV power generation. Using our method, we seek to achieve the optimal power schedule running at the minimum expected operation cost. We present some results of numerical experiments with data on real-life demands and PV power generation to show the effectiveness of our method.

Ozoe, Shunsuke; Tanaka, Yoichi; Fukushima, Masao

69

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. PMID:16678336

Li, Y P; Huang, G H

2006-11-01

70

Optimization-based methodologies for integrating design and control in cryogenic plants

The aim of this work has been to investigate the potential of advanced mixed-integer dynamic optimization (MIDO) strategies2 to identify optimal design and control schemes for an industrial cryogenic air separation plant (ASP). The MIDO framework is applied to include, along with the control structure choice, selection and sizing of process components. From an economic point of view, this technique

M. Schenk; V. Sakizlis; J. D. Perkins; E. N. Pistikopoulos

2002-01-01

71

Convex Quadratic Relaxations for Mixed-Integer Nonlinear ...

considered models are motivated by hybrid discrete/continuous applications where existing ... Three case studies in optimal power flow, optimal transmis- ... 35], energy market calculations [39,37], transmission switching [16,18], dis- tribution ...

H. Hijazi, C. Coffrin and P. Van Hentenryck

2014-06-03

72

Solution of Mixed-Integer Programming Problems on the XT5

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.

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

2009-01-01

73

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 combinations; secondly, it has capability in addressing the temporal variations of the functional intervals; thirdly, it can facilitate dynamic analysis for decisions of facility-expansion planning and waste-flow allocation within a multi-facility, multi-period and multi-option context. PMID:19854040

Guo, P; Huang, G H

2010-03-01

74

1 Accepted for Publication in Computers and Operations Research (2010) Faster Integer-Feasibility in Mixed-Integer Linear Programs by Branching to Force Change Jennifer Pryor (jpryor@sce.carleton.ca) John, Ontario K1S 5B6 Canada October 22, 2010 Abstract Branching in mixed-integer (or integer) linear

Chinneck, J.W.

2010-01-01

75

A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem

This paper presents a new mixed-integer linear formulation for the unit commitment problem of thermal units. The formulation proposed requires fewer binary variables and constraints than previously reported models, yielding a significant computational saving. Furthermore, the modeling framework provided by the new formulation allows including a precise description of time-dependent startup costs and intertemporal constraints such as ramping limits and

Miguel Carrión; José M. Arroyo

2006-01-01

76

Alternative mixed-integer linear programming models of a maritime inventory routing problem

Alternative mixed-integer linear programming models of a maritime inventory routing problem Jiang product maritime inventory routing problem is addressed in this paper by exploring the use of continuous Introduction Maritime transportation is a major mode of transportation covering more than 80% of the world

Grossmann, Ignacio E.

77

Amending and enhancing electoral laws through mixed integer programming: the case of Italy

Amending and enhancing electoral laws through mixed integer programming: the case of Italy Aline Pennisi 1 , Federica Ricca 1 , Paolo Serafini 2 , Bruno Simeone 3 1 Electoral Systems expert, Rome, Italy 2 Dept. of Mathematics and Computer Science, University of Udine, Italy 3 Dept. of Statistics, La

Serafini, Paolo

78

American Institute of Aeronautics and Astronautics 1 A Mixed Integer Linear Program for Airport system delay alone improves throughput over a basic first-come-first-serve rule. Modifications than separation based on weight class. Constraint Position Shifting (CPS) has been proposed

79

Asset liability management modeling using multi-stage mixed-integer stochastic programming

A pension fund has to match the portfolio of long-term liabilities with the portfolio of assets. Key instruments in strategic Asset Liability Management (ALM) are the adjustments of the contribution rate of the sponsor and the reallocation of the investments in several asset classes at various points of time. We formulate a multistage mixed-integer stochastic program to model this ALM

Maarten H. van der Vlerk; Willem K. Klein Haneveld; S. J. Drijver

2000-01-01

80

A mixed-integer linear program for the real-time railway traffic management problem

A mixed-integer linear program for the real-time railway traffic management problem: Quantification.pellegrini, gregory.marliere, joaquin.rodriguez}@ifsttar.fr Mots-clés : real-time railway traffic management problem and current practice At peak hours, railway timetables extensively exploit the infrastructure

Paris-Sud XI, Université de

81

A local search heuristic for a mixed integer nonlinear integrated airline schedule planning problem

of the transportation demand. Once the decisions on scheduling and fleeting are published, few changes can be made Bilge Atasoy Matteo Salani Michel Bierlaire April 18, 2013 Report TRANSP-OR 130402 Transport allocation, pricing and considers passengers' spill and recapture. The resulting problem is a mixed integer

Bierlaire, Michel

82

Concrete Structure Design Using Mixed-Integer Nonlinear Programming with Complementarity Constraints

Concrete Structure Design Using Mixed-Integer Nonlinear Programming with Complementarity) formulation to achieve minimum-cost designs for reinforced concrete (RC) structures that satisfy building code requirements. The objective function includes material and labor costs for concrete, steel reinforcing bars

83

Active-constraint variable ordering for faster feasibility of mixed integer linear programs

The selection of the branching variable can greatly affect the speed of the branch and bound solution of a mixed-integer or integer linear program. Traditional approaches to branching variable selection rely on estimating the effect of the candidate variables on the objective function. We present a new approach that relies on estimating the impact of the candidate variables on the

Jagat Patel; John W. Chinneck

2007-01-01

84

i Application of Mixed-Integer Programming for Flood Control in the Sacramento Valley: Insights fulfillment of the requirements for the degree of MASTER OF SCIENCE in Engineering in the OFFICE OF GRADUATE............................................................................................................ 3 1.3 DESCRIPTION OF FLOOD EVENTS

Lund, Jay R.

85

Mixed-Integer Models for Nonseparable Piecewise Linear ...

H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, ... the extension of these formulations to lower semicontinuous piecewise linear functions. ... 1993), optimization of electronic circuits (Graf et al.

2009-06-23

86

A several new mixed integer linear programming formulations for ...

May 31, 2014 ... method. Key words: Facility Location, Combinatorial Optimization, Social. Networks ... researchers, the only valuable scientific content of that paper seems to be ...... Regional Science and Urban Economics, 17, 451–473. 12 ...

2014-05-31

87

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

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 techniques developed here will facilitate the strain design process and extend the scope of its application to metabolic engineering. PMID:21949695

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

2011-01-01

88

Scheduling Smart Home Appliances Using Mixed Integer Linear Programming

in residential areas. Intermittent renewable energy sources, such as wind, are dynamic by definition and consumer preferences. Constraints such as enforcing uninterruptible and sequential operations are modeled seasons of the year, where the highest power demand typically occurs when the outdoor temperature drops

Johansson, Karl Henrik

89

An outer-approximation algorithm for a class of mixed-integer nonlinear programs

An outer-approximation algorithm is presented for solving mixed-integer nonlinear programming problems of a particular class.\\u000a Linearity of the integer (or discrete) variables, and convexity of the nonlinear functions involving continuous variables\\u000a are the main features in the underlying mathematical structure. Based on principles of decomposition, outer-approximation\\u000a and relaxation, the proposed algorithm effectively exploits the structure of the problems, and consists

Marco A. Duran; Ignacio E. Grossmann

1986-01-01

90

An Algorithm for the Solution of Multiparametric Mixed Integer Linear Programming Problems

In this paper, we present an algorithm for the solution of multiparametric mixed integer linear programming (mp-MILP) problems involving (i) 0-1 integer variables, and, (ii) more than one parameter, bounded between lower and upper bounds, present on the right hand side (RHS) of constraints. The solution is approached by decomposing the mp-MILP into two subproblems and then iterating between them.

Vivek Dua; Efstratios N. Pistikopoulos

2000-01-01

91

Mixed-Integer Linear Programming Solution to Multi-Robot Task Allocation Problem

Multi-robot systems require efficient and accurate planning in order to perform mission-critical tasks. This paper introduces a mixed-integer linear programming solution to coordinate multiple heterogenenous robots for detecting and controlling multiple regions of interest in an unknown environ- ment. The objective function contains four basic requirements of a multi-robot system serving this purpose: control regions of interest, provide communication between

Burchan Bayazit

92

A New Approach to Integrating Mixed Integer Programming and Constraint Logic Programming

This paper represents an integration of Mixed Integer Programming (MIP) andConstraint Logic Programming (CLP) which, like MIP, tightens bounds ratherthan adding constraints during search. The integrated system combines componentsof the CLP system ECLiPSe [7] and the MIP system CPLEX [5], in whichconstraints can be handled by either one or both components.Our approach is introduced in three stages. Firstly we present

Mark G. Wallace; Mozafar T. Hajian; Robert Rodo Sek

1997-01-01

93

Asset Liability Management modeling using multistage mixed-integer Stochastic Programming

A pension fund has to match the portfolio of long-term liabilities with the portfolio of assets.Key instruments in strategic Asset Liability Management (ALM) are the adjustments of thecontribution rate of the sponsor and the reallocation of the investments in several asset classesat various points of time. We formulate a multistage mixed-integer stochastic program to modelthis ALM process. Special attention is

Sibrand J. Drijver; Willem K. Klein Haneveld; Maarten H. Van Der Vlerk

2000-01-01

94

Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications

This paper reviews the advances of mixed-integer linear programming (MILP) based approaches for the scheduling of chemical\\u000a processing systems. We focus on the short-term scheduling of general network represented processes. First, the various mathematical\\u000a models that have been proposed in the literature are classified mainly based on the time representation. Discrete-time and\\u000a continuous-time models are presented along with their strengths

Christodoulos A. Floudas; Xiaoxia Lin

2005-01-01

95

Manpower scheduling problem is one of the key scheduling problems with extensive applications in manufacturing. This paper\\u000a presents a mixed-integer programming model with a two-stage heuristic algorithm for solving the manpower scheduling problem\\u000a in the precision engineering industry. Firstly, a mixed-integer programming formulation is developed to model the manpower\\u000a scheduling problem in this high-mix low-volume manufacturing environment. Secondly, a two-stage

Quan-Ke Pan; Ponnuthurai N. Suganthan; Tay J. Chua; T. X. Cai

2010-01-01

96

NASA Astrophysics Data System (ADS)

On-farm runoff collection through small impoundments (ponds) is a potential irrigation water source. This study evaluates the economic feasibility of such impoundments for supplemental irrigation in the Blacklands region of Texas. This is done using a risk sensitive model which simultaneously considers water supply, irrigation system investment, irrigation scheduling, and crop mix selection. A two-stage, mixed integer, nonlinear mathematical programming model under uncertainty, was used to formulate the problem and solved with Benders' decomposition. Pond-based supplemental irrigation is found to be both risk reducing and net income increasing in the study area. The model results also show off-farm water needs to be worth more than $100 per acre foot to make impoundments undesirable.

Ziari, Houshmand A.; McCarl, Bruce A.; Stockle, Claudio

1995-06-01

97

Optimal dynamic law enforcement

In this paper we present an intertemporal extension of Becker's [Journal of Political Economy 76 (1968) 169] static economic approach to crime and punishment. For a dynamic supply of offenders we determine the optimal dynamic trade-off between damages caused by offenders, law enforcement expenditures and cost of imprisonment. By using Pontryagin's maximum principle we obtain interesting insight into the dynamical

Gustav Feichtinger; Waltraud Grienauer; Gernot Tragler

2002-01-01

98

Optimal model for future expansion of radial distribution networks using mixed integer programming

One of the objectives of power distribution system planning is to minimise the total cost of feeders in the future expansion of distribution system. The problem is subjected to a few constraints. In the general case, solving this problem is not an easy task. Therefore, different methods such as branch and bound techniques or branch exchange method, etc. have been

S. Salamat Sharif; M. M. A. Salama; A. Vannelli

1994-01-01

99

Clinically relevant cancer chemotherapy dose scheduling via mixed-integer optimization

Cancer is a class of diseases characterized by an imbalance between cell proliferation and programmed cell death. Chemotherapy is commonly employed as a treatment by clinicians, who must deliver the agent on a schedule that balances treatment efficacy with the toxic side effects. Engineers have considered the development of drug administration schedules for simulated cancer patients constrained by pharmacokinetic (PK)

John M. Harrold; Robert S. Parker

2009-01-01

100

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

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.

Jeff Linderoth

2011-11-06

101

Mixed-integer programming methods for transportation and power generation problems

NASA Astrophysics Data System (ADS)

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.

Damci Kurt, Pelin

102

Optimization by record dynamics

NASA Astrophysics Data System (ADS)

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.

Barettin, Daniele; Sibani, Paolo

2014-03-01

103

A solution of the unit commitment problem via decomposition and dynamic programming

Each day power generating units have to be selected to realize a reliable production of electric energy with the fewest fuel costs. This paper proposes decomposition and dynamic programming as techniques for solving the unit commitment problem, a high dimensional non-linear, mixed-integer optimization problem. Experiments indicate that the proposed methods locate in less time a better solution than many existing techniques.

Van den Bosch, P.P.J.; Honderd, G.H.

1985-07-01

104

Dynamic Programming and Optimal Control

Dynamic Programming and Optimal Control Richard Weber Autumn 2014 i #12;Contents Table of Contents ii 1 Dynamic Programming 2 1.1 Control as optimization over time . . . . . . . . . . . . . . . . . . . . . . . . . 8 3 Dynamic Programming over the Infinite Horizon 10 3.1 Discounted costs

Weber, Richard

105

Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjective programming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different p(i) levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help the decision makers justify and/or adjust their waste management strategies based on their implicit knowledge and preferences. PMID:23313898

Zhang, Xiaodong; Huang, Gordon

2013-02-15

106

Optimization Online - All Areas Submissions - October 2012

... and Vanishing Constraints in Mixed-Integer Nonlinear Optimal Control ... Adaptive Regularized Self-Consistent Field Iteration with Exact Hessian for Electronic ... Minimax Robust Unit Commitment Problem with Demand and Market Price ...

107

February 15, 2006 Dynamic Optimization for

February 15, 2006 Dynamic Optimization for Enterprise Wide Optimization L. T. Biegler Chemical · Inherently dynamic systems Conclusions 2 #12;3 Goal: Bridge between planning, logistics (linear, discrete

Grossmann, Ignacio E.

108

. We shall discuss the first point in this paper from the point of view of integer programming. A one-step1 Presented at the IUGG95 Assembly, Boulder, Colorado, July 2-14, 1995. Mixed integer programming and are the random errors of the observables, X is the coordinate vector to be estimated, and fR(.) and f

Calgary, University of

109

Optimization with Extremal Dynamics

A local-search heuristic for finding high-quality solutions for many hard optimization problems is explored. The method is inspired by recent progress in understanding far-from-equilibrium phenomena in terms of self- organized criticality, a concept introduced to describe emergent complexity in physical systems. This method, called extremal optimization, successively replaces the value of extremely undesirable variables in a sub-optimal solution with new,

Stefan Boettcher; Allon G. Percus

2000-01-01

110

Optimization with Extremal Dynamics

We explore a new general-purpose heuristic for finding high-quality solutions to hard discrete optimization problems. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. Extremal optimization successively updates extremely undesirable variables of a single suboptimal solution, assigning them new, random values. Large fluctuations ensue, efficiently exploring many local optima.

Stefan Boettcher; Allon G. Percus

2001-01-01

111

Optimization with Extremal Dynamics

We explore a new general-purpose heuristic for finding high-quality solutions to hard discrete optimization problems. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. Extremal optimization successively updates extremely undesirable variables of a single suboptimal solution, assigning them new, random values. Large fluctuations ensue, efficiently exploring many local optima. We use extremal optimization to elucidate the phase transition in the 3-coloring problem, and we provide independent confirmation of previously reported extrapolations for the ground-state energy of {+-}J spin glasses in d=3 and 4 .

Boettcher, Stefan; Percus, Allon G.

2001-06-04

112

Optimization with Extremal Dynamics

NASA Astrophysics Data System (ADS)

We explore a new general-purpose heuristic for finding high-quality solutions to hard discrete optimization problems. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. Extremal optimization successively updates extremely undesirable variables of a single suboptimal solution, assigning them new, random values. Large fluctuations ensue, efficiently exploring many local optima. We use extremal optimization to elucidate the phase transition in the 3-coloring problem, and we provide independent confirmation of previously reported extrapolations for the ground-state energy of +/-J spin glasses in d = 3 and 4.

Boettcher, Stefan; Percus, Allon G.

2001-06-01

113

Optimization with extremal dynamics.

We explore a new general-purpose heuristic for finding high-quality solutions to hard discrete optimization problems. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. Extremal optimization successively updates extremely undesirable variables of a single suboptimal solution, assigning them new, random values. Large fluctuations ensue, efficiently exploring many local optima. We use extremal optimization to elucidate the phase transition in the 3-coloring problem, and we provide independent confirmation of previously reported extrapolations for the ground-state energy of +/-J spin glasses in d = 3 and 4. PMID:11384460

Boettcher, S; Percus, A G

2001-06-01

114

Exploring Frame Structures with Negative Poisson's Ratio via Mixed Integer Programming

'05] #12;optimization to achieve NPR Â· existing methods: Â· truss model [Sigmund '94] Â· continuum & homogenization method [Larsen, Sigmund, & Bouwstra '97] [Schwerdtfeger et al. '11] Â· continuum & genetic alg [Sigmund '94] Â· continuum & homogenization method [Larsen, Sigmund, & Bouwstra '97] [Schwerdtfeger et al

Kanno, Yoshihiro

115

Practical Guidelines for Solving Difficult Mixed Integer Linear1 Ed Klotz Alexandra M. Newman

, Colorado School of Mines, Golden, CO 80401 klotz@us.ibm.com · newman@mines.edu 3 Abstract4 Even with state-of-the for appropriate use of state-of-the-art optimizers7 and guidelines for careful formulation, both of which can instances can be solved. Indeed, state-of-the-art ptimizers such as CPLEX (IBM, 2012), Gurobi19 (Gurobi

116

Conceptual Design of Biorefineries Through the Synthesis of Optimal Chemical-reaction Pathways

on developing new pathways while optimizing existing ones. Here, potential chemicals are added to create a superstructure, then an algorithm is run to enumerate every feasible reaction stoichiometry through a mixed integer linear program (MILP). An optimal...

Pennaz, Eric James

2011-10-21

117

Optimized supply routing at Dell under non-stationary demand

This thesis describes the design and implementation of an optimization model to manage inventory at Dell's American factories. Specifically, the model is a mixed integer program which makes routing decisions on incoming ...

Foreman, John William

2008-01-01

118

An interior-point Benders based branch-and-cut algorithm for mixed integer programs

We present an interior-point branch-and-cut algorithm for structured integer programs based on Benders decomposition and the\\u000a analytic center cutting plane method (ACCPM). We show that the ACCPM based Benders cuts are both pareto-optimal and valid\\u000a for any node of the branch-and-bound tree. The valid cuts are added to a pool of cuts that is used to warm-start the solution\\u000a of

Joe Naoum-Sawaya; Samir Elhedhli

119

In this paper, we provide a general classification of mathematical optimization problems, followed by a matrix of applications that shows the areas in which these problems have been typically applied in process systems engineering. We then provide a review of solution methods of the major types of optimization problems for continuous and discrete variable optimization, particularly nonlinear and mixed-integer nonlinear

Lorenz T. Biegler; Ignacio E. Grossmann

2004-01-01

120

An infrastructure for adaptive dynamic optimization

Dynamic optimization is emerging as a promising approach to overcome many of the obstacles of traditional static compilation. But while there are a number of compiler infrastructures for developing static optimizations, there are very few for developing dynamic optimizations. We present a framework for implementing dynamic analyses and optimizations. We provide an interface for building external modules, or clients, for

Derek Bruening; Timothy Garnett; Saman P. Amarasinghe

2003-01-01

121

Optimal dynamic detection of explosives

NASA Astrophysics Data System (ADS)

We are utilizing control of molecular processes at the quantum level via the best capabilities of recent laser technology and recent discoveries in optimal shaping of laser pulses to significantly enhance the standoff detection of explosives. Optimal dynamic detection of explosives (ODD-Ex) is a methodology whereby laser pulses are optimally shaped to simultaneously enhance the sensitivity and selectivity of any of a wide variety of spectroscopic methods for explosives signatures while reducing the influence of noise and environmental perturbations. We discuss here recent results using complementary ODD-Ex methods.

Moore, D. S.; Rabitz, Herschel; McGrane, S. D.; Greenfield, M. T.; Scharff, R. J.; Chalmers, R. E.; Roslund, J.

2011-05-01

122

Optimal dynamic detection of explosives

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.

Moore, David Steven [Los Alamos National Laboratory; Mcgrane, Shawn D [Los Alamos National Laboratory; Greenfield, Margo T [Los Alamos National Laboratory; Scharff, R J [Los Alamos National Laboratory; Rabitz, Herschel A [PRINCETON UNIV; Roslund, J [PRINCETON UNIV

2009-01-01

123

Optimal dynamic detection of explosives

NASA Astrophysics Data System (ADS)

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.

Moore, D. S.; Rabitz, Herschel; McGrane, S. D.; Greenfield, M.; Scharff, R. J.; Beltrani, V.; Roslund, J.

2009-05-01

124

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

NASA Astrophysics Data System (ADS)

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 is that the resulting control law has an algebraic closed-form structure. The proposed method uses an optimal spatial statistical predictor called universal kriging to construct the surrogate model of a feedback controller, which is capable of quickly predicting an optimal control estimate based on current state (and time) information. With universal kriging, an approximation to the optimal feedback map is computed by conceptualizing a set of state-control samples from pre-computed extremals to be a particular realization of a jointly Gaussian spatial process. Feedback policies are computed for a variety of example dynamic optimization problems in order to evaluate the effectiveness of this methodology. This feedback synthesis approach is found to combine good numerical accuracy with low computational overhead, making it a suitable candidate for real-time applications. Particle swarm and universal kriging are combined for a capstone example, a near optimal, near-admissible, full-state feedback control law is computed and tested for the heat-load-limited atmospheric-turn guidance of an aeroassisted transfer vehicle. The performance of this explicit guidance scheme is found to be very promising; initial errors in atmospheric entry due to simulated thruster misfirings are found to be accurately corrected while closely respecting the algebraic state-inequality constraint.

Ghosh, Pradipto

125

Education and Optimal Dynamic Taxation

We study optimal tax and educational policies in a dynamic private information economy, in which ex-ante heterogeneous individuals make an educational investment early in their life and face a stochastic wage distribution. We characterize labor and education wedges in this setting analytically and numerically, using a calibrated example. We present ways to implement the optimum. In one implementation there is

Sebastian Findeisen; Dominik Sachs

2011-01-01

126

water using processes and water treatment operations are combined into a single network, and the design cost of each treatment unit, which is dependent on the maximum flow of wastewater handled by that treatment unit. The operating costs of the network appear in the second stage, which include the cost

Grossmann, Ignacio E.

127

DOI 10.1007/s11081-013-9226-6 A mixed-integer nonlinear program for the optimal

in alternative sources of energy for commercial building applications due to their potential to supply on generators or to take advantage of time periods in which utility prices are low. Our research considers

128

associated with volatile utility pricing and potentially high system capital costs. Energy technology and boilers), and/or thermal energy storage (e.g., hot water). For some markets, volatile utility pricing heat and power Fuel cells Building energy a b s t r a c t The distributed generation (DG) of combined

129

Optimal lines for railway systems

We discuss the optimal choice of traffic lines with periodic timetables on a railway system. A chosen line system has to offer sufficient capacity in order to serve the known amount of traffic on the system. The line optimization problem aims at the construction of a feasible line system optimizing certain objectives. We introduce a mixed integer linear programming formulation.

Michael R. Bussieck; Peter Kreuzer; Uwe T. Zimmermann

1997-01-01

130

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

The goal of this research 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.

Jeff Linderoth

2008-10-10

131

Multiobjective optimization of dynamic aperture

Dynamic aperture (DA) is one of the key nonlinear properties for a storage ring. Although there have been both analytical and numerical methods to find the aperture, the reverse problem of how to optimize it is still a challenging problem. A general and flexible way of optimizing the DA is highly demanded in accelerator design and operation. In this paper, we discuss the use of multiobjective optimization for DA. First we consider using objective functions based only on numerical tracking results. Data mining of these results demonstrated a correlation between DA and low-order nonlinear driving terms. Next we considered using objective functions which included both numerical tracking results and analytical estimates of low-order nonlinear driving terms. This resulted in faster convergence. The National Synchrotron Light Source II (NSLS-II) lattice was taken as an example to illustrate this method. This multiobjective approach is not limited by particular linear or nonlinear lattice settings, and can also be applied for optimizing other properties of a storage ring.

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

2011-05-02

132

Exact and heuristic approaches to the budget-constrained dynamic ...

Feb 2, 2012 ... Here we study a dynamic (multi-period) version of the problem, subject to a budget constraint limiting the investment in new facilities and network ... We present a mixed-integer linear programming (MIP) model generalizing ...

Abdolsalam Ghaderi

2012-02-02

133

APPROXIMATE DYNAMIC PROGRAMMING FOR OPTIMIZING OIL

CHAPTER 25 APPROXIMATE DYNAMIC PROGRAMMING FOR OPTIMIZING OIL PRODUCTION Zheng Wen, Louis J case. Components D R A F T February 17, 2012, 1:35pm D R A F T #12;2 APPROXIMATE DYNAMIC PROGRAMMING, the globally optimal control (global optimum) can be computed via dynamic programming (DP) [3]. However, most

Van Roy, Ben

134

Static and Dynamic Optimization Models in Agriculture

NSDL National Science Digital Library

Charles Moss, Associate Professor of Food and Resource Economics at the University of Florida developed this web site for his course on optimization models. The course aims to introduce students to classical optimization models, particularly mathematical programming and using optimal control theory to solve dynamic optimization models. The site provides lecture notes, slides from the lectures, assignments and solutions, and computer programs.

135

DYNAMIC RISK MANAGEMENT IN ELECTRICITY PORTFOLIO OPTIMIZATION

DYNAMIC RISK MANAGEMENT IN ELECTRICITY PORTFOLIO OPTIMIZATION VIA POLYHEDRAL RISK FUNCTIONALS the dynamic decision structure appropriately. In energy risk management, which is typically carried out ex, for integrating risk management into a stochastic optimization framework, risk has to be quantified in a definite

Eichhorn, Andreas

136

Particle Swarn Optimized Adaptive Dynamic Programming

Particle swarm optimization is used for the training of the action network and critic network of the adaptive dynamic programming approach. The typical structures of the adaptive dynamic programming and particle swarm optimization are adopted for comparison to other learning algorithms such as gradient descent method. Besides simulation on the balancing of a cart pole plant, a more complex plant

Dongbin Zhao; Jianqiang Yi; Derong Liu

2007-01-01

137

Golden optimal path in discrete-time dynamic optimization processes

is called Golden if any state moves to the next state repeating the same Golden section in each transition divisions are the Golden section. Definition 2.1 A sequence x : {0, 1, . . .} R1 is called GoldenGolden optimal path in discrete-time dynamic optimization processes Seiichi IWAMOTO and Masami

Yasuda, Masami

138

CONTROL OPTIMIZATION WITH STOCHASTIC DYNAMIC PROGRAMMING

Chapter 8 CONTROL OPTIMIZATION WITH STOCHASTIC DYNAMIC PROGRAMMING 1. Chapter Overview This chapter is to introduce the reader to classical dynamic programming in the context of solving Markov decision problems. In the next chapter, the same ideas will be presented in the context of simulation-based dynamic programming

Gosavi, Abhijit

139

Two Characterizations of Optimality in Dynamic Programming

Two Characterizations of Optimality in Dynamic Programming Ioannis Karatzas and Wiliam D. Sudderth later adapted for dynamic programming by Blackwell (1970), Hordijk (1974), Reider (1976) and Blume et al. (1982), among others. For a special class of dynamic programming problems important in economic models

Karatzas, Ioannis

140

Optimal arrival traffic spacing via dynamic programming

Optimal arrival traffic spacing via dynamic programming Alexandre M. Bayen DGA - LRBA Vernon of the spacing to perturbations. Keywords: Dynamic programming, fast-time simulation, arrival spacing. Tomlin§ Yinyu Ye¶ Jiawei Zhang Stanford University Palo Alto, CA We present the application of dynamic

141

Optimal control for singularly impulsive dynamical systems

Singularly impulsive (or generalized impulsive) dynamical systems are systems with dynamics that are characterized by the set of differential, difference and algebraic equations. They represent the class of hybrid systems, where algebraic equations represent constraints that differential and difference equations need to satisfy. For the class of singularly impulsive dynamical systems we present optimal control results. We developed unified framework

Nata A. Kablar

2005-01-01

142

TRACKING CODE DEVELOPMENT FOR BEAM DYNAMICS OPTIMIZATION

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.

Yang, L.

2011-03-28

143

Intelligent optimal control with dynamic neural networks.

The application of neural networks technology to dynamic system control has been constrained by the non-dynamic nature of popular network architectures. Many of difficulties are-large network sizes (i.e. curse of dimensionality), long training times, etc. These problems can be overcome with dynamic neural networks (DNN). In this study, intelligent optimal control problem is considered as a nonlinear optimization with dynamic equality constraints, and DNN as a control trajectory priming system. The resulting algorithm operates as an auto-trainer for DNN (a self-learning structure) and generates optimal feed-forward control trajectories in a significantly smaller number of iterations. In this way, optimal control trajectories are encapsulated and generalized by DNN. The time varying optimal feedback gains are also generated along the trajectory as byproducts. Speeding up trajectory calculations opens up avenues for real-time intelligent optimal control with virtual global feedback. We used direct-descent-curvature algorithm with some modifications (we called modified-descend-controller-MDC algorithm) for the optimal control computations. The algorithm has generated numerically very robust solutions with respect to conjugate points. The adjoint theory has been used in the training of DNN which is considered as a quasi-linear dynamic system. The updating of weights (identification of parameters) are based on Broyden-Fletcher-Goldfarb-Shanno BFGS method. Simulation results are given for an intelligent optimal control system controlling a difficult nonlinear second-order system using fully connected three-neuron DNN. PMID:12628610

Becerikli, Ya?ar; Konar, Ahmet Ferit; Samad, Tariq

2003-03-01

144

This work describes a stochastic approach for the optimal placement of sensors in municipal water networks to detect maliciously injected contaminants. The model minimizes the expected fraction of the population at risk. Our work explicity includes uncertainties in attack risks and population density, so that the resulting problem involves optimization under uncertainty. In our formulation, we include the number of

Sergio Frausto-Hernández; Urmila M. Diwekar; Salvador Hernández-Castro; Vicente Rico-Ramírez

2005-01-01

145

This work describes a stochastic approach for the optimal placement of sensors in municipal water networks to detect maliciously injected con- taminants. The model minimizes the expected fraction of the population at risk and the cost of the sensors. Our work explicitly includes uncertainties in the attack risk and population density, so that the resulting problem involves optimization under uncertainty.

Vicente Rico-ramírez; Sergio Frausto-hernández; Urmila M. Diwekar; Salvador Hernández-castro

2007-01-01

146

An optimal sizing method for cogeneration plants

An optimal planning method is proposed of the sizing problem for cogeneration system. Based on mathematical programming theory, equipment capacities are determined optimally so as to minimize the annual total cost in consideration of the plants’ annual operational strategy. The sizing problem is formulated as a mixed-integer nonlinear programming problem with the constraints of energy demands, equipment performance characteristics and

Zhang Beihong; Long Weiding

2006-01-01

147

Real-time path-planning using mixed-integer linear programming and global cost-to-go maps

With the advance in the fields of computer science, control and optimization, it is now possible to build aerial vehicles which do not need pilots. An important capability for such autonomous vehicles is to be able to ...

Toupet, Olivier

2006-01-01

148

Two Characterizations of Optimality in Dynamic Programming

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.

Karatzas, Ioannis, E-mail: ik@math.columbia.ed [Columbia University, Department of Mathematics (United States); Sudderth, William D., E-mail: bill@stat.umn.ed [University of Minnesota, School of Statistics (United States)

2010-06-15

149

The Jalapeño dynamic optimizing compiler for Java

The Jalapeiio Dynamic Optimizing Compiler is a key com- ponent of the Jalapeiio Virtual Machine, a new Java' Vir- tual Machine (JVM) designed to support efficient and scal- able execution of Java applications on SMP server machines. This paper describes the design of the Jalapefio Optimizing Compiler, and the implementation results that we have ob- tained thus far. To the

Michael G. Burke; Jong-Deok Choi; Stephen J. Fink; David Grove; Michael Hind; Vivek Sarkar; Mauricio J. Serrano; Vugranam C. Sreedhar; Harini Srinivasan; John Whaley

1999-01-01

150

Dynamic and Adjustable Particle Swarm Optimization

Particle Swarm Optimization (PSO) is a stochastic, population-based evolutionary search technique. It has difficulties in controlling the balance between exploration and exploitation. In order to improve the performance of PSO and maintain the diversities of particles, we propose a novel algorithm called Dynamic and Adjustable Particle Swarm Optimization (DAPSO). The distance from each particle to the global best position is

Chen-Yi Liao; Wei-Ping Lee; Xianghan Chen; Cheng-Wen Chiang

2007-01-01

151

Efficient dynamic optimization of logic programs

NASA Technical Reports Server (NTRS)

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.

Laird, Phil

1992-01-01

152

An Approach to Plantwide Optimization

AN APPROACH TO PLANTWIDE OPTIMIZATION RAVI NATH, BILL A WORSHAM, DALE J. LIBBY Union Carbide Corporation Houston, NlSTRACT Optimization of individual processing units as well as the energy systems has become common place in the processing... are obtained when the processing units and the plant energy system are optimized jointly, in which case the 'transfer prices' become superfluous. A MlLP (Mixed Integer Linear Programming) based approach for plant wide optimization is presented...

Nath, R.; Worsham, B. A.; Libby, D. J.

153

Optimal control of measure dynamics

NASA Astrophysics Data System (ADS)

Optimal control problem is considered in the space of measures. The general principles of solving are presented. On the basis of these principles feedback control has been suggested for satisfying the state constraint in the form of equality. The principles of solving are developed for specific problems with a state constraint. In particular, optimal control problems of heat conductivity with the state constraints as equality are considered. Feedback is constructed by using bilinear control and integral transformation. Numerical solution is proposed on the base of the method of moments.

Kuzenkov, Oleg A.; Novozhenin, Alexey V.

2015-04-01

154

Dynamic optimal reactive power flow

An efficient method for minimization of energy loss over time is presented. The proposed method uses different loading conditions during a given future time interval instead of one single snapshot of the network. The method finds the optimal conditions during the given interval. The given interval is divided into several shorter periods. By increasing the number of periods or load

S. Salamat Sharif; James H. Taylor

1998-01-01

155

Optimal Molecular Design under Property Prediction Uncertainty

nonlinearstochasticformula- tion into a deterministic MINLP problem with linear binary and convex continuous parts plethora of different potential molecular alternatives. One can already find in the literature success), mixed- integer linear optimization for linear structure-property 1250 May 1997 Vol. 43, No. 5 AICh

Maranas, Costas

156

Dynamic Memory Hierarchy Performance Optimization

Although microprocessor performance continues to in- crease at a rapid pace, the growing processor-memory speed gap threatens to limit future performance gains. In this paper, we propose a novel configurable cache and TLB as an alternative to conventional two-level hierar- chies. This organization leverages repeater insertion to provide low-cost configurability of size and speed. A novel configuration management algorithm dynamically

Rajeev Balasubramonian; David Albonesi; Alper Buyuktosunoglu; Sandhya Dwarkadas

2000-01-01

157

Methodology for simultaneous optimization with reliability: nuclear PWR example

Approaches to combining optimization and reliability usually treat the two as separate problems, determining the reliability by integer programming. The purpose of the paper is to describe a method for including reliability in the usual process optimization problem. The algorithm applied to this mixed integer problem is the adaptive random search, which can search both discrete and continuous variables simultaneously.

J. R. Campbell; J. L. Gaddy

1976-01-01

158

Role of controllability in optimizing quantum dynamics

This paper reveals an important role that controllability plays in the complexity of optimizing quantum control dynamics. We show that the loss of controllability generally leads to multiple locally suboptimal controls when gate fidelity in a quantum control system is maximized, which does not happen if the system is controllable. Such local suboptimal controls may attract an optimization algorithm into a local trap when a global optimal solution is sought, even if the target gate can be perfectly realized. This conclusion results from an analysis of the critical topology of the corresponding quantum control landscape, which refers to the gate fidelity objective as a functional of the control fields. For uncontrollable systems, due to SU(2) and SU(3) dynamical symmetries, the control landscape corresponding to an implementable target gate is proven to possess multiple locally optimal critical points, and its ruggedness can be further increased if the target gate is not realizable. These results imply that the optimization of quantum dynamics can be seriously impeded when operating with local search algorithms under these conditions, and thus full controllability is demanded.

Wu Rebing; Hsieh, Michael A.; Rabitz, Herschel [Department of Automation, Tsinghua University, Beijing, 100084, China and Center for Quantum Information Science and Technology, TNList, Beijing, 100084 (China); Department of Chemistry and Center for Quantum Information Science and Technology, University of Southern California, Los Angeles, California 90025 (United States); Department of Chemistry, Princeton University, Princeton, New Jersey 08544 (United States)

2011-06-15

159

Optimizing compressor operation with dynamic programming

Fuel consumption in natural gas compressor stations can be minimized using dynamic programming. Appropriate for installations with either reciprocating or centrifugal compressors in parallel or tandem configurations, this approach yields minimum fuel usage consistent with constraints on total throughput and operating limits on such individual parameters as speed, torque, and surge flow. The flow shares indicated by the optimization procedure

Baqui

1982-01-01

160

Particle Swarms for Dynamic Optimization Problems

Particle Swarms for Dynamic Optimization Problems Tim Blackwell1 , JÂ¨urgen Branke2 , and Xiaodong Li3 1 Department of Computing Goldsmiths College, London, UK t.blackwell@gold.ac.uk 2 Institute AIFB- ious authors [9, 7, 14, 17, 19, 20, 21, 32, 29, 38]. The overall consequence of #12;194 T. Blackwell, J

Li, Xiaodong

161

Optimal dynamic interval management in external memory

We present a space- and I/O-optimal external-memory data structure for answering stabbing queries on a set of dynamically maintained intervals. Our data structure settles an open problem in databases and I/O algorithms by providing the first optimal external-memory solution to the dynamic interval management problem, which is a special case of 2-dimensional range searching and a central problem for object-oriented and temporal databases and for constraint logic programming. Our data structure simultaneously uses optimal linear space (that is, O(N/B) blocks of disk space) and achieves the optimal O(log{sub B} N + T/B) I/O query bound and O(log{sub B} N) I/O update bound, where B is the I/O block size and T the number of elements in the answer to a query. Our structure is also the first optimal external data structure for a 2-dimensional range searching problem that has worst-case as opposed to amortized update bounds. Part of the data structure uses a novel balancing technique for efficient worst-case manipulation of balanced trees, which is of independent interest.

Arge, L.; Vitter, J.S. [Duke Univ., Durham, NC (United States)

1996-12-31

162

IMPACT OF DYNAMIC VOLTAGE SCALING (DVS) ON CIRCUIT OPTIMIZATION

Circuit designers perform optimization procedures targeting speed and power during the design of a circuit. Gate sizing can be applied to optimize for speed, while Dual-VT and Dynamic Voltage Scaling (DVS) can be applied to optimize for leakage...

Esquit Hernandez, Carlos A.

2010-01-16

163

Optimizing Motion Planning for Hyper Dynamic Manipulator

NASA Astrophysics Data System (ADS)

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.

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

2012-01-01

164

Application of optimal prediction to molecular dynamics

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 {delta}-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.

Barber IV, John Letherman

2004-12-01

165

MIXED INTEGER LINEAR PROGRAMMING FORMULATION ...

Jul 22, 2014 ... is known as the root LP relaxation and can be solved efficiently both in theory and ...... ing connectivity constraints in forest planning models, Operations ..... Scheduling of Public Transport Urban Passenger Vehicle and Crew ...

2014-07-22

166

Direct Optimal Control of Duffing Dynamics

NASA Technical Reports Server (NTRS)

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.

Oz, Hayrani; Ramsey, John K.

2002-01-01

167

Using MILP for UAVs Trajectory Optimization under Radar Detection Risk

This paper presents an approach to trajectories optimization for Unmanned Aerial Vehicle (UAV) in presence of obstacles, waypoints, and threat zones such as radar detection regions, using Mixed Integer Linear Programming (MILP). The main result is the linear approximation of a nonlinear radar detection risk function with integer constraints and indicator 0-1 variables. Several results are presented to show that

José Jaime Ruz; Orlando Arevalo; Jesús Manuel De La Cruz; Gonzalo Pajares

2006-01-01

168

Long-term optimization of cogeneration systems in a competitive market environment

A tool for long-term optimization of cogeneration systems is developed that is based on mixed integer linear-programming and Lagrangian relaxation. We use a general approach without heuristics to solve the optimization problem of the unit commitment problem and load dispatch. The possibility to buy and sell electric power at a spot market is considered as well as the possibility to

Eva Thorin; Heike Brand; Christoph Weber

2005-01-01

169

Integrated DFM Framework for Dynamic Yield Optimization

NSDL National Science Digital Library

This website includes an abstract of the following article. Users may request access to the full article via the website, and a direct link will be emailed to them. We present a new methodology for a balanced yield optimization and a new DFM (design for manufacturability) framework which implements it. Our approach allows designers to dynamically balance multiple factors contributing to yield loss and select optimal combination of DFM enhancements based on the current information about the IC layout, the manufacturing process, and known causes of failures. We bring together the information gained from layout analysis, layout aware circuit analysis, resolution enhancement and optical proximity correction tools, parasitics extraction, timing estimates, and other tools, to suggest the DFM solution which is optimized within the existing constraints on design time and available data. The framework allows us to integrate all available sources of yield information, characterize and compare proposed DFM solutions, quickly adjust them when new data or new analysis tools become available, fine tune DFM optimization for a particular design and process and provide the IC designer with a customized solution which characterizes the manufacturability of the design, identifies and classifies areas with the most opportunities for improvement, and suggests DFM improvements. The proposed methodology replaces the ad hoc approach to DFM which targets one yield loss cause at a time at the expense of other factors with a comprehensive analysis of competing DFM techniques and trade offs between them.

170

Mobile Robotic Systems: Dynamics, Control, and Optimization

NASA Astrophysics Data System (ADS)

Several classes of mobile robotic systems are discussed that are based on certain non-conventional principles of motion and can move along different surfaces and inside various media. Namely, we consider wall-climbing robots equipped with pneumatic grippers and able to move along vertical walls; snake-like multilink mechanisms with actuators installed at their joints; and vibro-robots moving in resistive media and containing movable masses. Kinematics and dynamics of these types of robots are discussed. Optimal geometrical and mechanical parameters as well as optimal periodic motions of robots are determined that correspond to the maximal average speed of locomotion. Results of experiments with prototypes of robots as well as results of computer simulation are presented. The locomotion principles analyzed are applicable to robots that can move in a complicated and hazardous environment, along different surfaces, and inside tubes.

Chernousko, F. L.

2009-08-01

171

Optimizing compressor operation with dynamic programming

Fuel consumption in natural gas compressor stations can be minimized using dynamic programming. Appropriate for installations with either reciprocating or centrifugal compressors in parallel or tandem configurations, this approach yields minimum fuel usage consistent with constraints on total throughput and operating limits on such individual parameters as speed, torque, and surge flow. The flow shares indicated by the optimization procedure may be achieved by adjusting pressure, temperature, or flow setpoints, depending on pipeline and compressor station configuration. Control may be exerted by changing compressor speed; reciprocating units can also be controlled by opening or closing the pockets.

Baqui, A.

1982-09-01

172

Optimal bolt preload for dynamic loading

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.

Duffey, T.A.

1992-08-01

173

Optimal bolt preload for dynamic loading

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.

Duffey, T.A.

1992-01-01

174

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

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

2012-01-01

175

Optimal dynamic remappping of data parallel computations

A large class of data parallel computations are characterized by a sequence of phases, with phase changes occurring unpredictably. Dynamic remapping of the workload to processors May be required to maintain good performance. The problem considered here arises when the utility of remapping and the future behavior of the workload is uncertain, phases exhibit stable execution requirements during a given phase, but requirements May change radically between phases. For these situations, a workload assignment generated for one phase May hinder performance during the next phase. This problem is treated formally for a probabilistic model of computation with at most two phases. The authors address the fundamental problem of balancing the expected remapping performance gain against the delay cost, and derive the optimal remapping decision policy. The promise of the approach is shown by application to multiprocessor implementations of an adaptive gridding fluid dynamics program, and to a battlefield simulation program.

Nicol, D.M. (Dept. of Computer Science, College of William and Mary, Williamsburg, VA (US)); Reynolds, P.F. (Institute for Parallel Computation, The Univ. of Virginia, Charlottesville, VA (US))

1990-02-01

176

Enhanced Dynamic Programming Algorithms for Series Line Optimization

1 Enhanced Dynamic Programming Algorithms for Series Line Optimization Michael H. Veatch* May 2005 Abstract Dynamic programming value iteration is made more ef cient on a ve-machine unreliable series line of optimal policies are identi ed. Index Terms Make-to-stock, production line, dynamic programming, control

Veatch, Michael H.

177

PLASMA Approximate Dynamic Programming finally cracks the locomotive optimization problem

PLASMA Â Approximate Dynamic Programming finally cracks the locomotive optimization problem programming to optimize the flows of locomotives over their networks. The problem was always to be handled if a model is going to accurately capture locomotive productivity. In addition

Powell, Warren B.

178

The lamination arrangements of moderately thick laminated composite plates for optimal dynamic characteristics are studied via a constrained multi-start global optimization technique. In the optimization process, the dynamical analysis of laminated composite plates is accomplished by utilizing a shear deformable laminated composite finite element, in which the exact expressions for determining shear correction factors were adopted and the modal damping

T. Y. Kam; F. M. Lai

1995-01-01

179

The lamination arrangements of moderately thick laminated composite plates for optimal dynamic characteristics are studied via a constrained multi-start global optimization technique. In the optimization process, the dynamical analysis of laminated composite plates is accomplished by utilizing a shear deformable laminated composite finite element, in which the exact expressions for determining shear correction factors were adopted, and the modal damping

T. Y. Kam; F. M. Lai

1995-01-01

180

An Optimal Dynamic Threat Evaluation and Weapon Scheduling Technique

NASA Astrophysics Data System (ADS)

Real time scheduling problems demand high level of flexibility and robustness under complex dynamic scenarios. Threat Evaluation (TE) and Weapon Assignment (WA), together TEWA is one such complex dynamic system having optimal or near optimal utilization of scarce defensive resources of supreme priority. Several static solutions of TEWA have been proposed. This paper discusses an optimal dynamic multi-air threat evaluation and weapon allocation algorithm using a variant of Stable Marriage Algorithm (SMA). WA uses a new dynamic weapon scheduling algorithm, allowing multiple engagements using shoot-look-shoot strategy, to compute near-optimal solution. Testing part of this paper shows feasibility of this approach for a range of scenarios.

Naeem, H.; Masood, A.

181

Optimization and Control: Examples Sheet 1 Dynamic programming

Optimization and Control: Examples Sheet 1 Dynamic programming 1. [lecture 1] Given a sequence to dynamic programming. 5. [lecture 2] (80114) The Greek adventurer Theseus is trapped in a room from which

Weber, Richard

182

Nonsmooth dynamic optimization of systems with varying structure

In this thesis, an open-loop numerical dynamic optimization method for a class of dynamic systems is developed. The structure of the governing equations of the systems under consideration change depending on the values of ...

Yunt, Mehmet, 1975-

2011-01-01

183

Dynamic optimization of a copolymerization reactor using tabu search.

A novel multistage dynamic optimization strategy based on meta-heuristic tabu search (TS) is proposed and evaluated through sequential and simultaneous implementation procedures by applying it to a semi-batch styrene-acrylonitrile (SAN) copolymerization reactor. The adaptive memory and responsive exploration features of TS are exploited to design the dynamic optimization strategy and compute the optimal control policies for temperature and monomer addition rate so as to achieve the desired product quality parameters expressed in terms of single and multiple objectives. The dynamic optimization results of TS sequential and TS simultaneous implementation strategies are analyzed and compared with those of a conventional optimization technique based on iterative dynamic programming (IDP). The simulation results demonstrate the usefulness of TS for optimal control of transient dynamic systems. PMID:25466914

Anand, P; Rao, M Bhagvanth; Venkateswarlu, Ch

2015-03-01

184

Optimal dynamic discrimination of similar quantum systems

NASA Astrophysics Data System (ADS)

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.

Li, Baiqing

2005-07-01

185

Optimal control of HIV/AIDS dynamic: Education and treatment

NASA Astrophysics Data System (ADS)

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.

Sule, Amiru; Abdullah, Farah Aini

2014-07-01

186

A model is proposed for optimizing the net benefits of removing multiple dams in U.S. watersheds of Lake Erie by quantifying impacts upon social, ecological, and economic objectives of importance to managers and stakeholders. Explicit consideration is given to the linkages between newly accessible tributary habitat and the lake's ecosystem. The model is a mixed integer linear program (MILP) that

Pearl Q. Zheng; Benjamin F. Hobbs; Joseph F. Koonce

2009-01-01

187

1 Optimal supply chain design and management over a multi-period horizon under demand uncertainty motors. Keywords: supply chain, demand uncertainty, inventory management, mixed integer non An optimization model is proposed to redesign the supply chain of spare part delivery under demand uncertainty

Grossmann, Ignacio E.

188

Static and dynamic optimization solutions for gait are practically equivalent

The proposition that dynamic optimization provides better estimates of muscle forces during gait than static optimization is examined by comparing a dynamic solution with two static solutions. A 23-degree-of-freedom musculoskeletal model actuated by 54 Hill-type musculotendon units was used to simulate one cycle of normal gait. The dynamic problem was to find the muscle excitations which minimized metabolic energy per

Frank C. Anderson; Marcus G. Pandy

2001-01-01

189

Optimal Dynamic Asset Allocation: A Stochastic Invariance Approach

Optimal asset allocation deals with how to divide the investor's wealth across some asset-classes in order to maximize the investor's gain. We consider the optimal asset allocation in a multi-period investment settings: optimal dynamic asset allocation provides the (optimal) re-balancing policy to accomplish some investment's criteria. Given a sequence of target sets, which represent the portfolio specifications at each re-balancing

Gianni Pola; Giordano Pola

2006-01-01

190

Optimal Dynamic Asset Allocation: A Stochastic Invariance Approach

Optimal Asset Allocation deals with how to divide the investor's wealth across some asset-classes in order to max- imize the investor's gain. We consider the Optimal Asset Allo- cation in a multi-period investment settings: Optimal Dynamic Asset Allocation provides the (optimal) re-balancing policy to accomplish some investment's criteria. Given a sequence of target sets, which represent the portfolio specifications at

Gianni Pol; Giordano Pol

2006-01-01

191

ASYMPTOTIC PROPERTIES OF OPTIMAL TRAJECTORIES IN DYNAMIC PROGRAMMING

ASYMPTOTIC PROPERTIES OF OPTIMAL TRAJECTORIES IN DYNAMIC PROGRAMMING SYLVAIN SORIN, XAVIER VENEL, GUILLAUME VIGERAL Abstract. We show in a dynamic programming framework that uniform convergence a dynamic programming problem as described in Lehrer and Sorin [1]. Given a set of states S

Paris-Sud XI, Université de

192

Optimal approach to quantum communication using dynamic programming

Optimal approach to quantum communication using dynamic programming Liang Jiang* , Jacob M. Taylor efficient protocols. Our approach makes use of a dynamic programming- based searching algorithm and asset management to control and estimation of dynamical systems (1). In this article we use

Nehorai, Arye

193

A Dynamic Programming Framework for Combinatorial Optimization Problems on

A Dynamic Programming Framework for Combinatorial Optimization Problems on Graphs with Bounded's performance and fault tolerance. The main technique considered in this paper is dynamic programming. I in the rest of the paper. In Section III we present a generic dynamic programming framework for solving combi

Paris-Sud XI, Université de

194

A Dynamic Programming Approach to Determining Optimal Forest Wildfire

A Dynamic Programming Approach to Determining Optimal Forest Wildfire Initial Attack Responses1 of deterministic dynamic programming, is offered as a method to search quickly through available options to find in this area was initiated by Wiitala (1986) in pioneering the use of dynamic programming to find cost

Standiford, Richard B.

195

Optimal Control of Cylindrical Plunge Grinding Using Dynamic Programming

NASA Astrophysics Data System (ADS)

An optimal grinding control scheme for cylindrical plunge grinding is proposed in this paper. The proposed grinding control scheme provides the optimal dressing and grinding parameters for batch production. The proposed control scheme consists of a G.A. (Genetic Algorithm) and dynamic programming. The optimized grinding parameters, in accordance with the state variable per cycle, are determined by the G.A. and dynamic programming is applied to ascertain the optimal grinding and dressing parameters for the overall batch. To evaluate the performance of the proposed scheme, off-line simulations based on the experimental data are conducted.

Choi, Jeongju

196

Dynamic systems of regional economy management optimization

NASA Astrophysics Data System (ADS)

One of the most actual problems of the Russian economic life is a regional economic systems formation. The hierarchy of economic and branch priorities should follow from the general idea of an industrial policy. The matter is that the concept of an industrial policy is defined by the system of priorities mainly incorporated in it. The problem of priorities is not solved yet neither on federal, nor at a regional level. It is necessary to recognize, that a substantiation of this or that variant of priorities - objectively a challenge. Such substantiation can be received with the help of dynamic structural modeling and management technology. At formation of the regional industrial policy program the special attention is given to creation of modern type commercial structures. In regions there are headquarters and branches of many largest corporations, holdings and banks. Besides it, many regional enterprises already became inter-regional or even the transnational companies. In this connection an assistance of transformation of the industrial enterprises and their groups in vertically integrated companies and modern type holdings can become a prominent aspect of an industrial policy. Regional economic structures should be reconstructed gradually on the general model of the world class competitive companies. Assistance to creation of new corporational control systems, the organization of headquarters and the central services work - all this can be included into the sphere of regional administration industrial policy. The special attention should be turned on necessity of development of own system of the corporate structures, capable to provide to the region an independent participation in use of the natural resources and industrial-technological potential, at the stage of a regional industrial policy program formation. Transformation of the industrial enterprises and their groups into modern type vertically-integrated companies and holdings can become one of the major 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-called "topographical" approach, which is used by intellectual information tec

Trofimov, S.; Kudzh, S.

197

Asymptotic Properties of Optimal Trajectories in Dynamic Programming

We prove in a dynamic programming framework that uniform convergence of the finite horizon values implies that asymptotically the average accumulated payoff is constant on optimal trajectories. We analyze and discuss several possible extensions to two-person games.

Sorin, Sylvain; Vigeral, Guillaume

2010-01-01

198

Dynamic optimization of fractionation schedules in radiation therapy

In this thesis, we investigate the improvement in treatment effectiveness when dynamically optimizing the fractionation scheme in radiation therapy. In the first part of the thesis, we consider delivering a different dose ...

Ramakrishnan, Jagdish

2013-01-01

199

Method to describe stochastic dynamics using an optimal coordinate.

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. PMID:24483410

Krivov, Sergei V

2013-12-01

200

Method to describe stochastic dynamics using an optimal coordinate

NASA Astrophysics Data System (ADS)

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.

Krivov, Sergei V.

2013-12-01

201

Noise-optimal capture for high dynamic range photography

Taking multiple exposures is a well-established approach both for capturing high dynamic range (HDR) scenes and for noise reduction. But what is the optimal set of photos to capture? The typical approach to HDR capture ...

Hasinoff, Samuel William

202

Unified approach for the optimization of nonlinear hydraulic systems

A theory for the optimization of nonlinear hydraulic systems is presented. The problem has been solved in spite of the nonlinear system model and the mixed-integer nature of the decision variables. The optimization problem is formulated in terms of the time-distribution-function concept. This leads to a numerically efficient two-level algorithm. No specific control model is needed: the algorithm employs a

B. Ulanicki; C. H. Orr

1991-01-01

203

An Optimization Framework for Dynamic, Distributed Real-Time Systems

NASA Technical Reports Server (NTRS)

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.

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

2003-01-01

204

Dynamical systems-based optimal control of incompressible fluids

For optimal control problems related to fluid flow the choice of an adequate cost functional for suppression of vortices is of significant importance. In this research we propose a cost functional based on a local dynamical systems characterization of vortices. The resulting functional is a non-convex function of the velocity gradient tensor. The resulting optimality system describing first order necessary

Michael Hintermüller; Karl Kunisch; Yulian Spasov; Stefan Volkwein

2004-01-01

205

Parallel dynamic programming for on-line flight path optimization

NASA Technical Reports Server (NTRS)

Parallel systolic algorithms for dynamic programming(DP) and their respective hardware implementations are presented for a problem in on-line trajectory optimization. The method is applied to a model for helicopter flight path optimization through a complex constraint region. This problem has application to an air traffic control problem and also to a terrain following/threat avoidance problem.

Slater, G. L.; Hu, K.

1989-01-01

206

Optimal investment models with vintage capital: Dynamic Programming approach

The Dynamic Programming approach for a family of optimal investment models with vintage capital is here developed. The problem falls into the class of infinite horizon optimal control problems of PDE's with age structure that have been studied in various papers (see e.g. [11, 12], [30, 32]) either in cases when explicit solutions can be found or using Maximum Principle

Silvia Faggian; Fausto Gozzi

2008-01-01

207

Optimal investment models with vintage capital: Dynamic programming approach

The dynamic programming approach for a family of optimal investment models with vintage capital is here developed. The problem falls into the class of infinite horizon optimal control problems of PDE’s with age structure that have been studied in various papers (Barucci and Gozzi, 1998, 2001; Feichtinger et al., 2003, 2006) either in cases when explicit solutions can be found

Silvia Faggian; Fausto Gozzi

2010-01-01

208

Dynamic Optimal Control Models in Advertising: Recent Developments

This paper presents a review of recent developments that have taken place in the area of dynamic optimal control models in advertising subsequent to the comprehensive survey of the literature by Sethi in 1977. The basic problem underlying these models is that of determining optimal advertising expenditures and possibly other variables of interest over time for a firm or a

Gustav Feichtinger; Richard F. Hartl; Suresh P. Sethi

1994-01-01

209

Dynamic Optimization in Gas Pipeline Networks EWO MEETING, Spring 2012

-based ROMeo platform. ROMeo: Rigorous On-line Modeling and Equation-based Optimization Model will provide a case study for ROMeo's dynamic optimization capabilities using the OPERA SQP solver. Generate(z,t) and q(z,t) Momentum Balance: Material Balance: Network Inventory: Node equations Flow balance

Grossmann, Ignacio E.

210

An Optimal Dynamic Mechanism for Multi-Armed Bandit Processes

We consider the problem of revenue-optimal dynamic mechanism design in settings where agents' types evolve over time as a function of their (both public and private) experience with items that are auctioned repeatedly over an infinite horizon. A central question here is under- standing what natural restrictions on the environment permit the design of optimal mechanisms (note that even in

Sham M. Kakade; Ilan Lobel; Hamid Nazerzadeh

2010-01-01

211

Vehicle dynamics applications of optimal control theory

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

R. S. Sharp; Huei Peng

2011-01-01

212

First principles molecular dynamics without self-consistent field optimization

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.

Souvatzis, Petros, E-mail: petros.souvatsiz@fysik.uu.se [Department of Physics and Astronomy, Division of Materials Theory, Uppsala University, Box 516, SE-75120 Uppsala (Sweden)] [Department of Physics and Astronomy, Division of Materials Theory, Uppsala University, Box 516, SE-75120 Uppsala (Sweden); Niklasson, Anders M. N., E-mail: amn@lanl.gov [Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States)] [Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States)

2014-01-28

213

OPTIMAL CONTROL OF ATOMIC, MOLECULAR AND ELECTRON DYNAMICS

, the dream was realized to actively exert control over quantum systems. Active control over the dynamicsChapter 9 OPTIMAL CONTROL OF ATOMIC, MOLECULAR AND ELECTRON DYNAMICS WITH TAILORED FEMTOSECOND on adaptive femtosecond quantum control where a learning algorithm and direct experimental feedback signals

Kassel, UniversitÃ¤t

214

Dynamic SLA Management with Forecasting using Multi-Objective Optimizations

Additional Key Words: Cloud Computing, IaaS, SLA Management, Resource Provisioning, Forecasting, MonitoringDynamic SLA Management with Forecasting using Multi-Objective Optimizations A.-F. Antonescu, P angewandte Mathematik, www.iam.unibe.ch #12;#12;Dynamic SLA Management with Forecasting using Multi

Braun, Torsten

215

Bridging Developmental Systems Theory and Evolutionary Psychology Using Dynamic Optimization

ERIC Educational Resources Information Center

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…

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

2013-01-01

216

DYNAMIC EMBEDDED OPTIMIZATION AND SHOOTING METHODS FOR POWER

example of hybrid systems, with in- teractions between continuous dynamics and discrete events playing, the optimization formulation in this case must capture the processes driving dynamics. This class of problems has. System oper- ators are often faced with maximizing transmission utilization subject to stability

Hiskens, Ian A.

217

A new particle swarm optimization algorithm for dynamic image clustering

In this paper, we present ACPSO a new dynamic image clustering algorithm based on particle swarm optimization. ACPSO can partition image into compact and well separated clusters without any knowledge on the real number of clusters. It uses a swarm of particles with variable number of length, which evolve dynamically using mutation operators. Experimental results on real images demonstrate that

Salima Ouadfel; Mohamed Batouche; Abdelmalik Taleb-Ahmed

2010-01-01

218

Structural optimization of rotor blades with integrated dynamics and aerodynamics

NASA Technical Reports Server (NTRS)

The problem of structural optimization of helicopter rotor blades with integrated dynamic and aerodynamic design considerations is addressed. Results of recent optimization work on rotor blades for minimum weight with constraints on multiple coupled natural flap-lag frequencies, blade autorotational inertia and centrifugal stress has been reviewed. A strategy has been defined for the ongoing activities in the integrated dynamic/aerodynamic optimization of rotor blades. As a first step, the integrated dynamic/airload optimization problem has been formulated. To calculate system sensitivity derivatives necessary for the optimization recently developed, Global Sensitivity Equations (GSE) are being investigated. A need for multiple objective functions for the integrated optimization problem has been demonstrated and various techniques for solving the multiple objective function optimization are being investigated. The method called the Global Criteria Approach has been applied to a test problem with the blade in vacuum and the blade weight and the centrifugal stress as the multiple objectives. The results indicate that the method is quite effective in solving optimization problems with conflicting objective functions.

Chattopadhyay, Aditi; Walsh, Joanne L.

1988-01-01

219

Structural optimization of rotor blades with integrated dynamics and aerodynamics

NASA Technical Reports Server (NTRS)

The problem of structural optimization of helicopter rotor blades with integrated dynamic and aerodynamic design considerations is addressed. Results of recent optimization work on rotor blades for minimum weight with constraints on multiple coupled natural flap-lag frequencies, blade autorotational inertia and centrifugal stress has been reviewed. A strategy has been defined for the ongoing activities in the integrated dynamic/aerodynamic optimization of rotor blades. As a first step, the integrated dynamic/airload optimization problem has been formulated. To calculate system sensitivity derivatives necessary for the optimization recently developed, Global Sensitivity Equations (GSE) are being investigated. A need for multiple objective functions for the integrated optimization problem has been demonstrated and various techniques for solving the multiple objective function optimization are being investigated. The method called the Global Criteria Approach has been applied to a test problem with the blade in vacuum and the blade weight and the centrifugal stress as the multiple objectives. The results indicate that the method is quite effective in solving optimization problems with conflicting objective functions.

Chattopadhyay, Aditi; Walsh, Joanne L.

1989-01-01

220

Fault tolerant and dynamic evolutionary optimization engines

Mimicking natural evolution to solve hard optimization problems has played an important role in the artificial intelligence arena. Such techniques are broadly classified as Evolutionary Algorithms (EAs) and have been ...

Morales Reyes, Alicia

2011-01-01

221

Solving dynamic control problems via deterministic global optimization

A significant multi-stage stochastic program from the area of financial planning is posed as a nonlinear stochastic control problem. The dynamic policy, called fixed-mix, results in a nonconvex optimization model. A deterministic global optimization algorithm specialized for this problem class produces a guaranteed optimal solution for realistic size applications. The proposed branch and bound type deterministic algorithm guarantees finite {element_of}-convergence to the global solution through the successive refinement of converging lower and upper bounds on the solution. These bounds are obtained through a novel convex lowering bounding and the subsequent solution of a series of nonlinear convex optimization problems. Computational results obtained with an efficient C implementation of the proposed procedure GLOFP, demonstrate the efficiency of the approach on a set of real world financial planning problems. These tests confirm that local optimization methods are prone to erroneously underestimate the efficient frontier. The concepts can be readily extended to other non-convex dynamic policies.

Mulvey, J.; Maranas, C.; Androulakis, I.P.; Floudas, C.; Berger, A.

1994-12-31

222

Application of dynamic merit function to nonimaging systems optimization

NASA Astrophysics Data System (ADS)

Automatic optimization algorithms have been recently introduced as nonimaging optics design techniques. Unlike optimization of imaging systems, nonsequential ray tracing simulations and complex noncentered systems design must be considered, adding complexity to the problem. The merit function is a key element in the automatic optimization algorithm; nevertheless, the selection of each objective's weight, {wi}, inside the merit function needs a prior trial and error process for each optimization. The problem then is to determine appropriate weights' values for each objective. We propose a new dynamic merit function with variable weight factors {wi(n)}. The proposed algorithm automatically adapts weight factors during the evolution of the optimization process. This dynamic merit function avoids the previous trial and error procedure by selecting the right merit function and provides better results than conventional merit functions.

Fernández-Balbuena, Antonio Álvarez; Montes, Mario González; García-Botella, Angel; Vázquez-Moliní, Daniel

2015-02-01

223

Dynamic optimization of metabolic networks coupled with gene expression.

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. PMID:25451533

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

2015-01-21

224

Optimal dynamic allocation of conservation funding among priority regions.

The optimal allocation of conservation resources between biodiverse conservation regions has generally been calculated using stochastic dynamic programming, or using myopic heuristics. These solutions are hard to interpret and may not be optimal. To overcome these two limitations, this paper approaches the optimal conservation resource allocation problem using optimal control theory. A solution using Pontryagin's maximum principle provides novel insight into the general properties of efficient conservation resource allocation strategies, and allows more extensive testing of the performance of myopic heuristics. We confirmed that a proposed heuristic (minimize short-term loss) yields near-optimal results in complex allocation situations, and found that a qualitative allocation feature observed in previous analyses (bang-bang allocation) is a general property of the optimal allocation strategy. PMID:18712571

Bode, Michael; Wilson, Kerrie; McBride, Marissa; Possingham, Hugh

2008-10-01

225

Trajectory priming with dynamic fuzzy networks in nonlinear optimal control.

Fuzzy logic systems have been recognized as a robust and attractive alternative to some classical control methods. The application of classical fuzzy logic (FL) technology to dynamic system control has been constrained by the nondynamic nature of popular FL architectures. Many difficulties include large rule bases (i.e., curse of dimensionality), long training times, etc. These problems can be overcome with a dynamic fuzzy network (DFN), a network with unconstrained connectivity and dynamic fuzzy processing units called "feurons." In this study, DFN as an optimal control trajectory priming system is considered as a nonlinear optimization with dynamic equality constraints. The overall algorithm operates as an autotrainer for DFN (a self-learning structure) and generates optimal feed-forward control trajectories in a significantly smaller number of iterations. For this, DFN encapsulates and generalizes the optimal control trajectories. By the algorithm, the time-varying optimal feedback gains are also generated along the trajectory as byproducts. This structure assists the speeding up of trajectory calculations for intelligent nonlinear optimal control. For this purpose, the direct-descent-curvature algorithm is used with some modifications [called modified-descend-controller (MDC) algorithm] for the nonlinear optimal control computations. The algorithm has numerically generated robust solutions with respect to conjugate points. The minimization of an integral quadratic cost functional subject to dynamic equality constraints (which is DFN) is considered for trajectory obtained by MDC tracking applications. The adjoint theory (whose computational complexity is significantly less than direct method) has been used in the training of DFN, which is as a quasilinear dynamic system. The updating of weights (identification of DFN parameters) are based on Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. Simulation results are given for controlling a difficult nonlinear second-order system using fully connected three-feuron DFN. PMID:15384531

Becerikli, Yasar; Oysal, Yusuf; Konar, Ahmet Ferit

2004-03-01

226

Fully integrated aerodynamic/dynamic optimization of helicopter rotor blades

NASA Technical Reports Server (NTRS)

This paper describes a fully integrated aerodynamic/dynamic optimization procedure for helicopter rotor blades. The procedure combines performance and dynamics 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 maneuver; 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.

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

1992-01-01

227

Techniques and tools for dynamic optimization

Traditional code optimizers have produced significant per- formance improvements over the past forty years. While promising avenues of research still exist, traditional static and profiling techniques have reached the point of diminish- ing returns. The main problem is that these approaches have only a limited view of the program and have difficulty taking advantage of the actual run-time behavior of

Jason D. Hiser; Naveen Kumar; Min Zhao; Shukang Zhou; Bruce R. Childers; Jack W. Davidson; Mary Lou Soffa

2006-01-01

228

Optimal disturbance rejection control for nonlinear impulsive dynamical systems

In this paper, we develop an optimality-based framework for addressing the problem of nonlinear–nonquadratic hybrid control for disturbance rejection of nonlinear impulsive dynamical systems with bounded exogenous disturbances. Specifically, we transform a given nonlinear–nonquadratic hybrid performance criterion to account for system disturbances. As a consequence, the disturbance rejection problem is translated into an optimal hybrid control problem. Furthermore, the resulting

Wassim M. Haddad; Nataša A. Kablar; VijaySekhar Chellaboina; Sergey G. Nersesov

2005-01-01

229

Global dynamic optimization approach to predict activation in metabolic pathways

Background During the last decade, a number of authors have shown that the genetic regulation of metabolic networks may follow optimality principles. Optimal control theory has been succesfully used to compute optimal enzyme profiles considering simple metabolic pathways. However, applying this optimal control framework to more general networks (e.g. branched networks, or networks incorporating enzyme production dynamics) yields problems that are analytically intractable and/or numerically very challenging. Further, these previous studies have only considered a single-objective framework. Results In this work we consider a more general multi-objective formulation and we present solutions based on recent developments in global dynamic optimization techniques. We illustrate the performance and capabilities of these techniques considering two sets of problems. First, we consider a set of single-objective examples of increasing complexity taken from the recent literature. We analyze the multimodal character of the associated non linear optimization problems, and we also evaluate different global optimization approaches in terms of numerical robustness, efficiency and scalability. Second, we consider generalized multi-objective formulations for several examples, and we show how this framework results in more biologically meaningful results. Conclusions The proposed strategy was used to solve a set of single-objective case studies related to unbranched and branched metabolic networks of different levels of complexity. All problems were successfully solved in reasonable computation times with our global dynamic optimization approach, reaching solutions which were comparable or better than those reported in previous literature. Further, we considered, for the first time, multi-objective formulations, illustrating how activation in metabolic pathways can be explained in terms of the best trade-offs between conflicting objectives. This new methodology can be applied to metabolic networks with arbitrary topologies, non-linear dynamics and constraints. PMID:24393148

2014-01-01

230

Dynamic Programming for Optimization of Timber Production and Grazing in

Dynamic programming procedures are presented for optimizing thinning and rota- tion of even-aged ponderosa pine by using the four descriptors: age, basal area, number of trees, and time since thinning. Because both timber yield and grazing yield are functions of stand density, the two outputs--forage and timber---can both be optimized. The soil expectation values for single and joint production are

J. DOUGLAS BRODIE; DAVID W. HANN

231

Optimal entangling capacity of dynamical processes

We investigate the entangling capacity of dynamical operations when provided with local ancilla. A comparison is made between the entangling capacity with and without the assistance of prior entanglement. An analytic solution is found for the log-negativity entangling capacity of two-qubit gates, which equals the entanglement of the Choi matrix isomorphic to the unitary operator. Surprisingly, the availability of prior entanglement does not affect this result, a property we call resource independence of the entangling capacity. We prove several useful upper bounds on the entangling capacity that hold for general qudit dynamical operations and for a whole family of entanglement monotones including log negativity and log robustness. The log-robustness entangling capacity is shown to be resource independent for general dynamics. We provide numerical results supporting a conjecture that the log-negativity entangling capacity is resource independent for all two-qudit unitary operators.

Campbell, Earl T. [Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT (United Kingdom)

2010-10-15

232

A comparison of static and dynamic optimization muscle force predictions during wheelchair t The primary purpose of this study was to compare static and dynamic optimization muscle force and work and net joint moments from the dynamic optimization were used as inputs into the static optimization

233

Optimal stabilization policy in a model of elasticity dynamics

This paper considers the role of optimal fiscal policy in the context of a macrodynamic model of the open economy. The dynamics of the model are governed by the transition of aggregate demand elasticities from their short-run values to long-run values. If there are no instrument costs attributed to government expenditure, then optimal fiscal policy can achieve perfect stabilization of price and exchange-rate levels. With instrument costs however, this is no longer possible and the optimal fiscal rule is of the linear feedback variety. The paper investigates the properties of this rule.

Bhandari, J.S.; Hanson, D.A.

1983-01-01

234

MULTIOBJECTIVE DYNAMIC APERTURE OPTIMIZATION AT NSLS-II

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.

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

2011-03-28

235

Speeding up critical system dynamics through optimized evolution

The number of defects which are generated upon crossing a quantum phase transition can be minimized by choosing properly designed time-dependent pulses. In this work we determine what are the ultimate limits of this optimization. We discuss under which conditions the production of defects across the phase transition is vanishing small. Furthermore we show that the minimum time required to enter this regime is T{approx}{pi}/{Delta}, where {Delta} is the minimum spectral gap, unveiling an intimate connection between an optimized unitary dynamics and the intrinsic measure of the Hilbert space for pure states. Surprisingly, the dynamics is nonadiabatic; this result can be understood by assuming a simple two-level dynamics for the many-body system. Finally we classify the possible dynamical regimes in terms of the action s=T{Delta}.

Caneva, Tommaso [International School for Advanced Studies (SISSA), Via Beirut 2-4, I-34014 Trieste (Italy); Institut fuer Quanteninformationsverarbeitung, Universitaet Ulm, D-89069 Ulm (Germany); Calarco, Tommaso; Montangero, Simone [Institut fuer Quanteninformationsverarbeitung, Universitaet Ulm, D-89069 Ulm (Germany); Fazio, Rosario [NEST, Scuola Normale Superiore and Istituto di Nanoscienze-CNR, Piazza dei Cavalieri 7, I-56126 Pisa (Italy); Santoro, Giuseppe E. [International School for Advanced Studies (SISSA), Via Beirut 2-4, I-34014 Trieste (Italy); CNR-INFM Democritos National Simulation Center, Via Beirut 2-4, I-34014 Trieste (Italy); International Centre for Theoretical Physics (ICTP), P.O. Box 586, I-34014 Trieste (Italy)

2011-07-15

236

A cavity approach to optimization and inverse dynamical problems

In these two lectures we shall discuss how the cavity approach can be used efficiently to study optimization problems with global (topological) constraints and how the same techniques can be generalized to study inverse problems in irreversible dynamical processes. These two classes of problems are formally very similar: they both require an efficient procedure to trace over all trajectories of either auxiliary variables which enforce global constraints, or directly dynamical variables defining the inverse dynamical problems. We will mention three basic examples, namely the Minimum Steiner Tree problem, the inverse threshold linear dynamical problem, and the zero patient problem in epidemic cascades. All these examples are root problems in optimization and inference over networks. They appear in many modern applications and in a variety of different contexts. Credit for these results should be shared with A. Braunstein, A. Ramezanpour, F. Altarelli, L. Dall'Asta, and A. Lage-Castellanos.

Lage-Castellanos, Alejandro; Zecchina, Riccardo

2014-01-01

237

Dynamic Optimal Design of Groundwater Remediation Using Genetic Algorithms

The use of genetic algorithms for the dynamic optimal design of pump-and-treat groundwater remediation systems is demonstrated\\u000a through two new dynamic formulations. In the first formulation in which the contaminant sorption was assumed to be in equilibrium,\\u000a the lengths of management periods were decision variables. The second formulation assumed a pulsed pumping approach to remove\\u000a a contaminant with mass-transfer-limited sorption.

Amy Chan Hilton; Aysegul Aksoy; Teresa B. Culver

238

Dynamically mapping screen real estate optimality

This research paper brings together the fields of systems engineering and media studies to investigate the cinema\\/television\\/computer\\/mobile device screen as a dynamic interface through which points of engagement or how the aesthetics and narrative structures presented on the screen engage the user and create meaning. The co-authors work towards the development of a “screen real estate grammar” or ontology by

Luigi Benedicenti; Sheila Petty

2010-01-01

239

Optimal dynamic remapping of parallel computations

NASA Technical Reports Server (NTRS)

A large class of computations are characterized by a sequence of phases, with phase changes occurring unpredictably. The decision problem was considered regarding the remapping of workload to processors in a parallel computation when the utility of remapping and the future behavior of the workload is uncertain, and phases exhibit stable execution requirements during a given phase, but requirements may change radically between phases. For these problems a workload assignment generated for one phase may hinder performance during the next phase. This problem is treated formally for a probabilistic model of computation with at most two phases. The fundamental problem of balancing the expected remapping performance gain against the delay cost was addressed. Stochastic dynamic programming is used to show that the remapping decision policy minimizing the expected running time of the computation has an extremely simple structure. Because the gain may not be predictable, the performance of a heuristic policy that does not require estimnation of the gain is examined. The heuristic method's feasibility is demonstrated by its use on an adaptive fluid dynamics code on a multiprocessor. The results suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change. The results also suggest that this heuristic is applicable to computations with more than two phases.

Nicol, David M.; Reynolds, Paul F., Jr.

1987-01-01

240

Dynamic optimization of district energy grid

NASA Astrophysics Data System (ADS)

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.

Salsbery, Scott

241

Structural dynamics test simulation and optimization for aerospace components

This paper initially describes an innovative approach to product realization called Knowledge Based Testing (KBT). This research program integrates test simulation and optimization software, rapid fabrication techniques and computational model validation to support a new experimentally-based design concept. This design concept implements well defined tests earlier in the design cycle enabling the realization of highly reliable aerospace components. A test simulation and optimization software environment provides engineers with an essential tool needed to support this KBT approach. This software environment, called the Virtual Environment for Test Optimization (VETO), integrates analysis and test based models to support optimal structural dynamic test design. A goal in developing this software tool is to provide test and analysis engineers with a capability of mathematically simulating the complete structural dynamics test environment within a computer. A developed computational model of an aerospace component can be combined with analytical and/or experimentally derived models of typical structural dynamic test instrumentation within the VETO to determine an optimal test design. The VETO provides the user with a unique analysis and visualization environment to evaluate new and existing test methods in addition to simulating specific experiments designed to maximize test based information needed to validate computational models. The results of both a modal and a vibration test design are presented for a reentry vehicle and a space truss structure.

Klenke, S.E.; Baca, T.J.

1996-06-01

242

Aerospace applications of integer and combinatorial optimization

NASA Technical Reports Server (NTRS)

Research supported by NASA Langley Research Center includes many applications of aerospace design optimization and is conducted by teams of applied mathematicians and aerospace engineers. This paper investigates the benefits from this combined expertise in solving combinatorial optimization problems. Applications range from the design of large space antennas to interior noise control. A typical problem, for example, seeks the optimal locations for vibration-damping devices on a large space structure and is expressed as a mixed/integer linear programming problem with more than 1500 design variables.

Padula, S. L.; Kincaid, R. K.

1995-01-01

243

Aerospace applications on integer and combinatorial optimization

NASA Technical Reports Server (NTRS)

Research supported by NASA Langley Research Center includes many applications of aerospace design optimization and is conducted by teams of applied mathematicians and aerospace engineers. This paper investigates the benefits from this combined expertise in formulating and solving integer and combinatorial optimization problems. Applications range from the design of large space antennas to interior noise control. A typical problem. for example, seeks the optimal locations for vibration-damping devices on an orbiting platform and is expressed as a mixed/integer linear programming problem with more than 1500 design variables.

Padula, S. L.; Kincaid, R. K.

1995-01-01

244

Aerospace Applications of Integer and Combinatorial Optimization

NASA Technical Reports Server (NTRS)

Research supported by NASA Langley Research Center includes many applications of aerospace design optimization and is conducted by teams of applied mathematicians and aerospace engineers. This paper investigates the benefits from this combined expertise in formulating and solving integer and combinatorial optimization problems. Applications range from the design of large space antennas to interior noise control. A typical problem, for example, seeks the optimal locations for vibration-damping devices on an orbiting platform and is expressed as a mixed/integer linear programming problem with more than 1500 design variables.

Padula, S. L.; Kincaid, R. K.

1995-01-01

245

Dynamic cellular manufacturing systems design—a comprehensive model

This paper addresses the dynamic cell formation problem (DCF). In dynamic environment, the product demand and mix changes\\u000a in each period of a multiperiod planning horizon. It causes need of reconfiguration of cells to respond to the product demand\\u000a and mix change in each period. This paper proposes a mixed-integer nonlinear programming model to design the dynamic cellular\\u000a manufacturing systems

Lokesh Kumar Saxena; Promod Kumar Jain

2011-01-01

246

Nonlinear impulsive dynamical systems. II. Feedback interconnections and optimality

For part I, see ibid. In part I, Lyapunov and invariant set theorems, and dissipativity theory were developed for nonlinear impulsive dynamical systems. In this part we build on these results to develop general stability criteria for feedback interconnections of nonlinear impulsive systems. In addition, a unified framework for hybrid feedback optimal control involving a hybrid nonlinear-nonquadratic performance functional is

W. M. Haddad; V. Chellaboina; N. A. Kablar

1999-01-01

247

Book Corrections for Optimal Estimation of Dynamic Systems, 2nd

L. Junkins March 19, 2014 This document provides corrections for the book: Crassidis, J.L., and Junkins, J.L., Optimal Estimation of Dynamics Systems, 2nd Edi- tion, CRC Press, Boca Raton, FL, 2011. Any Station, TX 77843-3141. E-mail: junkins@tamu.edu. 1 #12;Chapter 6 · The MATLAB code for Example 6

Crassidis, John L.

248

Book Corrections for Optimal Estimation of Dynamic Systems

Book Corrections for Optimal Estimation of Dynamic Systems John L. Crassidis and John L. Junkins November 14, 2011 This document provides corrections for the book: Crassidis, J.L., and Junkins, J, Texas A&M University, College Station, TX 77843-3141. E-mail: junkins@tamu.edu. 1 #12;· Equation (2

Crassidis, John L.

249

Optimal Real Consumption and Investment Strategies in Dynamic Stochastic Economies

Abstract. We derive optimal consumption and investment strategies of an investor with CRRA utility of consumption and\\/or terminal wealth and with access to trade in a complete, but otherwise very general, nancial market. Interest rates, excess expected returns, price volatilities, correlations, and con- sumer prices may all evolve stochastically over time, even with non-Markovian dynamics. Our result pinpoints exactly what

Claus Munk; Carsten Srensen

2003-01-01

250

HIV Dynamics: Modeling, Data Analysis, and Optimal Treatment Protocols

HIV Dynamics: Modeling, Data Analysis, and Optimal Treatment Protocols B. M. Adams 1 , H. T. Banks in model- ing HIV pathogenesis. After a brief discussion of motivation for and previous efforts in the development of mathematical models for progression of HIV infection and treatment, we discuss mathematical

251

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

NASA Technical Reports Server (NTRS)

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.

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

2011-01-01

252

Preserving electron spin coherence in solids by optimal dynamical decoupling

NASA Astrophysics Data System (ADS)

To exploit the quantum coherence of electron spins in solids in future technologies such as quantum computing, it is first vital to overcome the problem of spin decoherence due to their coupling to the noisy environment. Dynamical decoupling, which uses stroboscopic spin flips to give an average coupling to the environment that is effectively zero, is a particularly promising strategy for combating decoherence because it can be naturally integrated with other desired functionalities, such as quantum gates. Errors are inevitably introduced in each spin flip, so it is desirable to minimize the number of control pulses used to realize dynamical decoupling having a given level of precision. Such optimal dynamical decoupling sequences have recently been explored. The experimental realization of optimal dynamical decoupling in solid-state systems, however, remains elusive. Here we use pulsed electron paramagnetic resonance to demonstrate experimentally optimal dynamical decoupling for preserving electron spin coherence in irradiated malonic acid crystals at temperatures from 50K to room temperature [1]. Using a seven-pulse optimal dynamical decoupling sequence, we prolonged the spin coherence time to about 30 ms; it would otherwise be about 0.04 ms without control or 6.2 ms under one-pulse control. By comparing experiments with microscopic theories, we have identified the relevant electron spin decoherence mechanisms in the solid. Recently, we demonstrate experimentally that dynamical decoupling can preserve bipartite pseudo-entanglement in phosphorous donors in a silicon system [2]. In particular, the lifetime of pseudo entangled states is extended from 0.4 us in the absence of decoherence control to 30 us in the presence of a two-flip dynamical decoupling sequence. [4pt] [1]. Jiangfeng Du, Xing Rong, Nan Zhao, Ya Wang, Jiahui Yang and R. B. Liu, Preserving electron spin coherence in solids by optimal dynamical decoupling, Nature 461, 1265-1268 (2009). [0pt] [2] Ya Wang, Xing Rong, Pengbo Feng, Wanjie Xu, Bo Chong, Ji-Hu Su, Jiangbin Gong, and Jiangfeng Du, Preservation of bipartite pseudo-entanglement in solids using dynamical decoupling, submitted to Phys. Rev. Lett.

Du, Jiangfeng

2011-03-01

253

A dynamic optimization model for solid waste recycling.

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. PMID:23158873

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

2013-02-01

254

Analysis and optimization of pulse dynamics for magnetic stimulation.

Magnetic stimulation is a standard tool in brain research and has found important clinical applications in neurology, psychiatry, and rehabilitation. Whereas coil designs and the spatial field properties have been intensively studied in the literature, the temporal dynamics of the field has received less attention. Typically, the magnetic field waveform is determined by available device circuit topologies rather than by consideration of what is optimal for neural stimulation. This paper analyzes and optimizes the waveform dynamics using a nonlinear model of a mammalian axon. The optimization objective was to minimize the pulse energy loss. The energy loss drives power consumption and heating, which are the dominating limitations of magnetic stimulation. The optimization approach is based on a hybrid global-local method. Different coordinate systems for describing the continuous waveforms in a limited parameter space are defined for numerical stability. The optimization results suggest that there are waveforms with substantially higher efficiency than that of traditional pulse shapes. One class of optimal pulses is analyzed further. Although the coil voltage profile of these waveforms is almost rectangular, the corresponding current shape presents distinctive characteristics, such as a slow low-amplitude first phase which precedes the main pulse and reduces the losses. Representatives of this class of waveforms corresponding to different maximum voltages are linked by a nonlinear transformation. The main phase, however, scales with time only. As with conventional magnetic stimulation pulses, briefer pulses result in lower energy loss but require higher coil voltage than longer pulses. PMID:23469168

Goetz, Stefan M; Truong, Cong Nam; Gerhofer, Manuel G; Peterchev, Angel V; Herzog, Hans-Georg; Weyh, Thomas

2013-01-01

255

Beam Dynamics Optimization for the Xfel Photo Injector

NASA Astrophysics Data System (ADS)

The main challenge for the European XFEL photo injector is the production of 1 nC electron beams with a normalized transverse emittance of 0.9 mm mrad. The photo injector setup consists of a 1.5-cell L-band rf gun cavity supplied with solenoids for beam focusing and emittance compensation and the first accelerating section with 8 TESLA superconducting cavities. The first 4 cavities are used as a booster to provide by proper choice of its position, gradient and phase matching conditions for the emittance conservation. For optimization of the beam dynamics in the photo injector, a staged algorithm, based on ASTRA simulations, has been developed. The first stage considers the emission of electrons from a photo cathode. The cathode laser energy and its transverse parameters are adjusted to produce a bunch charge of 1 nC in presence of space charge forces (including image charge at the cathode) and Schottky-like effects. The second stage contains rf gun cavity and solenoid optimization. The booster position, gradient and initial phase are optimized at the third stage yielding the minimum emittance at the photo injector exit. Results of the XFEL photo injector optimization will be presented. Besides simulations experimental studies towards XFEL photo injector are carried out. The photo injector test facility at DESY in Zeuthen (PITZ) develops photo injectors for FELs, including FLASH and the European XFEL. A thorough comparison of measured data with results of beam dynamics simulations is one of the main PITZ goals. Detailed experimental studies on photo emission processes, thermal emittance, transverse and longitudinal phase space of the electron beam are being performed together with beam dynamics simulations. This aims to result in better understanding of beam dynamics in high brightness photo injectors. Experimentally obtained photo injector characteristics (like thermal emittance) have to be used in an additional optimization of the photo injector resulting in more realistic beam dynamics simulations. Results of these studies will be reported as well.

Krasilnikov, Mikhail

256

Optimal Control of HIV Dynamic Using Embedding Method

This present study proposes an optimal control problem, with the final goal of implementing an optimal treatment protocol which could maximize the survival time of patients and minimize the cost of drug utilizing a system of ordinary differential equations which describes the interaction of the immune system with the human immunodeficiency virus (HIV). Optimal control problem transfers into a modified problem in measure space using an embedding method in which the existence of optimal solution is guaranteed by compactness of the space. Then the metamorphosed problem is approximated by a linear programming (LP) problem, and by solving this LP problem a suboptimal piecewise constant control function, which is more practical from the clinical viewpoint, is achieved. The comparison between the immune system dynamics in treated and untreated patients is introduced. Finally, the relationships between the healthy cells and virus are shown. PMID:21687584

Zarei, H.; Kamyad, A. V.; Farahi, M. H.

2011-01-01

257

Optimal control of HIV dynamic using embedding method.

This present study proposes an optimal control problem, with the final goal of implementing an optimal treatment protocol which could maximize the survival time of patients and minimize the cost of drug utilizing a system of ordinary differential equations which describes the interaction of the immune system with the human immunodeficiency virus (HIV). Optimal control problem transfers into a modified problem in measure space using an embedding method in which the existence of optimal solution is guaranteed by compactness of the space. Then the metamorphosed problem is approximated by a linear programming (LP) problem, and by solving this LP problem a suboptimal piecewise constant control function, which is more practical from the clinical viewpoint, is achieved. The comparison between the immune system dynamics in treated and untreated patients is introduced. Finally, the relationships between the healthy cells and virus are shown. PMID:21687584

Zarei, H; Kamyad, A V; Farahi, M H

2011-01-01

258

Particle swarm optimization with composite particles in dynamic environments.

In recent years, there has been a growing interest in the study of particle swarm optimization (PSO) in dynamic environments. This paper presents a new PSO model, called PSO with composite particles (PSO-CP), to address dynamic optimization problems. PSO-CP partitions the swarm into a set of composite particles based on their similarity using a "worst first" principle. Inspired by the composite particle phenomenon in physics, the elementary members in each composite particle interact via a velocity-anisotropic reflection scheme to integrate valuable information for effectively and rapidly finding the promising optima in the search space. Each composite particle maintains the diversity by a scattering operator. In addition, an integral movement strategy is introduced to promote the swarm diversity. Experiments on a typical dynamic test benchmark problem provide a guideline for setting the involved parameters and show that PSO-CP is efficient in comparison with several state-of-the-art PSO algorithms for dynamic optimization problems. PMID:20371407

Liu, Lili; Yang, Shengxiang; Wang, Dingwei

2010-12-01

259

Adaptive optimal spectral range for dynamically changing scene

NASA Astrophysics Data System (ADS)

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.

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

2012-06-01

260

Label free optimal dynamic discrimination of biological macromolecules

NASA Astrophysics Data System (ADS)

The fast development of laser techniques, in particular, the generation of ultrashort femtosecond and even attosecond pulses opens new frontiers and various experimental tools for biomedical applications. The combination of pulse shaping and optimal control is a very promising tool based on coherent manipulation of wavepackets on an ultrafast time scale. It already has successfully been applied for optimal dynamic discrimination (ODD) experiments of biomolecules like free amino acids and flavins which are indistinguishable by spectroscopic means. This approach can be extended toward to label free cellular imaging and detection of chemical or biological substances.

Afonina, S.; Rondi, A.; Kiselev, D.; Bonacina, L.; Wolf, J. P.

2013-03-01

261

Set-valued dynamic treatment regimes for competing outcomes

Summary Dynamic treatment regimes operationalize the clinical decision process as a sequence of functions, one for each clinical decision, where each function maps up-to-date patient information to a single recommended treatment. Current methods for estimating optimal dynamic treatment regimes, for example Q-learning, require the specification of a single outcome by which the ‘goodness’ of competing dynamic treatment regimes is measured. However, this is an over-simplification of the goal of clinical decision making, which aims to balance several potentially competing outcomes, e.g., symptom relief and side-effect burden. When there are competing outcomes and patients do not know or cannot communicate their preferences, formation of a single composite outcome that correctly balances the competing outcomes is not possible. This problem also occurs when patient preferences evolve over time. We propose a method for constructing dynamic treatment regimes that accommodates competing outcomes by recommending sets of treatments at each decision point. Formally, we construct a sequence of set-valued functions that take as input up-to-date patient information and give as output a recommended subset of the possible treatments. For a given patient history, the recommended set of treatments contains all treatments that produce non-inferior outcome vectors. Constructing these set-valued functions requires solving a non-trivial enumeration problem. We offer an exact enumeration algorithm by recasting the problem as a linear mixed integer program. The proposed methods are illustrated using data from the CATIE schizophrenia study. PMID:24400912

Laber, Eric B.; Lizotte, Daniel J.; Ferguson, Bradley

2014-01-01

262

Airframe structural dynamic considerations in rotor design optimization

NASA Technical Reports Server (NTRS)

An an overview and discussion of those aspects of airframe structural dynamics that have a strong influence on rotor design optimization is provided. Primary emphasis is on vibration requirements. The vibration problem is described, the key vibratory forces are identified, the role of airframe response in rotor design is summarized, and the types of constraints which need to be imposed on rotor design due to airframe dynamics are discussed. Some considerations of ground and air resonance as they might affect rotor design are included.

Kvaternik, Raymond G.; Murthy, T. Sreekanta

1989-01-01

263

Optimizing airport runway improvement program - A dynamic programming approach

NASA Technical Reports Server (NTRS)

In order to reduce the air traffic delay in the terminal area, an immediate remedy is to increase airport capacity by an expansion of the existing runway system. The runway expansion program is often limited by budgetary constraints; the expensive facilities for a long-term improvement cannot be built at once. When a runway improvement strategy is being considered for a longer planning horizon, the investiment decision depends upon the interrelations of its composite periods. The problem, therefore, is to determine how time factor and investment decisions interact to yield an optimal improvement scheme that meets demand at a minimum cost. With this objective in mind, a dynamic programming methodology is employed to determine the optimal planning scheme. Also, an example runway improvement problem is tested to illustrate how a dynamic programming model is practical in actual application.

Yu, J. C.; Gibson, D. R.

1975-01-01

264

Exploring the capabilities of quantum optimal dynamic discrimination

NASA Astrophysics Data System (ADS)

Optimal dynamic discrimination (ODD) uses closed-loop learning control techniques to discriminate between similar quantum systems. ODD achieves discrimination by employing a shaped control (laser) pulse to simultaneously exploit the unique quantum dynamics particular to each system, even when they are quite similar. In this work, ODD is viewed in the context of multiobjective optimization, where the competing objectives are the degree of similarity of the quantum systems and the level of controlled discrimination that can be achieved. To facilitate this study, the D-MORPH gradient algorithm is extended to handle multiple quantum systems and multiple objectives. This work explores the trade-off between laser resources (e.g., the length of the pulse, fluence, etc.) and ODD's ability to discriminate between similar systems. A mechanism analysis is performed to identify the dominant pathways utilized to achieve discrimination between similar systems.

Beltrani, Vincent; Ghosh, Pritha; Rabitz, Herschel

2009-04-01

265

Optimal dynamic performance for high-precision actuators/stages.

System dynamic performance of actuator/stage groups, such as those found in optical instrument positioning systems and other high-precision applications, is dependent upon both individual component behavior and the system configuration. Experimental modal analysis techniques were implemented to determine the six degree of freedom stiffnesses and damping for individual actuator components. These experimental data were then used in a multibody dynamic computer model to investigate the effect of stage group configuration. Running the computer model through the possible stage configurations and observing the predicted vibratory response determined the optimal stage group configuration. Configuration optimization can be performed for any group of stages, provided there is stiffness and damping data available for the constituent pieces.

Preissner, C.; Lee, S.-H.; Royston, T. J.; Shu, D.

2002-07-03

266

Optimization Research of Generation Investment Based on Linear Programming Model

NASA Astrophysics Data System (ADS)

Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.

Wu, Juan; Ge, Xueqian

267

Optimal Control of a Parabolic Equation with Dynamic Boundary Condition

We investigate a control problem for the heat equation. The goal is to find an optimal heat transfer coefficient in the dynamic boundary condition such that a desired temperature distribution at the boundary is adhered. To this end we consider a function space setting in which the heat flux across the boundary is forced to be an L{sup p} function with respect to the surface measure, which in turn implies higher regularity for the time derivative of temperature. We show that the corresponding elliptic operator generates a strongly continuous semigroup of contractions and apply the concept of maximal parabolic regularity. This allows to show the existence of an optimal control and the derivation of necessary and sufficient optimality conditions.

Hoemberg, D., E-mail: hoemberg@wias-berlin.de; Krumbiegel, K., E-mail: krumbieg@wias-berlin.de [Weierstrass Institute for Applied Mathematics and Stochastics, Nonlinear Optimization and Inverse Problems (Germany); Rehberg, J., E-mail: rehberg@wias-berlin.de [Weierstrass Institute for Applied Mathematics and Stochastics, Partial Differential Equations (Germany)

2013-02-15

268

Extended Formulations in Mixed Integer Conic Quadratic ...

Jan 6, 2015 ... We can construct a polyhedral relaxation of Ld through its semi-infinite ..... Constraint (9c) is not convex, but because y0 is fixed to a constant, ..... Finally, a generic refinement procedure for the current branch-and-bound node ...

2015-03-05

269

Polyhedral Approaches to Mixed Integer Linear Programming

(1). This is the topic of this tutorial. 1.2 Historical perspective Babylonian tablets show. In 1809, Gauss [29] used this method in his work and presented it as a ''standard technique started analyzing systems of linear inequalities. This is a fertile ground for beautiful theories. In 1826

Cornuejols, Gerard P.

270

Polyhedral Approaches to Mixed Integer Linear Programming

of this tutorial. 1.2 Historical perspective Babylonian tablets show that mathematicians were already solving this method in his work and presented it as a "standard technique". Surprisingly, the method was subsequently inequalities. This is a fertile ground for beautiful theories. In 1826 Fourier [28] gave an algorithm

Cornuejols, Gerard P.

271

Perspective Reformulations of Mixed Integer Nonlinear Programs ...

{(x, z, v) ? Rn+2 : Ax ? b, f(x) + c ? v ? 0, ux ? x ? lx, uv ? v ? lv, z = 1} where bounds .... For example, for n = 30 and m = 200, Ipopt takes, on average, 383 CPU ..... from a factor model and has the form Q = B?BT + ?2, for a given exposure ...

2009-06-02

272

Lookahead Branching for Mixed Integer Programming

impact of the current branching decision on the bounds of the child nodes two ... In fact, a long line of integer programming research in the 1970's was fo- ...... Deutschen Mathematiker-Vereinigung, International Congress of Mathematicians

2006-10-12

273

Primal Heuristics for Mixed Integer Programs Diplomarbeit

. . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3 Start Heuristics 15 3.1 Diving Heuristics . . . . . . . . . . . . . . . . . . . . . . . . . 15 3 Results . . . . . . . . . . . . . . . . . . . . . . 66 5 Results 69 5.1 Impact of the SCIP Heuristics

GrÃ¶tschel, Martin

274

Dynamic multi-swarm particle swarm optimizer with harmony search

In this paper, the dynamic multi-swarm particle swarm optimizer (DMS-PSO) is improved by hybridizing it with the harmony search (HS) algorithm and the resulting algorithm is abbreviated as DMS-PSO-HS. We present a novel approach to merge the HS algorithm into each sub-swarm of the DMS-PSO. Combining the exploration capabilities of the DMS-PSO and the stochastic exploitation of the HS, the

Shi-Zheng Zhao; Ponnuthurai N. Suganthan; Quan-Ke Pan; Mehmet Fatih Tasgetiren

2011-01-01

275

Confronting dynamics and uncertainty in optimal decision making for conservation

NASA Astrophysics Data System (ADS)

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 critically endangered population through captive breeding, control of invasive species, construction of biodiversity reserves, design of landscapes to increase habitat connectivity, and resource exploitation. Although these decision making problems and their solutions present significant challenges, we suggest that a systematic and effective approach to dynamic decision making in conservation need not be an onerous undertaking. The requirements are shared with any systematic approach to decision making—a careful consideration of values, actions, and outcomes.

Williams, Byron K.; Johnson, Fred A.

2013-06-01

276

Optimization of Dynamic Aperture of PEP-X Baseline Design

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.

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

2010-08-23

277

Human opinion dynamics: an inspiration to solve complex optimization problems.

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

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

2013-01-01

278

Dynamic optimization of the Tennessee Eastman process using the OptControlCentre

This study focuses on the performance of large-scale nonlinear programming (NLP) solvers for the dynamic optimization in real-time of large processes. The matlab-based OptControlCentre (OCC) is coupled with large-scale optimization tools and developed for on-line, real-time dynamic optimization. To demonstrate these new developments, we consider the on-line, real-time dynamic optimization of the Tennessee Eastman (TE) challenge process in a nonlinear

Tobias Jockenhövel; Lorenz T. Biegler; Andreas Wächter

2003-01-01

279

Optimized Uncertainty Quantification Algorithm Within a Dynamic Event Tree Framework

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.

J. W. Nielsen; Akira Tokuhiro; Robert Hiromoto

2014-06-01

280

Optimizing spread dynamics on graphs by message passing

NASA Astrophysics Data System (ADS)

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).

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

2013-09-01

281

Accelerated monotonic convergence of optimal control over quantum dynamics

NASA Astrophysics Data System (ADS)

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.

Ho, Tak-San; Rabitz, Herschel

2010-08-01

282

Accelerated monotonic convergence of optimal control over quantum dynamics.

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. PMID:20866936

Ho, Tak-San; Rabitz, Herschel

2010-08-01

283

Exposure Time Optimization for Highly Dynamic Star Trackers

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. PMID:24618776

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

2014-01-01

284

A mathematical programming approach to stochastic and dynamic optimization problems

We propose three ideas for constructing optimal or near-optimal policies: (1) for systems for which we have an exact characterization of the performance space we outline an adaptive greedy algorithm that gives rise to indexing policies (we illustrate this technique in the context of indexable systems); (2) we use integer programming to construct policies from the underlying descriptions of the performance space (we illustrate this technique in the context of polling systems); (3) we use linear control over polyhedral regions to solve deterministic versions for this class of problems. This approach gives interesting insights for the structure of the optimal policy (we illustrate this idea in the context of multiclass queueing networks). The unifying theme in the paper is the thesis that better formulations lead to deeper understanding and better solution methods. Overall the proposed approach for stochastic and dynamic optimization parallels efforts of the mathematical programming community in the last fifteen years to develop sharper formulations (polyhedral combinatorics and more recently nonlinear relaxations) and leads to new insights ranging from a complete characterization and new algorithms for indexable systems to tight lower bounds and new algorithms with provable a posteriori guarantees for their suboptimality for polling systems, multiclass queueing and loss networks.

Bertsimas, D.

1994-12-31

285

Modelling the Transmission Dynamics of Hepatitis B & Optimal control

Hepatitis B is a potentially life-threatening viral infection that can cause illness and even death. The Hepatitis B virus is fifty to hundred times more infectious than HIV, and world wide an estimated two billion people have been affected (WHO2008). HBV is the most common serious viral infection and leading cause of deaths in main land in china South Asia and Africa and almost all parts of the world. Every year 300,000 people from HBV related diseases only in China. Hepatitis B is a common disease in Pakistan as every tenth person is carrier and every fifth person has been exposed to hepatitis B. We proposed a model to understand the transmission dynamics and prevalence of HBV. To control the prevalence of diseases, we use optimal control strategies, which reduce the latent, infected and carrier individuals and increase the total number of recovered and immune individuals. In order to do this, we show that an optimal control exists for this optimal control problem and then we use optimal control techniques ...

Mehmood, Nayyar

2011-01-01

286

Dynamic optimization of bioprocesses: efficient and robust numerical strategies.

The dynamic optimization (open loop optimal control) of non-linear bioprocesses is considered in this contribution. These processes can be described by sets of non-linear differential and algebraic equations (DAEs), usually subject to constraints in the state and control variables. A review of the available solution techniques for this class of problems is presented, highlighting the numerical difficulties arising from the non-linear, constrained and often discontinuous nature of these systems. In order to surmount these difficulties, we present several alternative stochastic and hybrid techniques based on the control vector parameterization (CVP) approach. The CVP approach is a direct method which transforms the original problem into a non-linear programming (NLP) problem, which must be solved by a suitable (efficient and robust) solver. In particular, a hybrid technique uses a first global optimization phase followed by a fast second phase based on a local deterministic method, so it can handle the nonconvexity of many of these NLPs. The efficiency and robustness of these techniques is illustrated by solving several challenging case studies regarding the optimal control of fed-batch bioreactors and other bioprocesses. In order to fairly evaluate their advantages, a careful and critical comparison with several other direct approaches is provided. The results indicate that the two-phase hybrid approach presents the best compromise between robustness and efficiency. PMID:15888349

Banga, Julio R; Balsa-Canto, Eva; Moles, Carmen G; Alonso, Antonio A

2005-06-29

287

Optimal approach to quantum communication using dynamic programming

Reliable preparation of entanglement between distant systems is an outstanding problem in quantum information science and quantum communication. In practice, this has to be accomplished via noisy channels (such as optical fibers) that generally result in exponential attenuation of quantum signals at large distances. A special class of quantum error correction protocols--quantum repeater protocols--can be used to overcome such losses. In this work, we introduce a method for systematically optimizing existing protocols and developing new, more efficient protocols. Our approach makes use of a dynamic programming-based searching algorithm, the complexity of which scales only polynomially with the communication distance, letting us efficiently determine near-optimal solutions. We find significant improvements in both the speed and the final state fidelity for preparing long distance entangled states.

Liang Jiang; Jacob M. Taylor; Navin Khaneja; Mikhail D. Lukin

2007-10-31

288

Optimal approach to quantum communication using dynamic programming

Reliable preparation of entanglement between distant systems is an outstanding problem in quantum information science and quantum communication. In practice, this has to be accomplished by noisy channels (such as optical fibers) that generally result in exponential attenuation of quantum signals at large distances. A special class of quantum error correction protocols, quantum repeater protocols, can be used to overcome such losses. In this work, we introduce a method for systematically optimizing existing protocols and developing more efficient protocols. Our approach makes use of a dynamic programming-based searching algorithm, the complexity of which scales only polynomially with the communication distance, letting us efficiently determine near-optimal solutions. We find significant improvements in both the speed and the final-state fidelity for preparing long-distance entangled states. PMID:17959783

Jiang, Liang; Taylor, Jacob M.; Khaneja, Navin; Lukin, Mikhail D.

2007-01-01

289

Dynamic Simulation and Optimization of Nuclear Hydrogen Production Systems

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.

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

2009-07-31

290

An Optimal Solution to a General Dynamic Jet Fuel Hedging Problem

combine dynamic programming and Kalman filter estimation to obtain an optimal policy that minimizesAn Optimal Solution to a General Dynamic Jet Fuel Hedging Problem Juliana M. Nascimento Warren B #12;Abstract We propose a dynamic hedging strategy for jet fuel which strikes a balance between

Powell, Warren B.

291

Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

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.

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

2015-01-01

292

Data-driven optimization of dynamic reconfigurable systems of systems.

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.

Tucker, Conrad S.; Eddy, John P.

2010-11-01

293

Parallel and Distributed Optimization of Dynamic Data Structures for Multimedia Embedded Systems

Energy-efficient design of multimedia embedded systems demands optimizations in both hardware and software. Software optimization\\u000a has no received much attention, although modern multimedia applications exhibit high resource utilization. In order to efficiently\\u000a run this kind of applications in embedded systems, the dynamic memory subsystem needs to be optimized. A key role in this\\u000a optimization is played by the Dynamic Data

José L. Risco-Martín; David Atienza; José Ignacio Hidalgo; Juan Lanchares

2010-01-01

294

Optimal spatiotemporal reduced order modeling for nonlinear dynamical systems

NASA Astrophysics Data System (ADS)

Proposed in this dissertation is a novel reduced order modeling (ROM) framework called optimal spatiotemporal reduced order modeling (OPSTROM) for nonlinear dynamical 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 dynamical systems. In the context of nonlinear continuum dynamics, 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 dynamical 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 dynamics, 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 dynamic 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 optimal (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-discretization schemes. Four nonlinear dynamical systems serve as testbeds to demonstrate the technique. First we consider an autonomous van der Pol oscillator for which all trajectories evolve to self-sustained limit cycle oscillations. Next we investigate a forced Duffing oscillator for which the response may be regular or chaotic. In order to demonstrate application for a problem in nonlinear wave propagation, we consider the viscous Burgers equation with large-amplitude inflow disturbances. For the fourth and final system, we analyze the nonlinear structural dynamics of a geometrically nonlinear beam under the influence of time-dependent external forcing. The practical utility of the proposed subgrid-scale models is enhanced if it can be shown that certain statistical moments amongst the subgrid-scale dynamics display to some extent the following properties: spatiotemporal homogeneity, ergodicity, smooth scaling with respect to the system parameters, and universality. To this end, we characterize the subgrid-scale dynamics for each of the four problems. The results in this dissertation indicate that temporal homogeneity and ergodicity are excellent assumptions for both regular and chaotic response types. Spatial homogeneity is found to be a very good assumption for the nonlinear beam problem with models based upon single-point but not multi-point spatial stencils. The viscous Burgers flow, however, requires spatially heterogeneous models regardless of the stencil. For each of the four problems, the required statistical moments display a functional dependence which can easily be characterized with respect to the physical parameters and the computational grid. This observed property, in particular, greatly simplifies model construction by way of moment estimation. We investigate the performance of the subgrid-scale models with under-resolved simulations (in space and time) and various discretization schemes. For the canonical Duffing and van der Pol oscillators, the subgrid-scale models are found to improve the accuracy of under-resolved time-marching and time-s

LaBryer, Allen

295

An inverse dynamics approach to trajectory optimization and guidance for an aerospace plane

NASA Technical Reports Server (NTRS)

The optimal ascent problem for an aerospace planes is formulated as an optimal inverse dynamic problem. Both minimum-fuel and minimax type of performance indices are considered. Some important features of the optimal trajectory and controls are used to construct a nonlinear feedback midcourse controller, which not only greatly simplifies the difficult constrained optimization 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 dynamics approach. Accurate orbital insertion can be achieved with near-optimal control of the rocket through inverse dynamics even in the presence of disturbances.

Lu, Ping

1992-01-01

296

A Formal Approach to Empirical Dynamic Model Optimization and Validation

NASA Technical Reports Server (NTRS)

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.

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

2014-01-01

297

group. Understanding the nonlinear reactor dynamics is not only interesting from academic point of viewPolymer Reaction Engineering Laboratory - University of Maryland at College Park Reactor Dynamics, Control, Optimization Exothermic polymerization reactions in continuous flow reactors may cause complex

Rubloff, Gary W.

298

A relaxed reduced space SQP strategy for dynamic optimization problems.

Recently, strategies have been developed to solve dynamic simulation and optimization problems in a simultaneous manner by applying orthogonal collocation on finite elements and solving the nonlinear program (NLP) with a reduced space successive quadratic programming (SQP) approach. We develop a relaxed simultaneous approach that leads to faster performance. The method operates in the reduced space of the control variables and solves the collocation equations inexactly at each SQP iteration. Unlike previous simultaneous formulations, it is able to consider the state variables one element at a time. Also, this approach is compared on two process examples to the reduced gradient, feasible path approach outlined in Logsdon and Biegler. Nonlinear programs with up to 5500 variables are solved with only 40% of the effort. Finally, a theoretical analysis of this approach is provided.

Logsdon, J. S.; Biegler, L. T.; Carnegie-Mellon Univ.

1993-01-01

299

Performance Study and Dynamic Optimization Design for Thread Pool Systems

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 dynamically determine the optimal thread pool size. The simulation results show that this approach is effective in improving overall application performance.

Dongping Xu

2004-12-19

300

Improved self-protection using dynamically optimized expendable countermeasures

NASA Astrophysics Data System (ADS)

The use of expendable countermeasures is still found to be a viable choice for self protection against Man Portable Air Defense Systems (MANPADS) due to their simplicity, low cost, flexibility, recent improvements in decoy technology, the ability to handle multiple threats simultaneously and the off-board nature of these countermeasures. In civil aviation, the risk of general hazards linked to the use of pyrotechnics is the main argument against expendable countermeasures, whereas for military platforms, the limitation in capacity due to a limited number of rounds is often used as an argument to replace expendable countermeasures by laser-based countermeasures. This latter argument is in general not substantiated by modelling or figures of merit, although it is often argued that a laser based system allows for more false alarms, hence enabling a more sensitive missile approach warning system. The author has developed a model that accounts for the statistical effects of running out of expendable countermeasures during a mission, in terms of the overall mission survival probability. The model includes key parameters of the missile approach warning system (MAWS), and can handle multiple missile types and missile attack configurations, as well as various statistical models of missile attacks. The model enables quantitative comparison between laser based and expendable countermeasures, but also a dynamic optimization of the countermeasures in terms of whether to use small or large countermeasure programs, as well as the dynamic tuning of MAWS key parameters to optimize the overall performance. The model is also well suited for determination of the contributions of the different components of the system in the overall survival probability.

Hovland, Harald

2007-04-01

301

Dynamic estimation of specific fluxes in metabolic networks using non-linear dynamic optimization.

BackgroundMetabolic network models describing the biochemical reaction network and material fluxes inside microorganisms open interesting routes for the model-based optimization of bioprocesses. Dynamic metabolic flux analysis (dMFA) has lately been studied as an extension of regular metabolic flux analysis (MFA), rendering a dynamic view of the fluxes, also in non-stationary conditions. Recent dMFA implementations suffer from some drawbacks, though. More specifically, the fluxes are not estimated as specific fluxes, which are more biologically relevant. Also, the flux profiles are not smooth, and additional constraints like, e.g., irreversibility constraints on the fluxes, cannot be taken into account. Finally, in all previous methods, a basis for the null space of the stoichiometric matrix, i.e., which set of free fluxes is used, needs to be chosen. This choice is not trivial, and has a large influence on the resulting estimates.ResultsIn this work, a new methodology based on a B-spline parameterization of the fluxes is presented. Because of the high degree of non-linearity due to this parameterization, an incremental knot insertion strategy has been devised, resulting in a sequence of non-linear dynamic optimization problems. These are solved using state-of-the-art dynamic optimization methods and tools, i.e., orthogonal collocation, an interior-point optimizer and automatic differentiation. Also, a procedure to choose an optimal basis for the null space of the stoichiometric matrix is described, discarding the need to make a choice beforehand. The proposed methodology is validated on two simulated case studies: (i) a small-scale network with 7 fluxes, to illustrate the operation of the algorithm, and (ii) a medium-scale network with 68 fluxes, to show the algorithm¿s capabilities for a realistic network. The results show an accurate correspondence to the reference fluxes used to simulate the measurements, both in a theoretically ideal setting with no experimental noise, and in a realistic noise setting.ConclusionsBecause, apart from a metabolic reaction network and the measurements, no extra input needs to be given, the resulting algorithm is a systematic, integrated and accurate methodology for dynamic metabolic flux analysis that can be run online in real-time if necessary. PMID:25466625

Vercammen, Dominique; Logist, Filip; Impe, Jan

2014-12-01

302

Molecular dynamics simulator for optimal control of molecular motion

NASA Astrophysics Data System (ADS)

In recognition of recent interest in developing optimal control techniques for manipulating molecular motion, this paper introduces a computer-driven electro-mechanical analog of this process. The resultant Molecular Dynamic Simulator (MDS) is centered around a linear air track for which the atoms of the controlled molecule are simulated as nearly frictionless carts on the track. Bonds in the simulated molecule are described by precision springs, and the interaction with an external optical field is simulated through a computer-based linear driver. When the MDS is operated in the harmonic regime, it can be used as an exact analog of molecular scale quantum systems through Ehrenfest's Theorem, or equivalently as a classical set of coupled oscillators. The tools of optimal control theory currently being applied at the molecular scale are used to design the forcing function for the MDS. Optical encoders are used to measure bond distances for graphic representation of the MDS behavior. Bond breaking can also be simulated by bond-length sensitive trigger-release mechanisms. The MDS is especially useful as a modelling tool to bridge theoretical studies and eventual laboratory experiments at the true molecular scale.

Rabitz, Herschel

1990-12-01

303

Molecular-dynamics simulator for optimal control of molecular motion

NASA Astrophysics Data System (ADS)

In recognition of recent interest in developing optimal control techniques for manipulating molecular motion, this paper introduces a computer-driven electromechanical analog of this process. The resultant molecular-dynamics simulator (MDS) is centered around a linear air track for which the atoms of the controlled molecule are simulated as nearly frictionless carts on the track. Bonds in the simulated molecule are described by precision springs, and the interaction with an external optical field is simulated through a computer-based linear driver. When the MDS is operated in the harmonic regime, it can be used as an exact analog of molecular-scale quantum systems through Ehrenfest's theorem or, equivalently, as a classical set of coupled oscillators. The tools of optimal control theory currently being applied at the molecular scale are used to design the forcing function for the MDS. Optical encoders are used to measure bond distances for graphic representation of the MDS behavior. Bond breaking can also be simulated by bond-length-sensitive trigger-release mechanisms. The MDS is especially useful as a modeling tool to bridge theoretical studies and eventual laboratory experiments at the true molecular scale.

Husman, M.; Schwieters, C.; Littman, M.; Rabitz, H.

1991-11-01

304

On-line optimization of large dynamic systems

This thesis proposes an algorithm for the on-line optimization of large-scale nonlinear dynamic systems. It combines the concepts of moving time horizon, augmented state estimation, and discrete modeling, thus allowing formulation of the problem as a mathematical programming problem. The moving time horizon reduces the effect of disturbances and model inaccuracy, and the augmented state estimator is used (in conjunction with the moving time horizon) in order to obtain a good approximation of the system state (at the time the computation of the control path is performed) and to account for nonstationary disturbances. Discretizing time allows the use of already developed and well tested optimization algorithms and the possibility of changing the problem (the objective function, the model and/or the constraints) with relative ease. The algorithm's effectiveness was tested by using it to improve the operation of a commercially important system. The operation of these systems - pipeline networks for natural gas transmission - is a challenge for any control algorithm because pipeline networks have large dimensions, the gas flow is modeled by nonlinear hyperbolic partial differential equations, and the operation is subject to constraints on the manipulated, state, and output variables. The successful application of the proposed algorithm to pipeline networks of significant dimension exhibits its strength.

Marques, D.

1985-01-01

305

Geometry optimization for micro-pressure sensor considering dynamic interference

Presented is the geometry optimization 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. Optimization 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 dynamic 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.

Yu, Zhongliang; Zhao, Yulong, E-mail: zhaoyulong@mail.xjtu.edu.cn; Li, Lili; Tian, Bian; Li, Cun [State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049 (China)

2014-09-15

306

The study in Fleming(F1) brings a connection of some optimal investment problem and the theory of risk sensitive control. From this, the method of dynamical programming can be used. Then the dynamical programming equation can be derived. It is a nonlinear partial differential equation. A solution gives a candidate of optimal portfolio. We consider a particular investment model( is refered

H. Kaise; S. J. Sheu

307

ON THE DYNAMIC PROGRAMMING APPROACH FOR OPTIMAL CONTROL PROBLEMS OF PDE'S WITH AGE STRUCTURE

A survey and some new results are presented concerning the dynamic programming for a class of optimal control problems of partial differential equations with age-structure and of delay systems that include some applied examples from economic theory and from population dynamics. A general optimal control problem in Hilbert spaces applying to all examples is investigated, with particular stress on one

SILVIA FAGGIAN; FAUSTO GOZZI

2004-01-01

308

Structural and Dynamic Requirements for Optimal Activity of the Essential Bacterial Enzyme

Structural and Dynamic Requirements for Optimal Activity of the Essential Bacterial Enzyme) is an essential enzyme involved in the lysine biosynthesis pathway. DHDPS from E. coli is a homotetramer and Dynamic Requirements for Optimal Activity of the Essential Bacterial Enzyme Dihydrodipicolinate Synthase

Hickman, Mark

309

Dynamic Property Optimization of Suspension MBD Model based on Sensitivity Analysis

In recent years, the needs to achieve the eigenvalue optimization considering the NVH performance increase in the initial design of suspension systems. This paper presents an application of MBD (Multi-Body Dynamics) model to dynamic property optimization. A vehicle suspension is modeled by MBD and the vibration properties are analyzed based on the linearization of the system equation. The model can

Tomonori Ikezawa; Takuya Yoshimura

2008-01-01

310

A key challenge for the unmanned aerial vehicles (UAVs) is to develop an overall system architecture that can perform optimal coordination of the UAVs and reconfigure to account for changes in the dynamic environment with uncertainty. This paper presents a multi-task allocation and path planning optimal coordination algorithm for UAVs based on dynamic Bayesian network (DBN) perceiving architecture, which leads

Guo Wen-Qiang; Hou Yong-yan

2009-01-01

311

Illinois Power Company (IP) is a leader in implementing online dynamic optimization at its fossil-fired power stations. As part of the company's Phase II CAAA compliance plan, IP proceeded with similar online systems at its Baldwin, Wood River, Havana, and Vermilion stations for all 10 of its coal-fired units. These Operator Advisory Systems utilize the Ultramax Method™ and Dynamic Optimization,

Morgan McVay; Peter D. Patterson

312

Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint

the profit. Our model is motivated by the problem faced by retailers of stocking products on a shelfDynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint Paat Abstract The paper considers a stylized model of a dynamic assortment optimization problem, where given

Shen, Zuo-Jun "Max"

313

Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint

Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint Paat of products that maximizes the profit subject to a capacity constraint. The demand is represented by a multinomial logit choice model. We consider both the static and dynamic optimization problems. In the static

Rusmevichientong, Paat

314

Dynamic analysis of optimality in myocardial energy metabolism under normal and ischemic conditions

To better understand the dynamic regulation of optimality in metabolic networks under perturbed conditions, we reconstruct the energetic-metabolic network in mammalian myocardia using dynamic flux balance analysis (DFBA). Additionally, we modified the optimal objective from the maximization of ATP production to the minimal fluctuation of the profile of metabolite concentration under ischemic conditions, extending the hypothesis of original minimization of

Ruo-Yu Luo; Sha Liao; Guan-Yang Tao; Yuan-Yuan Li; Shaoqun Zeng; Yi-Xue Li; Qingming Luo

2006-01-01

315

The present work aims at the development of a systematic method to optimally choose the parameters of digitally controlled nonlinear reactor dynamics. In addition to traditional performance requirements for the controlled reactor dynamics such as stability, fast and smooth regulation, disturbance rejection, etc., optimality is requested with respect to a physically meaningful performance. The value of the performance index is

Nguyen Huynh; Nikolaos Kazantzis

2005-01-01

316

Indirect optimization of interplanetary trajectories including spiral dynamics

NASA Astrophysics Data System (ADS)

In the future small, robotic probes and large, human-crewed spacecraft will utilize long-duration, finite-burning engines. These types of engines have already been proven in several missions and research is on-going for the design of newer engines of this class. The trajectories they generate are significantly different than those that use conventional high-thrust chemical propulsion. The indirect method was chosen for the optimization of the missions presented due to its mathematical elegance and other problem specific issues. The goal was to choose a difficult optimization problem for an engine of this class and determine techniques, trends, and formulations that help overcome the indirect method's traditional shortcoming: the numerical difficulty of generating an accurate first guess for complex missions. The problem chosen was the optimization of interplanetary trajectories, with particular results presented for the problem of transferring from Low Earth Orbit (LEO) to Low Mars Orbit (LMO). Most previous attempts at this problem use an array of simplifications to the engine system and/or problem dynamics to make the optimization feasible. These simplifications are systematically removed here. The complete trajectory was broken down into its component phases and careful study was paid to each. Analysis of the escape and capture spirals provided useful insight into the appropriate coordinate frames for spirals. This study yielded a technique that quickly and accurately estimates the unknown Lagrange multipliers. These results were applied to the full LEO to LMO mission as part of a sequential process for a two-dimensional solar system model and the equivalent three-dimensional model. This process includes many new derivations that facilitate the generation of an accurate first guess for these LEO to LMO missions. One new derivation in particular is vital where the co-states for a Mars capture spiral referenced to a Martian coordinate frame are transformed into their Earth based equivalents. This sets up a multiple shooting problem integrated in a single coordinate frame which is different than the single shooting method used in published benchmarks. The new approach generates more fuel efficient trajectories and significantly more complex numerically achievable capture sequence compared with such benchmarks.

Ranieri, Christopher Louis

2007-12-01

317

Optimal feeder routing is an important part of the general optimal distribution network planning. This article proposes a new algorithm for the optimal feeder routing problem using the dynamic programming technique and GIS facilities. All practical issues, such as cost parameters (investments, line losses, reliability) and technical constraints (voltage drop and thermal limits), as well as physical routing constraints (obstacles,

N. G. Boulaxis; M. P. Papadopoulos

2001-01-01

318

Optimal feeder routing is an important part of the general optimal distribution network planning. This paper proposes a new algorithm for the optimal feeder routing problem using the dynamic programming technique and geographical information systems (GIS) facilities. All practical issues, such as cost parameters (investments, line losses, reliability) and technical constraints (voltage drop and thermal limits), as well as physical

Nicholas G. Boulaxis; Michael P. Papadopoulos

2002-01-01

319

One-Dimensional Infinite Horizon Nonconcave Optimal Control Problems Arising in Economic Dynamics

We study the existence of optimal solutions for a class of infinite horizon nonconvex autonomous discrete-time optimal control problems. This class contains optimal control problems without discounting arising in economic dynamics which describe a model with a nonconcave utility function.

Zaslavski, Alexander J., E-mail: ajzasl@tx.technion.ac.il [Technion-Israel Institute of Technology, Department of Mathematics (Israel)

2011-12-15

320

An effective dynamic optimization method based on modified orthogonal collocation and reduced SQP

An effective dynamic optimization solution method based on the modified orthogonal collocation (mOC) and reduced successive quadratic programming (rSQP) is proposed, where the mOC is proposed to decrease the approximation error of the discrete optimal problem while traditional OC method converts the dynamic optimization problem to a regular but discrete nonlinear programming (NLP) problem, and the rSQP method is introduced

Xinggao Liu; Long Chen; Yunqing Hu

2011-01-01

321

Optimal foot shape for a passive dynamic biped.

Passive walking dynamics describe the motion of a biped that is able to "walk" down a shallow slope without any actuation or control. Instead, the walker relies on gravitational and inertial effects to propel itself forward, exhibiting a gait quite similar to that of humans. These purely passive models depend on potential energy to overcome the energy lost when the foot impacts the ground. Previous research has demonstrated that energy loss at heel-strike can vary widely for a given speed, depending on the nature of the collision. The point of foot contact with the ground (relative to the hip) can have a significant effect: semi-circular (round) feet soften the impact, resulting in much smaller losses than point-foot walkers. Collisional losses are also lower if a single impulse is broken up into a series of smaller impulses that gradually redirect the velocity of the center of mass rather than a single abrupt impulse. Using this principle, a model was created where foot-strike occurs over two impulses, "heel-strike" and "toe-strike," representative of the initial impact of the heel and the following impact as the ball of the foot strikes the ground. Having two collisions with the flat-foot model did improve efficiency over the point-foot model. Representation of the flat-foot walker as a rimless wheel helped to explain the optimal flat-foot shape, driven by symmetry of the virtual spoke angles. The optimal long period foot shape of the simple passive walking model was not very representative of the human foot shape, although a reasonably anthropometric foot shape was predicted by the short period solution. PMID:17570405

Kwan, Maxine; Hubbard, Mont

2007-09-21

322

Optimized dynamical decoupling in a model quantum memory.

Any quantum system, such as those used in quantum information or magnetic resonance, is subject to random phase errors that can dramatically affect the fidelity of a desired quantum operation or measurement. In the context of quantum information, quantum error correction techniques have been developed to correct these errors, but resource requirements are extraordinary. The realization of a physically tractable quantum information system will therefore be facilitated if qubit (quantum bit) error rates are far below the so-called fault-tolerance error threshold, predicted to be of the order of 10(-3)-10(-6). The need to realize such low error rates motivates a search for alternative strategies to suppress dephasing in quantum systems. Here we experimentally demonstrate massive suppression of qubit error rates by the application of optimized dynamical decoupling pulse sequences, using a model quantum system capable of simulating a variety of qubit technologies. We demonstrate an analytically derived pulse sequence, UDD, and find novel sequences through active, real-time experimental feedback. The latter sequences are tailored to maximize error suppression without the need for a priori knowledge of the ambient noise environment, and are capable of suppressing errors by orders of magnitude compared to other existing sequences (including the benchmark multi-pulse spin echo). Our work includes the extension of a treatment to predict qubit decoherence under realistic conditions, yielding strong agreement between experimental data and theory for arbitrary pulse sequences incorporating nonidealized control pulses. These results demonstrate the robustness of qubit memory error suppression through dynamical decoupling techniques across a variety of qubit technologies. PMID:19396139

Biercuk, Michael J; Uys, Hermann; VanDevender, Aaron P; Shiga, Nobuyasu; Itano, Wayne M; Bollinger, John J

2009-04-23

323

In this study, a two-stage support-vector-regression optimization model (TSOM) is developed for the planning of municipal solid waste (MSW) management in the urban districts of Beijing, China. It represents a new effort to enhance the analysis accuracy in optimizing the MSW management system through coupling the support-vector-regression (SVR) model with an interval-parameter mixed integer linear programming (IMILP). The developed TSOM can not only predict the city's future waste generation amount, but also reflect dynamic, interactive, and uncertain characteristics of the MSW management system. Four kernel functions such as linear kernel, polynomial kernel, radial basis function, and multi-layer perception kernel are chosen based on three quantitative simulation performance criteria [i.e. prediction accuracy (PA), fitting accuracy (FA) and over all accuracy (OA)]. The SVR with polynomial kernel has accurate prediction performance for MSW generation rate, with all of the three quantitative simulation performance criteria being over 96%. Two cases are considered based on different waste management policies. The results are valuable for supporting the adjustment of the existing waste-allocation patterns to raise the city's waste diversion rate, as well as the capacity planning of waste management system to satisfy the city's increasing waste treatment/disposal demands. PMID:21872384

Dai, C; Li, Y P; Huang, G H

2011-12-01

324

THE DYNAMIC PROGRAMMING EQUATION FOR THE PROBLEM OF OPTIMAL INVESTMENT UNDER CAPITAL GAINS TAXES

THE DYNAMIC PROGRAMMING EQUATION FOR THE PROBLEM OF OPTIMAL INVESTMENT UNDER CAPITAL GAINS TAXES and capital gains taxes. We derive the dynamic programming equation in the sense of constrained viscosity of an approximation of our dynamic programming equation. In particular, this result justifies the numerical results

Touzi, Nizar

325

Adapted Convex Optimization Algorithm for Wavelet-Based Dynamic PET Reconstruction

1 Adapted Convex Optimization Algorithm for Wavelet-Based Dynamic PET Reconstruction Nelly Abstract--This work deals with Dynamic Positron Emission Tomography (PET) data reconstruction, considering. The effectiveness of this approach is shown with simulated dynamic PET data. Comparative results are also provided

Paris-Sud XI, UniversitÃ© de

326

On the Optimization of Riemann-Stieltjes-Control-Systems with Application in Vehicle Dynamics

On the Optimization of Riemann-Stieltjes-Control-Systems with Application in Vehicle Dynamics J of Riemann-Stieltjes-Control-Systems with Application in Vehicle Dynamics J. Michael Content Problem-Stieltjes-Control-Systems with Application in Vehicle Dynamics J. Michael ProactiveÂChassisÂControl Setting: Input: Vetical Road Model

Boyer, Edmond

327

Optimal Dynamic Production Policy: The Case of a Large Oil Field in Saudi Arabia

We model the optimal dynamic oil production decisions for a stylized oilfield resembling the largest developed light oil field in Saudi Arabia, Ghawar. We use data from a number of sources to estimate the cost and revenue functions used in the dynamic programming model. We also pay particular attention to the dynamic aspects of oil production. We use a nonparametric

Weiyu Gao; Peter Hartley; Robin C. Sickles

328

Modeling and Optimization of Dynamic Signal Processing in Resource-Aware Sensor Networks

processing functional- ity in which computational structure must be dynamically assessed and adapted based- tured specification, simulation, and synthesis of dynamic signal processing systems. These modelsModeling and Optimization of Dynamic Signal Processing in Resource-Aware Sensor Networks Shuvra S

Bhattacharyya, Shuvra S.

329

Optimization of conventional water treatment plant using dynamic programming.

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 dynamic 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 optimized 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. PMID:23625909

Mostafa, Khezri Seyed; Bahareh, Ghafari; Elahe, Dadvar; Pegah, Dadras

2013-04-26

330

Conceptualizing a Tool to Optimize Therapy Based on Dynamic Heterogeneity

Complex biological systems often display a randomness paralleled in processes studied in fundamental physics. This simple stochasticity emerges owing to the complexity of the system and underlies a fundamental aspect of biology called phenotypic stochasticity. Ongoing stochastic fluctuations in phenotype at the single-unit level can contribute to two emergent population phenotypes. Phenotypic stochasticity not only generates heterogeneity within a cell population, but also allows reversible transitions back and forth between multiple states. This phenotypic interconversion tends to restore a population to a previous composition after that population has been depleted of specific members. We call this tendency homeostatic heterogeneity. These concepts of dynamic heterogeneity can be applied to populations composed of molecules, cells, individuals, etc. Here we discuss the concept that phenotypic stochasticity both underlies the generation of heterogeneity within a cell population and can be used to control population composition, contributing, in particular, to both the ongoing emergence of drug resistance and an opportunity for depleting drug-resistant cells. Using notions of both “large” and “small” numbers of biomolecular components, we rationalize our use of Markov processes to model the generation and eradication of drug-resistant cells. Using these insights, we have developed a graphical tool, called a metronomogram, that we propose will allow us to optimize dosing frequencies and total course durations for clinical benefit. PMID:23197078

Liao, David; Estévez-Salmerón, Luis; Tlsty, Thea D.

2012-01-01

331

Photocathode Optimization for a Dynamic Transmission Electron Microscope: Final Report

The Dynamic Transmission Electron Microscope (DTEM) team at Harvey Mudd College has been sponsored by LLNL to design and build a test setup for optimizing 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.

Ellis, P; Flom, Z; Heinselman, K; Nguyen, T; Tung, S; Haskell, R; Reed, B W; LaGrange, T

2011-08-04

332

Metamodeling and the Critic-based approach to multi-level optimization.

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 optimized using some variation of Linear Programming, such as Mixed Integer 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 Dynamic 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 optimization 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 optimization modules allows for multiple queries for the same system, providing flexibility and optimizing 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. PMID:22386785

Werbos, Ludmilla; Kozma, Robert; Silva-Lugo, Rodrigo; Pazienza, Giovanni E; Werbos, Paul J

2012-08-01

333

NASA Astrophysics Data System (ADS)

The goal of this study is to numerically compare solutions and algorithms determined by element- and node-wise topology optimization designs for dynamic free vibration-resistance structures. As another version in the fields of topology optimization methods, the study supports the node-based optimization rather than the classical element-based optimization comparing two methods. The terms element-and node-wise denote the usage of element and node density as design parameter, respectively. For static problems solution comparisons of the two types for SIMP topology optimization designs have already been introduced by the author(1). For dynamic topology optimization problems the objective is in general related to maximum eigenfrequency optimization subject to a given material limit since structures with a high fundamental frequency tends to be reasonable stiff for static loads. For dynamic problems SIMP material is used in this study and an implemented optimization method is the method of moving asymptotes (MMA). Numerical applications topologically maximizing the first natural eigenfrequency for dynamic concrete deep beam designs depending on element or node density verify differences of solutions and algorithms between dynamic element- and node-wise topology optimum designs.

Lee, Dong-Kyu; Park, Sung-Soo; Shin, Soo-Mi

334

Power flow response based dynamic topology optimization of bi-material plate Structures

NASA Astrophysics Data System (ADS)

Work on dynamic topology optimization of engineering structures for vibration suppression has mainly addressed the maximization of eigenfrequencies and gaps between consecutive eigenfrequencies of free vibration, minimization of the dynamic compliance subject to forced vibration, and minimization of the structural frequency response. A dynamic topology optimization method of bi-material plate structures is presented based on power flow analysis. Topology optimization problems formulated directly with the design objective of minimizing the power flow response are dealt with. In comparison to the displacement or velocity response, the power flow response takes not only the amplitude of force and velocity into account, but also the phase relationship of the two vector quantities. The complex expression of power flow response is derived based on time-harmonic external mechanical loading and Rayleigh damping. The mathematical formulation of topology optimization is established based on power flow response and bi-material solid isotropic material with penalization(SIMP) model. Computational optimization procedure is developed by using adjoint design sensitivity analysis and the method of moving asymptotes(MMA). Several numerical examples are presented for bi-material plate structures with different loading frequencies, which verify the feasibility and effectiveness of this method. Additionally, optimum results between topological design of minimum power flow response and minimum dynamic compliance are compared, showing that the present method has strong adaptability for structural dynamic topology optimization problems. The proposed research provides a more accurate and effective approach for dynamic topology optimization of vibrating structures.

Xue, Xiaoguang; Li, Guoxi; Xiong, Yeping; Gong, Jingzhong

2013-05-01

335

Optimized dynamic framing for PET-based myocardial blood flow estimation

NASA Astrophysics Data System (ADS)

An optimal experiment design methodology was developed to select the framing schedule to be used in dynamic 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-optimality criterion for a wide range of candidate framing schedules. To validate the optimality calculation, noisy time-activity curves were simulated, from which parameter values were estimated using an efficient and robust decomposition of the estimation problem. D-optimized schedules improved estimate precision compared to non-optimized schedules, including previously published schedules. To assess robustness, a range of physiologic conditions were simulated. Schedules that were optimal for one condition were nearly-optimal for others. The effect of infusion duration was investigated. Optimality was better for shorter than for longer tracer infusion durations, with the optimal schedule for the shortest infusion duration being nearly optimal for other durations. Together this suggests that a framing schedule optimized 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 optimizing schedules is general and could be applied in other dynamic PET imaging studies.

Kolthammer, Jeffrey A.; Muzic, Raymond F.

2013-08-01

336

An optimization model for energy generation and distribution in a dynamic facility

NASA Technical Reports Server (NTRS)

An analytical model is described using linear programming for the optimum generation and distribution of energy demands among competing energy resources and different economic criteria. The model, which will be used as a general engineering tool in the analysis of the Deep Space Network ground facility, considers several essential decisions for better design and operation. The decisions sought for the particular energy application include: the optimum time to build an assembly of elements, inclusion of a storage medium of some type, and the size or capacity of the elements that will minimize the total life-cycle cost over a given number of years. The model, which is structured in multiple time divisions, employ the decomposition principle for large-size matrices, the branch-and-bound method in mixed-integer programming, and the revised simplex technique for efficient and economic computer use.

Lansing, F. L.

1981-01-01

337

Optimal Regulation of Heating Systems with Metering Based on Dynamic Simulation

is applied, and the optimal supply water temperatures are worked out by the estimate method of linear summation with weights based on dynamic simulation. The simulative results reflect the relationship between energy loss of heating systems and users' comfort....

Zhao, H.; Wang, P.; Zeng, G.; Tian, Y.

2006-01-01

338

Optimal foreign borrowing in a multisector dynamic equilibrium model for Brazil

This paper shows how a dynamic multisector equilibrium model can be formulated to be able to analyze the optimal borrowing policy of a developing country. It also describes how a non-linear programming model with the ...

Tourinho, Octv?io A. F.

1985-01-01

339

Optimization of a high-efficiency jet ejector by using computational fluid dynamic (CFD) software

in a desalination process High-Pressure Motive Steam Heat Exchanger # 1 # 2 Brine Distillate Sea Water # 3 # n-1 # nOptimization of a high-efficiency jet ejector by using computational fluid dynamic (CFD) software

340

OPTIMAL SEDUCING POLICIES FOR DYNAMIC CONTINUOUS LOVERS UNDER RISK OF BEING KILLED BY A RIVAL

This paper provides useful decision rules for finite horizon dynamic continuous lovers to find an optimal tradeoff between satisfaction by fooling around with girls and the risk of being killed by the former friends of the latter.

RICHARD F. HARTL; ALEXANDER MEHLMANN

1984-01-01

341

SUMMARY This paper is concerned with the optimal birth control of a McKendrick-type age-structured population dynamic system. We use the dynamic programming approach in our investigation. The Hamilton-Jacobi- Bellman equation satisfied by the value function is derived. It is shown that the value function is the viscosity solution of the Hamilton-Jacobi-Bellman equation. The optimal birth feedback control is found explicitly

Bao-Zhu Guo; Bing Sun

2005-01-01

342

An optimal operational planning method is proposed for cogeneration systems with thermal storage. The daily operational strategy of constituent equipment is determined so as to minimize the daily operational cost subject to the energy demand requirement. This optimization problem is formulated as a large-scale mixed-integer linear programming one, and it is solved by means of the decomposition method. Effects of thermal storage on the operation of cogeneration systems are examined through a numerical study on a gas engine-driven cogeneration system installed in a hotel. This method is a useful tool for evaluating the economic and energy-saving properties of cogeneration systems with thermal storage.

Yokoyama, R.; Ito, K. [Osaka Prefecture Univ., Sakai, Osaka (Japan). Dept. of Energy Systems Engineering

1995-12-01

343

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 optimal design points which are computed before the plant is built. The operational optimization 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 mixed-integer 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

Wang, Jian; Wang, Xiaolong; Jiang, Aipeng; Jiangzhou, Shu; Li, Ping

2014-01-01

344

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 optimal design points which are computed before the plant is built. The operational optimization 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 mixed-integer 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

Wang, Xiaolong; Jiang, Aipeng; Jiangzhou, Shu; Li, Ping

2014-01-01

345

Optimal GENCO bidding strategy

NASA Astrophysics Data System (ADS)

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 optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer 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 optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer 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 optimal 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 optimal 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 optimization model may not be enough to consider the distributed, large-scale, and complex energy market. This research compares the performance and searching paths of different artificial life techniques such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm (PS), and look for a proper method to emulate Generation Companies' (GENCOs) bidding strategies. After deregulation, GENCOs face risk and uncertainty associated with the fast-changing market environment. A profit-based bidding decision support system is critical for GENCOs to keep a competitive position in the new environment. Most past research do not pay special attention to the piecewise staircase characteristic of generator offer curves. This research proposes an optimal bidding strategy based on Parametric Linear Programming. The proposed algorithm is able to handle actual piecewise staircase energy offer curves. The proposed method is then extended to incorporate incomplete information based on Decision Analysis. Finally, the author develops an optimal bidding tool (GenBidding) and applies it to the RTS96 test system.

Gao, Feng

346

Real-time Optimization-based Planning in Dynamic Environments using GPUs

Real-time Optimization-based Planning in Dynamic Environments using GPUs Chonhyon Park and Jia Pan planning. Some of the applications include automated wheel chairs, manufacturing tasks with robots multiple trajectory optimization algorithm to many-core GPUs (graphics pro- Chonhyon Park and Jia Pan

North Carolina at Chapel Hill, University of

347

Optimal control of coupled spin dynamics in the presence of relaxation

In this thesis, we study methods for optimal manipulation of coupled spin dynamics in the presence of relaxation. We use these methods to compute analytical upper bounds for the efficiency of coherence and polarization transfer between coupled nuclear spins in multidimensional nuclear magnetic resonance (NMR) experiments, under the presence of relaxation. We derive relaxation optimized pulse sequences which achieve or

Dionisis Stefanatos

2005-01-01

348

This note shows that the optimal control of dynamic systems with uncertain parameters has certain limitations. In particular, by means of a simple scalar linear-quadratic optimal 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

M. Athans; R. Ku; S. Gershwin

1977-01-01

349

OPTIMAL INTERVENTION IN THE FOREIGN EXCHANGE MARKET WHEN INTERVENTIONS AFFECT MARKET DYNAMICS

-variational inequalities, stopping times. 1. Introduction. In countries dependent on foreign trade and foreign capitalOPTIMAL INTERVENTION IN THE FOREIGN EXCHANGE MARKET WHEN INTERVENTIONS AFFECT MARKET DYNAMICS ALEC N. KERCHEVAL AND JUAN F. MORENO Abbreviated Title: Optimal intervention in foreign exchange Abstract

350

An inverse dynamics approach to trajectory optimization for an aerospace plane

NASA Technical Reports Server (NTRS)

An inverse dynamics approach for trajectory optimization is proposed. This technique can be useful in many difficult trajectory optimization and control problems. The application of the approach is exemplified by ascent trajectory optimization for an aerospace plane. Both minimum-fuel and minimax types of performance indices are considered. When rocket augmentation is available for ascent, it is shown that accurate orbital insertion can be achieved through the inverse control of the rocket in the presence of disturbances.

Lu, Ping

1992-01-01

351

Pole vault performance for anthropometric variability via a dynamical optimal control model

Optimal performance of a dynamical pole vault process was modeled as a constrained nonlinear optimization problem. That is, given a vaulter’s anthropomorphic data and approach speed, the vaulter chose a specific take-off angle, pole stiffness and gripping height in order to yield the greatest jumping height compromised by feasible bar-crossing velocities. The optimization problem was solved by nesting a technique

Guangyu Liu; Sing-Kiong Nguang; Yanxin Zhang

2011-01-01

352

Dynamic optimization of hybridoma growth in a fed-batch bioreactor.

This study addressed the problem of maximizing cell mass and monoclonal antibody production from a fed-batch hybridoma cell culture. We hypothesized that inaccuracies in the process model limited the mathematical optimization. On the basis of shaker flask data, we established a simple phenomenological model with cell mass and lactate production as the controlled variables. We then formulated an optimal control algorithm, which calculated the process-model mismatch at each sampling time, updated the model parameters, and re-optimized the substrate concentrations dynamically throughout the time course of the batch. Manipulated variables were feed rates of glucose and glutamine. Dynamic parameter adjustment was done using a fuzzy logic technique, while a heuristic random optimizer (HRO) optimized the feed rates. The parameters selected for updating were specific growth rate and the yield coefficient of lactate from glucose. These were chosen by a sensitivity analysis. The cell mass produced using dynamic optimization was compared to the cell mass produced for an unoptimized case, and for a one-time optimization at the beginning of the batch. Substantial improvements in reactor productivity resulted from dynamic re-optimization and parameter adjustment. We demonstrated first that a single offline optimization of substrate concentration at the start of the batch significantly increased the yield of cell mass by 27% over an unoptimized fermentation. Periodic optimization online increased yield of cell mass per batch by 44% over the single offline optimization. Concomitantly, the yield of monoclonal antibody increased by 31% over the off-line optimization case. For batch and fed-batch processes, this appears to be a suitable arrangement to account for inaccuracies in process models. This suggests that implementation of advanced yet inexpensive techniques can improve performance of fed-batch reactors employed in hybridoma cell culture. PMID:10592517

Dhir, S; Morrow, K J; Rhinehart, R R; Wiesner, T

2000-01-20

353

Optimization of the Dynamic Aperture for SPEAR3 Low-Emittance Upgrade

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 dynamic aperture for the lower emittance optics due to a stronger nonlinearity. Elegant based Multi-Objective Genetic Algorithm (MOGA) is used to maximize the dynamic aperture. Both the dynamic aperture and beam lifetime are optimized simultaneously. Various configurations of the sextupole magnets have been studied in order to find the best configuration. The betatron tune also can be optimized to minimize resonance effects. The optimized dynamic 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 dynamic aperture is mainly in the beam injection direction. Therefore the injection efficiency will benefit from this improvement.

Wang, Lanfa; Huang, Xiaobiao; Nosochkov, Yuri; Safranek, James A.; /SLAC; Borland, Michael; /Argonne

2012-05-30

354

Data-driven learning in dynamic pricing using adaptive optimization

We model his capacity to exploit the information dynamically acquired by ... Dynamic pricing policies have been long-employed in the travel, hospitality, and ... management is a useful tool for increasing profit, it only serves to decrease costs.

2014-10-09

355

Capacity planning of link restorable optical networks under dynamic change of traffic

NASA Astrophysics Data System (ADS)

Future backbone networks shall require full-survivability and support dynamic changes of traffic demands. The Generalized Survivable Networks (GSN) was proposed to meet these challenges. GSN is fully-survivable under dynamic traffic demand changes, so it offers a practical and guaranteed characterization framework for ASTN / ASON survivable network planning and bandwidth-on-demand resource allocation 4. The basic idea of GSN is to incorporate the non-blocking network concept into the survivable network models. In GSN, each network node must specify its I/O capacity bound which is taken as constraints for any allowable traffic demand matrix. In this paper, we consider the following generic GSN network design problem: Given the I/O bounds of each network node, find a routing scheme (and the corresponding rerouting scheme under failure) and the link capacity assignment (both working and spare) which minimize the cost, such that any traffic matrix consistent with the given I/O bounds can be feasibly routed and it is single-fault tolerant under the link restoration scheme. We first show how the initial, infeasible formal mixed integer programming formulation can be transformed into a more feasible problem using the duality transformation of the linear program. Then we show how the problem can be simplified using the Lagrangian Relaxation approach. Previous work has outlined a two-phase approach for solving this problem where the first phase optimizes the working capacity assignment and the second phase optimizes the spare capacity assignment. In this paper, we present a jointly optimized framework for dimensioning the survivable optical network with the GSN model. Experiment results show that the jointly optimized GSN can bring about on average of 3.8% cost savings when compared with the separate, two-phase approach. Finally, we perform a cost comparison and show that GSN can be deployed with a reasonable cost.

Ho, Kwok Shing; Cheung, Kwok Wai

2005-11-01

356

Optimal Dynamic Advertising Strategy Under Age-Specific Market Segmentation

NASA Astrophysics Data System (ADS)

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 optimal control sub problems we find the optimal advertising strategy and goodwill.

Krastev, Vladimir

2011-12-01

357

Optimal Campaign Strategies in Fractional-Order Smoking Dynamics

NASA Astrophysics Data System (ADS)

This paper deals with the optimal control problem in the giving up smoking model of fractional order. For the eradication of smoking in a community, we introduce three control variables in the form of education campaign, anti-smoking gum, and anti-nicotive drugs/medicine in the proposed fractional order model. We discuss the necessary conditions for the optimality of a general fractional optimal control problem whose fractional derivative is described in the Caputo sense. In order to do this, we minimize the number of potential and occasional smokers and maximize the number of ex-smokers. We use Pontryagin's maximum principle to characterize the optimal levels of the three controls. The resulting optimality system is solved numerically by MATLAB.

Zeb, Anwar; Zaman, Gul; Jung, Il Hyo; Khan, Madad

2014-06-01

358

NASA Astrophysics Data System (ADS)

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

Huang, Xiaobiao; Safranek, James

2014-09-01

359

Using dynamic programming with adaptive grid scheme for optimal control problems in economics

The study of the solutions of dynamic models with optimizing agents has often been limited by a lack of available analytical techniques to explicitly find the global solution paths. On the other hand, the application of numerical techniques such as dynamic programming to find the solution in interesting regions of the state was restricted by the use of fixed grid

Lars Grüne; Willi Semmler

2004-01-01

360

SOPS - A Tool to Find Optimal Policies in Stochastic Dynamic Systems

The task of finding optimal policies in stochastic dynamic systems is challenging. The theory of stochastic dynamic programming (SDP) is quite complex and the available software packages are not intended for non-specialists. Furthermore, SDP is traditionally limited to quite small and well defined problems. Stochastic optimisation in policy space (SOPS) seems to be an attractive alternative, particularly for people with

Arne Krakenes; Erling Moxnes

361

CAE Applied to Dynamic Optimal Design for Large-Scale Vibrating Screen

Using ANSYS, static analysis and dynamic analysis were made for a certain large-scale linear vibrating screen structure, weak links were found out in structural design. The improved schemes were proposed for vibrating screen structure. The static and dynamics analysis's results of each schemes were compared, the optimal improved scheme was obtained. It is shown that, in the vibrating screen structure,

Su Ronghua; Zhu Liuqing; Peng Chenyu

2010-01-01

362

Optimal asset-liability management with constraints: A dynamic programming approach

This paper is devoted to the analysis of a discrete-time dynamic programming algorithm for the numerical solution of an optimal asset–liability management model with transaction costs and in presence of constraints. By exploiting the financial properties of the model, we propose an approximation method based on the classical dynamic programming algorithm, which reduces significantly the computational and storage requirements of

Marco Papi; Simone Sbaraglia

2006-01-01

363

The Optimal Golf Swing An exercise in simulation of dynamic systems

The Optimal Golf Swing An exercise in simulation of dynamic systems Simulators for Dynamic Systems from the dimples on the surface of the ball. The Flight of a Golf Ball In order to obtain the best golf stroke you may carry out experiments on a model of the player and his golf swing, followed by the impact

Mosegaard, Klaus

364

A multilevel optimization of large-scale dynamic systems

NASA Technical Reports Server (NTRS)

A multilevel feedback control scheme is proposed for optimization of large-scale systems composed of a number of (not necessarily weakly coupled) subsystems. Local controllers are used to optimize each subsystem, ignoring the interconnections. Then, a global controller may be applied to minimize the effect of interconnections and improve the performance of the overall system. At the cost of suboptimal performance, this optimization strategy ensures invariance of suboptimality and stability of the systems under structural perturbations whereby subsystems are disconnected and again connected during operation.

Siljak, D. D.; Sundareshan, M. K.

1976-01-01

365

The primary purpose of this study was to compare static and dynamic optimization muscle force and work predictions during the push phase of wheelchair propulsion. A secondary purpose was to compare the differences in predicted shoulder and elbow kinetics and kinematics and handrim forces. The forward dynamics simulation minimized differences between simulated and experimental data (obtained from 10 manual wheelchair users) and muscle co-contraction. For direct comparison between models, the shoulder and elbow muscle moment arms and net joint moments from the dynamic optimization were used as inputs into the static optimization routine. RMS errors between model predictions were calculated to quantify model agreement. There was a wide range of individual muscle force agreement that spanned from poor (26.4% Fmax error in the middle deltoid) to good (6.4% Fmax error in the anterior deltoid) in the prime movers of the shoulder. The predicted muscle forces from the static optimization were sufficient to create the appropriate motion and joint moments at the shoulder for the push phase of wheelchair propulsion, but showed deviations in the elbow moment, pronation-supination motion and hand rim forces. These results suggest the static approach does not produce results similar enough to be a replacement for forward dynamics simulations, and care should be taken in choosing the appropriate method for a specific task and set of constraints. Dynamic optimization modeling approaches may be required for motions that are greatly influenced by muscle activation dynamics or that require significant co-contraction. PMID:25282075

Morrow, Melissa M; Rankin, Jeffery W; Neptune, Richard R; Kaufman, Kenton R

2014-11-01

366

Optimizing Dynamic Responses of Structures using Isight to Integrate NASTRAN

With the development of science and technology, engineering structures become more and more complex, being required good property,\\u000a working in random conditions. Ordinary static design method does not satisfy the requirements of structural design .It is\\u000a more and more important to research the optimal design of structures, being applied random loads. In this paper the mathematic\\u000a model of structural optimization

Kailin Jian; Fanghao Xiao; Ying Chen

367

Optimal dynamic control of resources in a distributed system

NASA Technical Reports Server (NTRS)

The authors quantitatively formulate the problem of controlling resources in a distributed system so as to optimize a reward function and derive optimal control strategies using Markov decision theory. The control variables treated are quite general; they could be control decisions related to system configuration, repair, diagnostics, files, or data. Two algorithms for resource control in distributed systems are derived for time-invariant and periodic environments, respectively. A detailed example to demonstrate the power and usefulness of the approach is provided.

Shin, Kang G.; Krishna, C. M.; Lee, Yann-Hang

1989-01-01

368

NASA Technical Reports Server (NTRS)

This paper describes an integrated aerodynamic, dynamic, and structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general purpose optimizer 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 optimization technique that is compatible with industrial design practices in which the aerodynamic and dynamic 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, dynamic, and structural groups. The IADS procedure is demonstrated for several cases.

Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.

1994-01-01

369

NASA Technical Reports Server (NTRS)

This paper describes an integrated aerodynamic/dynamic/structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general-purpose optimizer 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 optimization technique that is compatible with industrial design practices in which the aerodynamic and dynamic 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, dynamic, and structural groups. The IADS procedure is demonstrated for several examples.

Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.

1995-01-01

370

DYNAMICALLY OPTIMAL AND APPROXIMATELY OPTIMAL BEEF CATTLE DIETS FORMULATED BY NONLINEAR PROGRAMMING

Cattle purchasing, feeding, and selling decisions are described by a free-time optimal control model. The nutrient constraints of the National Research Council and a recently published dry matter intake constraint augment the model and make it nonlinear in the feed ingredients, the daily gain, and the weight of the cattle. Optimal feeding programs are calculated by nonlinear programming under two

Greg Hertzler

1988-01-01

371

Communication Relaxometry of insensitive nuclei: Optimizing dissolution dynamic

Keywords: Dynamic nuclear polarization Hyperpolarization Relaxometry Scavenging a b s t r a c t We report, but it can be quenched by using scavengers. Ã? 2011 Elsevier Inc. All rights reserved. Dynamic nuclear', to select the best scavenging agents to eliminate the radicals after dissolution [20], and to predict which

372

Dynamic adaptive search for large-scale global optimization

We directly exploit a new, more realistic paradigm for the iterative optimization process itself, wherein we return the best-ever solution found over the entire computation rather than the last-seen solution that is generated in the final iteration. We propose non-monotone, adaptive threshold methods which are self-tuning to the individual optimization instance. These methods allow efficient escape from local minimum solutions because the parameter (threshold or temperature) schedule is allowed to be highly non-monotone, in some sense {open_quotes}following{close_quotes} the algorithm`s knowledge of the cost surface. We propose strategies for bounded-time optimization, i.e., strategies which explicitly depend on the total computing time allowed as well as the current stage of the optimization. We exploit a new {open_quotes}big valley{close_quotes} picture of structure in the optimization cost surface to generate effective initial states for the computation; these ideas greatly influence the implementation of {open_quotes}multi-start{close_quotes} strategies.

Hu, T.C.; Kahng, A.B.

1994-12-31

373

Approximate dynamic programming recurrence relations for a hybrid optimal control problem

NASA Astrophysics Data System (ADS)

This paper presents a hybrid approximate dynamic programming (ADP) method for a hybrid dynamic system (HDS) optimal 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 optimal control problem (HOCP) is to nd the optimal discrete event decisions and the optimal 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 optimal control, neither continuous nor discrete, is not available ahead of time. Therefore, ADP is adopted to learn the optimal 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 optimizing methods, such as dynamic programming (DP) and Markov decision process (MDP), are facing due to the high dimensions of HOCP.

Lu, W.; Ferrari, S.; Fierro, R.; Wettergren, T. A.

2012-06-01

374

The existing inexact optimization methods based on interval-parameter linear programming can hardly address problems where coefficients in objective functions are subject to dual uncertainties. In this study, a superiority-inferiority-based inexact fuzzy two-stage mixed-integer linear programming (SI-IFTMILP) model was developed for supporting municipal solid waste management under uncertainty. The developed SI-IFTMILP approach is capable of tackling dual uncertainties presented as fuzzy boundary intervals (FuBIs) in not only constraints, but also objective functions. Uncertainties expressed as a combination of intervals and random variables could also be explicitly reflected. An algorithm with high computational efficiency was provided to solve SI-IFTMILP. SI-IFTMILP was then applied to a long-term waste management case to demonstrate its applicability. Useful interval solutions were obtained. SI-IFTMILP could help generate dynamic facility-expansion and waste-allocation plans, as well as provide corrective actions when anticipated waste management plans are violated. It could also greatly reduce system-violation risk and enhance system robustness through examining two sets of penalties resulting from variations in fuzziness and randomness. Moreover, four possible alternative models were formulated to solve the same problem; solutions from them were then compared with those from SI-IFTMILP. The results indicate that SI-IFTMILP could provide more reliable solutions than the alternatives. PMID:20580864

Tan, Q; Huang, G H; Cai, Y P

2010-09-01

375

A complex-valued neural dynamical optimization approach and its stability analysis.

In this paper, we propose a complex-valued neural dynamical method for solving a complex-valued nonlinear convex programming problem. Theoretically, we prove that the proposed complex-valued neural dynamical approach is globally stable and convergent to the optimal solution. The proposed neural dynamical approach significantly generalizes the real-valued nonlinear Lagrange network completely in the complex domain. Compared with existing real-valued neural networks and numerical optimization methods for solving complex-valued quadratic convex programming problems, the proposed complex-valued neural dynamical approach can avoid redundant computation in a double real-valued space and thus has a low model complexity and storage capacity. Numerical simulations are presented to show the effectiveness of the proposed complex-valued neural dynamical approach. PMID:25462634

Zhang, Songchuan; Xia, Youshen; Zheng, Weixing

2015-01-01

376

Optimization Online - A dynamic approach to a proximal-Newton ...

Feb 15, 2015 ... Abstract: In a Hilbert setting, we introduce a new dynamic system and ... Given a maximal monotone operator $A$, the evolution is governed by the ... way, by resolution of the algebraic equation $\\lambda \

Hedy Attouch

2015-02-15

377

Wind Optimal Investment Timing Decisions Based on Stochastic Dynamic Programming

Compared with the conventional energy power generation investments, the uncertainty of wind power investment will bring greater risk. For wind power investors, wind power investment strategy-makers, even for wind power equipment manufacturers, all urgently need decision-support tools to minimize the risk and obtain optimal investment opportunities. In this paper, firstly we analyze the current problems and risks of wind power

Zeng Ming; Zhang Jinrong; Xu Wenqiu; Yan Fan

2010-01-01

378

INTRAOPERATIVE DYNAMIC DOSE OPTIMIZATION IN PERMANENT PROSTATE IMPLANTS

Purpose: With the advent of intraoperative optimized planning, the treatment of prostate cancer with permanent implants has reached an unprecedented level of dose conformity. However, because of well-documented (and unavoidable) inaccuracies in seed placement into the gland, carrying out a plan results in a large degree of variability relative to the intended dose distribution. This brings forth the need to

EVA K. LEE; MARCO ZAIDER

2003-01-01

379

Dynamic Optimization of Energy Supply Systems with Modelica Models

The paper describes a design tool for decentral- ised energy supply by preferable use of renew- able energy. The powerful modelling language Modelica has been used to develop a model library for input data generation and\\/or predict- ing and modelling the main parts of the energy supply system for the simulation tool Dymola. An optimal control design using the well

H. Puta

380

Dynamic Rate Control Algorithms for HDR Throughput Optimization

The relative delay tolerance of data applications, together with the bursty traffic character- istics, opens up the possibility for scheduling transmissions so as to optimize throughput. A particularly attractive approach, in fading environments, is to exploit the variations in the channel conditions, and transmit to the user with the currently 'best' channel. We show that the 'best' user may be

Sem Borst; Phil Whiting

381

Was Your Glass Left Half Full? Family Dynamics and Optimism

ERIC Educational Resources Information Center

Students' levels of a frequently studied adaptive schema (optimism) 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…

Buri, John R.; Gunty, Amy

2008-01-01

382

Optimal Formation Flight Control Using Coupled Inter-Spacecraft Dynamics

The increasing number of formation ight space missions proposed by the scientic community for the near future has led many researchers to the study, development and implementation of optimal control systems applied techniques known from the theory of control. Most of the future formation ight missions have been designed

383

Particle Swarm Optimization: Dynamic parameter adjustment using swarm activity

In this paper, swarm activity, which is a new index for assessing the diversification (global search) and intensification (local search) during particle swarm optimization (PSO) searches, is introduced. It is shown that swarm activity allows the quantitative assessment of the diversification and intensification during the PSO search. Using this concept, a new PSO called activity feedback PSO (AFPSO) is constructed,

Nobuhiro Iwasaki; Keiichiro Yasuda; Genki Ueno

2008-01-01

384

NASA Astrophysics Data System (ADS)

A molecular dynamics calculation of the amino acid polar requirement is used to score the canonical genetic code. Monte Carlo simulation shows that this computational polar requirement has been optimized by the canonical genetic code, an order of magnitude more than any previously known measure, effectively ruling out a vertical evolution dynamics. The sensitivity of the optimization to the precise metric used in code scoring is consistent with code evolution having proceeded through the communal dynamics of statistical proteins using horizontal gene transfer, as recently proposed. The extreme optimization of the genetic code therefore strongly supports the idea that the genetic code evolved from a communal state of life prior to the last universal common ancestor.

Butler, Thomas; Goldenfeld, Nigel; Mathew, Damien; Luthey-Schulten, Zaida

2009-06-01

385

Discrete Adjoint-Based Design Optimization of Unsteady Turbulent Flows on Dynamic Unstructured Grids

NASA Technical Reports Server (NTRS)

An adjoint-based methodology for design optimization of unsteady turbulent flows on dynamic unstructured grids is described. The implementation relies on an existing unsteady three-dimensional unstructured grid solver capable of dynamic 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 dynamic 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 optimization methodology for the true time-dependent formulation of the Navier-Stokes equations in a practical computational code. Large-scale shape optimizations are demonstrated for turbulent flows over a tiltrotor geometry and a simulated aeroelastic motion of a fighter jet.

Nielsen, Eric J.; Diskin, Boris; Yamaleev, Nail K.

2009-01-01

386

INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization

It is well-known that dynamic 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 dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic 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 dynamic 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 dynamic programming code runs several times faster than these other methods.

Groer, Christopher S [ORNL; Sullivan, Blair D [ORNL; Weerapurage, Dinesh P [ORNL

2012-10-01

387

NASA Technical Reports Server (NTRS)

This note shows that the optimal control of dynamic systems with uncertain parameters has certain limitations. In particular, by means of a simple scalar linear-quadratic optimal 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.

Athans, M.; Ku, R.; Gershwin, S. B.

1977-01-01

388

NASA Technical Reports Server (NTRS)

This note shows that the optimal control of dynamic systems with uncertain parameters has certain limitations. In particular, by means of a simple scalar linear-quadratic optimal 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.

Athans, M.; Ku, R.; Gershwin, S. B.

1977-01-01

389

Integration of dynamic, aerodynamic, and structural optimization of helicopter rotor blades

NASA Technical Reports Server (NTRS)

Summarized here is the first six years of research into the integration of structural, dynamic, and aerodynamic considerations in the design-optimization process for rotor blades. Specifically discussed here is the application of design optimization techniques for helicopter rotor blades. The reduction of vibratory shears and moments at the blade root, aeroelastic stability of the rotor, optimum airframe design, and an efficient procedure for calculating system sensitivities with respect to the design variables used are discussed.

Peters, David A.

1991-01-01

390

An enhanced integrated aerodynamic load\\/dynamic optimization procedure for helicopter rotor blades

An enhanced integrated aerodynamic load\\/dynamic optimization procedure is developed for minimizing vibratory root shears and moments of a helicopter rotor blade. The optimization problem is formulated with 4\\/rev inplane shears at the blade root as objective functions. Constraints are imposed on 3\\/rev radial shear, 3\\/rev flapping and torsional moments, 4\\/rev lagging moment, blade natural frequencies, weight, autorotational inertia, centrifugal stress

A. Chattopadhyay; Y. D. Chiu

1992-01-01

391

Download - Optimization Online

Oct 20, 2003 ... the unpublished COCONUT report [36]. ...... M.R. Garey and D.S. Johnson, Computers and Intractability, Freeman, San Francisco, ... [112] R.E. Gomory, An algorithm for the mixed integer problem, RM-2597, The Rand Cor-.

2003-10-20

392

Notes on optimality of direct characterisation of quantum dynamics

We argue that the claimed optimality of a new process tomography method suggested in [quant-ph/0601033] and [quant-ph/0601034] is based on not completely fair comparison that does not take into account the available information in an equal way. We also argue that the method is not a new process tomography scheme, but rather represents an interesting modification of ancilla assisted process tomography method. In our opinion these modifications require deeper understanding and further investigation.

Mario Ziman

2006-03-17

393

Dynamic modeling and optimization for space logistics using time-expanded networks

NASA Astrophysics Data System (ADS)

This research develops a dynamic logistics network formulation for lifecycle optimization of mission sequences as a system-level integrated method to find an optimal combination of technologies to be used at each stage of the campaign. This formulation can find the optimal transportation architecture considering its technology trades over time. The proposed methodologies are inspired by the ground logistics analysis techniques based on linear programming network optimization. Particularly, the time-expanded network and its extension are developed for dynamic space logistics network optimization 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 dynamic system-level trades over time and give recommendation of the optimal 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.

Ho, Koki; de Weck, Olivier L.; Hoffman, Jeffrey A.; Shishko, Robert

2014-12-01

394

System design optimization for stand-alone photovoltaic systems sizing by using superstructure model

NASA Astrophysics Data System (ADS)

Although the photovoltaic (PV) systems have been increasingly installed as an alternative and renewable green power generation, the initial set up cost, maintenance cost and equipment mismatch are some of the key issues that slows down the installation in small household. This paper presents the design optimization of stand-alone photovoltaic systems using superstructure model where all possible types of technology of the equipment are captured and life cycle cost analysis is formulated as a mixed integer programming (MIP). A model for investment planning of power generation and long-term decision model are developed in order to help the system engineer to build a cost effective system.

Azau, M. A. M.; Jaafar, S.; Samsudin, K.

2013-06-01

395

Optimal input design for aircraft parameter estimation using dynamic programming principles

NASA Technical Reports Server (NTRS)

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic 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 dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Klein, Vladislav; Morelli, Eugene A.

1990-01-01

396

NASA Technical Reports Server (NTRS)

The fundamental limitations of the optimal control of dynamic systems with random parameters are analyzed by studying a scalar linear-quadratic optimal control example. It is demonstrated that optimum long-range decision making is possible only if the dynamic 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.

Athans, M.; Ku, R.; Gershwin, S. B.

1976-01-01

397

Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

NASA Technical Reports Server (NTRS)

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic 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 dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Morelli, Eugene A.; Klein, Vladislav

1990-01-01

398

NASA Technical Reports Server (NTRS)

This paper considers an H2 optimization 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 optimization problems. The paper constructs and parameterizes all the static and dynamic H2 optimal state feedback solutions. Moreover, all the eigenvalues of an optimal closed-loop system are characterized. All optimal closed-loop systems share a set of eigenvalues which are termed here as the optimal fixed modes. Every H2 optimal controller must assign among the closed-loop eigenvalues the set of optimal fixed modes. This set of optimal fixed modes includes a set of optimal fixed decoupling zeros which shows the minimum absolutely necessary number and locations of pole-zero cancellations present in any H2 optimal design. It is shown that both the sets of optimal fixed modes and optimal fixed decoupling zeros do not vary depending upon whether the static or the dynamic controllers are used.

Chen, Ben M.; Saberi, Ali; Sannuti, Peddapullaiah; Shamash, Yacov

1993-01-01

399

Dynamic Stability Optimization of Laminated Composite Plates under Combined Boundary Loading

NASA Astrophysics Data System (ADS)

Dynamic stability and design optimization of laminated simply supported plates under planar conservative boundary loads are investigated in current study. Examples can be found in internal connecting elements of spacecraft and aerospace structures subjected to edge axial and shear loads. Designation of such elements is function of layup configuration, plate aspect ratio, loading combinations, and layup thickness. An optimum design aims maximum stability load satisfying a predefined stable vibration frequency. The interaction between compound loading and layup angle parameter affects the order of merging vibration modes and may stabilize the dynamic response. Laminated plates are assumed to be angle-plies symmetric to mid-plane surface. Dynamic equilibrium PDE has been solved using kernel integral transformation for modal frequency values and eigenvalue-based orthogonal functions for critical stability loads. The dictating dynamic stability mode is shown to be controlled by geometric stiffness distributions of composite plates. Solution of presented design optimization problem has been done using analytical approach combined with interior penalty multiplier algorithm. The results are verified by FEA approach and stability zones of original and optimized plates are stated as final data. Presented method can help designers to stabilize the dynamic response of composite plates by selecting an optimized layup orientation and thickness for prescribed design circumstances.

Shafei, Erfan; Kabir, Mohammad Zaman

2011-12-01

400

A new method of optimal design for a two-dimensional diffuser by using dynamic programming

NASA Technical Reports Server (NTRS)

A new method for predicting the optimal velocity distribution on the wall of a two dimensional diffuser is presented. The method uses dynamic programming to solve the optimal control problem with inequality constraints of state variables. The physical model of optimization 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. Optimal 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 optimal velocity distribution can be used to design the contour of the diffuser.

Gu, Chuangang; Zhang, Moujin; Chen, XI; Miao, Yongmiao

1991-01-01

401

Shape optimization of the diffuser blade of an axial blood pump by computational fluid dynamics.

Computational fluid dynamics (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 optimization of the diffuser blade to enhance pressure output and diminish backflow in the impeller-diffuser connecting region at a fixed design point. Our optimization combined a computer-aided design package, a mesh generator, and a CFD solver in an automation environment with process integration and optimization software. A genetic optimization algorithm was employed to find the pareto-optimal 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. PMID:20447042

Zhu, Lailai; Zhang, Xiwen; Yao, Zhaohui

2010-03-01

402

An optimized ultrasound digital beamformer with dynamic focusing implemented on FPGA.

We present a resource-optimized dynamic digital beamformer for an ultrasound system based on a field-programmable gate array (FPGA). A comprehensive 64-channel receive beamformer with full dynamic focusing is embedded in the Altera Arria V FPGA chip. To improve spatial and contrast resolution, full dynamic beamforming is implemented by a novel method with resource optimization. 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 dynamic beamformer architecture is amenable for a low power FPGA-based implementation in a portable ultrasound system. PMID:25570695

Almekkawy, Mohamed; Xu, Jingwei; Chirala, Mohan

2014-01-01

403

Optimal foot shape for a passive dynamic biped

Passive walking dynamics describe the motion of a biped that is able to “walk” down a shallow slope without any actuation or control. Instead, the walker relies on gravitational and inertial effects to propel itself forward, exhibiting a gait quite similar to that of humans. These purely passive models depend on potential energy to overcome the energy lost when the

Maxine Kwan; Mont Hubbard

2007-01-01

404

Optimal design of stochastic production lines: a dynamic programming approach

We consider the problem of choosing the number and type of machines for each station in a new production line where the sequence of processes (i.e., manufacturing recipe) has already been established. We formulate a model to minimize cost (investment plus operating) subject to constraints on throughput and cycle time. Using queueing network approximations within a dynamic programming framework, we

KAREN L. DONOHUE; WALLACE J. HOPP; MARK L. SPEARMAN

2002-01-01

405

Optimization of the dynamic behavior of strongly nonlinear heterogeneous materials

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 dynamic testing. These materials are

Eric B. Herbold

2008-01-01

406

Dale's Principle is necessary for an optimal neuronal network's dynamics

set of bio- chemical substances (called neurotransmitters) to the other neurons that are connectedÂ´ublica and ANII of Uruguay. 1 #12;Nevertheless, during plastic phases of the nervous systems network. This plasticity allows the network perform diverse and adequate dynamical re- sponses to external

407

A static optimization approach to assess dynamic available transfer capability

This paper deals with the development of a nonlinear programming methodology for evaluating available transfer capability. The main feature of the approach is the capability to treat static and dynamic security constraints in a unique integrated piece of software. The algorithm has been implemented and tested on an actual power system

E. de Tuglie; M. Dicorato; M. La Scala; P. Scarpellini

1999-01-01

408

A static optimization approach to assess dynamic available transfer capability

This paper deals with the development of a nonlinear programming methodology for evaluating available transfer capability. The main feature of the approach is the capability to treat static and dynamic security constraints in a unique integrated piece of software. The algorithm has been implemented and tested on an actual power system

Enrico De Tuglie; Maria Dicorato; Massimo La Scala; Pierangelo Scarpellini

2000-01-01

409

Optimal dynamic dispatch owing to spinning-reserve and power-rate limits

This paper deals with the formulation and solution of the optimal dynamic dispatch problem owing to spinning-reserve and power-rate limits. The power production of a thermal unit is considered as a dynamic system, which limits the maximum increase and decrease of power. The solution is obtained with a special projection method having conjugate search directions that quickly and accurately solves the associated non-linear programming problem with up to 2400 variables and up to 9600 constraints.

Van den Bosh, P.P.J.

1985-12-01

410

Dynamic simulation and optimal control strategy of a decentralized supply chain system

Efficient management of inventory in supply chains is critical to the profitable operation of modern enterprises. The supply\\/demand networks characteristic of discrete-parts industries represent highly stochastic, nonlinear, and constrained dynamical systems whose study merits a control-oriented approach. Minimum variance control (MVC) strategy is applied to solve the dynamic optimization problems of the inventory for a decentralized supply chain system. Transfer

Dong Hai; Li Yan-ping

2009-01-01

411

On the optimal reconstruction and control of adaptive optical systems with mirror dynamics.

In adaptive optics (AO) the deformable mirror (DM) dynamics are usually neglected because, in general, the DM can be considered infinitely fast. Such assumption may no longer apply for the upcoming Extremely Large Telescopes (ELTs) with DM that are several meters in diameter with slow and/or resonant responses. For such systems an important challenge is to design an optimal regulator minimizing the variance of the residual phase. In this contribution, the general optimal minimum-variance (MV) solution to the full dynamical reconstruction and control problem of AO systems (AOSs) is established. It can be looked upon as the parent solution from which simpler (used hitherto) suboptimal solutions can be derived as special cases. These include either partial DM-dynamics-free solutions or solutions derived from the static minimum-variance reconstruction (where both atmospheric disturbance and DM dynamics are neglected altogether). Based on a continuous stochastic model of the disturbance, a state-space approach is developed that yields a fully optimal MV solution in the form of a discrete-time linear-quadratic-Gaussian (LQG) regulator design. From this LQG standpoint, the control-oriented state-space model allows one to (1) derive the optimal state-feedback linear regulator and (2) evaluate the performance of both the optimal and the sub-optimal solutions. Performance results are given for weakly damped second-order oscillatory DMs with large-amplitude resonant responses, in conditions representative of an ELT AO system. The highly energetic optical disturbance caused on the tip/tilt (TT) modes by the wind buffeting is considered. Results show that resonant responses are correctly handled with the MV regulator developed here. The use of sub-optimal regulators results in prohibitive performance losses in terms of residual variance; in addition, the closed-loop system may become unstable for resonant frequencies in the range of interest. PMID:20126246

Correia, Carlos; Raynaud, Henri-François; Kulcsár, Caroline; Conan, Jean-Marc

2010-02-01

412

NASA Astrophysics Data System (ADS)

Recent contributions to the ecohydrological literature have questioned the continued usefulness of the classical model calibration paradigm to estimating parameters in coupled models of soil moisture dynamics, ecophysiological gas exchange and photosynthesis. In their seminal papers, (Kleidon, 2004; Kleidon, 2007; Schymanski et al., 2007; Schymanski et al., 2008a) have demonstrated that the principle of vegetation optimality provides an attractive and parsimonious alternative to using site specific calibration measurements for estimating vegetation cover, rooting depth, transpiration fluxes, and CO2 assimilation. Optimality based approaches not only reduce the need for detailed field measurements, but also provide flexible frameworks to continuously adapt vegetation responses to changing environmental conditions. Yet, the main focus in optimality-based approaches has been on finding a single optimal combination of ecohydrological parameter values. This approach downplays the importance of variability, and implicitly ignores model and measurement uncertainty. Here we show that significant advances to optimality based modelling can be made if we embrace a novel concept of stochastic optimization that includes explicit recognition of parameter uncertainty. To illustrate our ideas, we develop a multi-layer soil and canopy Vegetation Optimality Model, hereafter referred to as VOM(mlsc), and apply this extended VOM model to a Douglas Fir stand in the Netherlands. We use the DiffeRential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo algorithm for parameter exploration with NCP as optimality criteria. Our results show that significant dispersion exists in optimized vegetation structure and properties from optimality of NCP, and that modelled and measured H2O and CO2 fluxes compare rather poorly. These findings question the usefulness of NCP as single optimality criteria, and advocate the simultaneous use of multiple non-commensurable (optimality) criteria for ecohydrological parameter estimation and model evaluation.

Dekker, S. C.; Elkington, R. J.; Vrugt, J. A.

2009-04-01

413

A new multiobjective dynamic 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 optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically 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 dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model. PMID:24982962

Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari

2014-01-01

414

A new multiobjective dynamic 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 optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically 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 dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model. PMID:24982962

Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari

2014-01-01

415

Dynamic programming algorithm optimization for spoken word recognition

This paper reports on an optimum dynamic progxamming (DP) based time-normalization algorithm for spoken word recognition. First, a general principle of time-normalization is given using time-warping function. Then, two time-normalized distance definitions, called symmetric and asymmetric forms, are derived from the principle. These two forms are compared with each other through theoretical discussions and experimental studies. The symmetric form algorithm

HIROAKI SAKOE; SEIBI CHIBA

1978-01-01

416

Improving the dynamic characteristics of body-in-white structure using structural optimization.

The dynamic 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 dynamic 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 optimization subjected to dynamic 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 optimization using mass and natural frequencies as the design variables. The individual components obtained from the analysis go through a size optimization 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 optimization steps suggest several design modifications to achieve the target vibration specifications without compromising the stiffness of the structure. A method of combining both optimization approaches is proposed to improve the design modification process. PMID:25101312

Yahaya Rashid, Aizzat S; Ramli, Rahizar; Mohamed Haris, Sallehuddin; Alias, Anuar

2014-01-01

417

Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic 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 dynamics of the PDE system. Subsequently, the optimal 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 optimal 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 optimal 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. PMID:25794375

Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong

2015-04-01

418

Optimal control landscape for the generation of unitary transformations with constrained dynamics

The reliable and precise generation of quantum unitary transformations is essential for the realization of a number of fundamental objectives, such as quantum control and quantum information processing. Prior work has explored the optimal control problem of generating such unitary transformations as a surface-optimization problem over the quantum control landscape, defined as a metric for realizing a desired unitary transformation as a function of the control variables. It was found that under the assumption of nondissipative and controllable dynamics, the landscape topology is trap free, which implies that any reasonable optimization heuristic should be able to identify globally optimal solutions. The present work is a control landscape analysis, which incorporates specific constraints in the Hamiltonian that correspond to certain dynamical symmetries in the underlying physical system. It is found that the presence of such symmetries does not destroy the trap-free topology. These findings expand the class of quantum dynamical systems on which control problems are intrinsically amenable to a solution by optimal control.

Hsieh, Michael [Center for Quantum Information Science and Technology, University of Southern California, Los Angeles, California 90089 (United States); Department of Chemistry, University of Southern California, Los Angeles, California 90089 (United States); Wu, Rebing [Department of Automation, Tsinghua University, Beijing, 100084 (China); Rabitz, Herschel [Department of Chemistry, Princeton University, Princeton, New Jersey 08544 (United States); Lidar, Daniel [Center for Quantum Information Science and Technology, University of Southern California, Los Angeles, California 90089 (United States); Department of Chemistry, University of Southern California, Los Angeles, California 90089 (United States); Department of Electrical Engineering, University of Southern California, Los Angeles, California 90089 (United States); Department of Physics, University of Southern California, Los Angeles, California 90089 (United States)

2010-06-15

419

An optimality-based model of the coupled soil moisture and root dynamics

NASA Astrophysics Data System (ADS)

The main processes determining soil moisture dynamics are infiltration, percolation, evaporation and root water uptake. Modelling soil moisture dynamics therefore requires an interdisciplinary approach that links hydrological, atmospheric and biological processes. Previous approaches treat either root water uptake rates or root distributions and transpiration rates as given, and calculate the soil moisture dynamics based on the theory of flow in unsaturated media. The present study introduces a different approach to linking soil water and vegetation dynamics, based on vegetation optimality. Assuming that plants have evolved mechanisms that minimise costs related to the maintenance of the root system while meeting their demand for water, we develop a model that dynamically adjusts the vertical root distribution in the soil profile to meet this objective. The model was used to compute the soil moisture dynamics, root water uptake and fine root respiration in a tropical savanna over 12 months, and the results were compared with observations at the site and with a model based on a fixed root distribution. The optimality-based model reproduced the main features of the observations such as a shift of roots from the shallow soil in the wet season to the deeper soil in the dry season and substantial root water uptake during the dry season. At the same time, simulated fine root respiration rates never exceeded the upper envelope determined by the observed soil respiration. The model based on a fixed root distribution, in contrast, failed to explain the magnitude of water use during parts of the dry season and largely over-estimated root respiration rates. The observed surface soil moisture dynamics were also better reproduced by the optimality-based model than the model based on a prescribed root distribution. The optimality-based approach has the potential to reduce the number of unknowns in a model (e.g. the vertical root distribution), which makes it a valuable alternative to more empirically-based approaches, especially for simulating possible responses to environmental change.

Schymanski, S. J.; Sivapalan, M.; Roderick, M. L.; Beringer, J.; Hutley, L. B.

2008-06-01

420

An optimality-based model of the coupled soil moisture and root dynamics

NASA Astrophysics Data System (ADS)

The main processes determining soil moisture dynamics are infiltration, percolation, evaporation and root water uptake. Modelling soil moisture dynamics therefore requires an interdisciplinary approach that links hydrological, atmospheric and biological processes. Previous approaches treat either root water uptake rates or root distributions and transpiration rates as given, and calculate the soil moisture dynamics based on the theory of flow in unsaturated media. The present study introduces a different approach to linking soil water and vegetation dynamics, based on vegetation optimality. Assuming that plants have evolved mechanisms that minimise costs related to the maintenance of the root system while meeting their demand for water, we develop a model that dynamically adjusts the vertical root distribution in the soil profile to meet this objective. The model was used to compute the soil moisture dynamics, root water uptake and fine root respiration in a tropical savanna over 12 months, and the results were compared with observations at the site and with a model based on a fixed root distribution. The optimality-based model reproduced the main features of the observations such as a shift of roots from the shallow soil in the wet season to the deeper soil in the dry season and substantial root water uptake during the dry season. At the same time, simulated fine root respiration rates never exceeded the upper envelope determined by the observed soil respiration. The model based on a fixed root distribution, in contrast, failed to explain the magnitude of water use during parts of the dry season and largely over-estimated root respiration rates. The observed surface soil moisture dynamics were also better reproduced by the optimality-based model than the model based on a prescribed root distribution. The optimality-based approach has the potential to reduce the number of unknowns in a model (e.g. the vertical root distribution), which makes it a valuable alternative to more empirically-based approaches, especially for simulating possible responses to environmental change.

Schymanski, S. J.; Sivapalan, M.; Roderick, M. L.; Beringer, J.; Hutley, L. B.

2008-01-01

421

Determination of Optimal Parameters of Distributive Gas Pipeline by Dynamic Programming Method

In this article we present a model for determination of optimal parameters of main distributive gas pipelines by dynamic programming (DP) methods. The basic characteristic of this gas pipeline system is that the transported gas quantities are variables. This article presents DP techniques for solving the problem of minimizing investment costs of gas pipeline building. The main objective of this

D. Danilovic; V. K. Maricic; I. Ristovic

2011-01-01

422

The Dynamic Programming Equation for the Problem of Optimal Investment Under Capital Gains Taxes

This paper considers an extension of the Merton optimal investment problem to the case where the risky asset is subject to transaction costs and capital gains taxes. We derive the dynamic programming equation in the sense of constrained viscosity solutions. We next introduce a family of functions (V?)?>0, which converges to our value function uniformly on compact subsets, and which

Imen Ben Tahar; H. Mete Soner; Nizar Touzi

2007-01-01

423

Efficient Dynamic Modeling, Numerical Optimal Control and Experimental Results for Various Gaits

and entertainment robot, there also exist worldwide competitions for teams of autonomous soccer playing robots (www of a Quadruped Robot M STELZER, M HARDT and O von STRYK Simulation and Systems Optimization, Technische Universit robots based on nonlinear multi- body dynamics models of legged locomotion have made progress recently

Stryk, Oskar von

424

Optimization of Fed-Batch Saccharomyces cereWisiae Fermentation Using Dynamic Flux Balance Models

is that nutrient levels can be varied to achieve favorable growth conditions. Fed-batch yeast fermentation-batch yeast fermenters have been extensively investigated (10-15). These studies were based on simpleARTICLES Optimization of Fed-Batch Saccharomyces cereWisiae Fermentation Using Dynamic Flux Balance

Mountziaris, T. J.

425

Prerequisites: Engine Systems, Dynamic Programming and Optimal Control, MATLAB/Simulink

Prerequisites: Engine Systems, Dynamic Programming and Optimal Control, MATLAB/Simulink Contact: Mu to be carefully controlled. Nowadays, the SCR control is tuned independently from the engine emission control, the objective of this work is to develop a control structure for integrated control of the system "Engine + SCR

Lygeros, John

426

between these robots must be feasible. In many such applications, there exists a need to coordi nateAbstract Planning for multiple mobile robots in dynamic environ ments involves determining the optimal path each robot should follow to accomplish the goals of the mission, given the current knowledge

Stentz, Tony

427

Cross-Layer Optimized Routing for Wireless Sensor Networks Using Dynamic Programming

In this paper, we study the joint optimization problem on channel coding, power allocation, and route planning in wireless sensor networks (WSN) using dynamic programming (DP). Each sensor node has multiple antennas and applies orthogonal space time block codes (OSTBC) in order to improve the transmission reliability. A decode-and-forward protocol is adopted to relay the signals. The objective function is

Lingyang Song; Yan Zhang; Rong Yu; Wenqing Yao; Zhuo Wu

2009-01-01

428

Optimal Passive Dynamics for Torque/Force Control Kevin Kemper, Devin Koepl and Jonathan Hurst

Optimal Passive Dynamics for Torque/Force Control Kevin Kemper, Devin Koepl and Jonathan Hurst-- For robotic manipulation tasks in uncertain envi- ronments, good force control can provide significant benefits. The design of force-controlled actuators typically revolves around developing the best possible

Hurst, Jonathan

429

The shortest path algorithm is critical for dynamic traffic assignment and for the realization of route guidance in intelligent transportation systems (ITS). In this paper, a hybrid Particle Swarm Optimization (PSO) algorithm combined fluid neural network (FNN) to search for the shortest path in stochastic traffic networks is introduced. The algorithm overcomes the weight coefficient symmetry restrictions of the traditional

Yanfang Deng; Hengqing Tong; Xiedong Zhang

2010-01-01

430

Dynamic clustering using particle swarm optimization with application in image segmentation

A new dynamic clustering approach (DCPSO), based on particle swarm optimization, is proposed. This approach is applied to image segmentation. The proposed approach automatically determines the “optimum” number of clusters and simultaneously clusters the data set with minimal user interference. The algorithm starts by partitioning the data set into a relatively large number of clusters to reduce the effects of

Mahamed G. H. Omran; Ayed A. Salman; Andries Petrus Engelbrecht

2006-01-01

431

Dynamic Control and Optimization of Buffer Size for Short Message Transfer in GPRS/UMTS Networks*

System for Mobile Communications (GSM) networks, controlling the most successful wireless data serviceDynamic Control and Optimization of Buffer Size for Short Message Transfer in GPRS/UMTS Networks, emerges a need to control the traffic generated using the capabilities of the existent infrastructure

Panayiotou, Christos

432

New multimedia embedded applications are increasingly dy- namic, and rely on Dynamically-allocated Data Types (DDTs) to store their data. The optimization of DDTs for each tar- get embedded system is a time-consuming process due to the large design space of possible DDTs implementations. Thus, suitable exploration methods for embedded design metrics (memory accesses, memory usage and power consumption) need to

José Ignacio Hidalgo; José L. Risco-martín; David Atienza; Juan Lanchares

2008-01-01

433

Dynamic optimization of batch processes II. Role of measurements in handling uncertainty

Dynamic optimization of batch processes II. Role of measurements in handling uncertainty B at the industrial level is the presence of uncertainty in the form of model mismatch and disturbances. The way approaches are compared via the simulation of a bioreactor for penicillin production. # 2002 Elsevier Science

Palanki, Srinivas

434

Optimal dynamic scheduling in a multiclass fluid model of Internet servers with transient overload

We consider the optimal dynamic scheduling of different requests of service in a multiclass stochastic fluid model that is motivated by recent and emerging computing paradigms for Internet services and applications. Our primary focus is on environments with specific performance guarantees for each class under a profit model in which revenues are gained when performance guarantees are satisfied and penalties

Junxia Chang; Hayriye Ayhan; Jim Dai; Zhen Liu; Mark S. Squillante; Cathy H. Xia

2003-01-01

435

Optimal Security Design and Dynamic Capital Structure in a Continuous-Time Agency Model

the credit line when it realizes a profit. Thus, in our model leverage is negatively related with pastOptimal Security Design and Dynamic Capital Structure in a Continuous-Time Agency Model PETER M. Leverage is nonstationary, and declines with past profitability. The firm may hold a compensating cash

436

Optimal intervention in the foreign exchange market when interventions affect market dynamics

, foreign exchange intervention. 1 Introduction In countries dependent on foreign trade and foreign capitalOptimal intervention in the foreign exchange market when interventions affect market dynamics Alec) forms: adjustment of domestic interest rate levels, which influences the attractiveness of foreign

Aluffi, Paolo

437

Optimal solid shells for non-linear analyses of multilayer composites. II. Dynamics

Optimal solid shells for non-linear analyses of multilayer composites. II. Dynamics L. Vu-Quoc *, X Ekkehard Ramm for his 60th anniversary Abstract We are presenting a simple low-order solid-shell element of large deformable multilayer shell structures using elements at extremely high aspect ratio

Vu-Quoc, Loc

438

Content-based medical image retrieval using dynamically optimized regional features

This paper proposes a content-based medical image retrieval (CBMIR) framework using dynamically optimized features from multiple regions of medical images. These regional features, including structural and statistical properties of color, texture and geometry, are extracted from multiple dominant regions segmented by applying Gaussian mixture modeling (GMM) and the expectation maximization (EM) algorithm to medical images. Over them, principal component analysis

Wei Xiong; Bo Qiu; Qi Tian; Changsheng Xu; Sim Heng Ong; Kelvin W. C. Foong

2005-01-01

439

A wave dynamics criterion for optimization of mammalian cardiovascular system.

The cardiovascular system in mammals follows various optimization criteria covering the heart, the vascular network, and the coupling of the two. Through a simple dimensional analysis we arrived at a non-dimensional number (wave condition number) that can predict the optimum wave state in which the left ventricular (LV) pulsatile power (LV workload) is minimized in a mammalian cardiovascular system. This number is also universal among all mammals independent of animal size maintaining a value of around 0.1. By utilizing a unique in vitro model of human aorta, we tested our hypothesis against a wide range of aortic compliance (pulse wave velocity). We concluded that the optimum value of the wave condition number remains to be around 0.1 for a wide range of aorta compliance that we could simulate in our in-vitro system. PMID:24642352

Pahlevan, Niema M; Gharib, Morteza

2014-05-01

440

Locusts use dynamic thermoregulatory behaviour to optimize nutritional outcomes

Because key nutritional processes differ in their thermal optima, ectotherms may use temperature selection to optimize performance in changing nutritional environments. Such behaviour would be especially advantageous to small terrestrial animals, which have low thermal inertia and often have access to a wide range of environmental temperatures over small distances. Using the locust, Locusta migratoria, we have demonstrated a direct link between nutritional state and thermoregulatory behaviour. When faced with chronic restrictions to the supply of nutrients, locusts selected increasingly lower temperatures within a gradient, thereby maximizing nutrient use efficiency at the cost of slower growth. Over the shorter term, when locusts were unable to find a meal in the normal course of ad libitum feeding, they immediately adjusted their thermoregulatory behaviour, selecting a lower temperature at which assimilation efficiency was maximal. Thus, locusts use fine scale patterns of movement and temperature selection to adjust for reduced nutrient supply and thereby ameliorate associated life-history consequences. PMID:21288941

Coggan, Nicole; Clissold, Fiona J.; Simpson, Stephen J.

2011-01-01

441

Characterization of control noise effects in optimal quantum unitary dynamics

NASA Astrophysics Data System (ADS)

This work develops measures for quantifying the effects of field noise upon targeted unitary transformations. Robustness to noise is assessed in the framework of the quantum control landscape, which is the mapping from the control to the unitary transformation performance measure (quantum gate fidelity). Within that framework, a geometric interpretation of stochastic noise effects naturally arises, where more robust optimal controls are associated with regions of small overlap between landscape curvature and the noise correlation function. Numerical simulations of this overlap in the context of quantum information processing reveal distinct noise spectral regimes that better support robust control solutions. This perspective shows the dual importance of both noise statistics and the control form for robustness, thereby opening up new avenues of investigation on how to mitigate noise effects in quantum systems.

Hocker, David; Brif, Constantin; Grace, Matthew D.; Donovan, Ashley; Ho, Tak-San; Tibbetts, Katharine Moore; Wu, Rebing; Rabitz, Herschel

2014-12-01

442

Characterization of control noise effects in optimal quantum unitary dynamics

This work develops measures for quantifying the effects of field noise upon targeted unitary transformations. Robustness to noise is assessed in the framework of the quantum control landscape, which is the mapping from the control to the unitary transformation performance measure (quantum gate fidelity). Within that framework, a new geometric interpretation of stochastic noise effects naturally arises, where more robust optimal controls are associated with regions of small overlap between landscape curvature and the noise correlation function. Numerical simulations of this overlap in the context of quantum information processing reveal distinct noise spectral regimes that better support robust control solutions. This perspective shows the dual importance of both noise statistics and the control form for robustness, thereby opening up new avenues of investigation on how to mitigate noise effects in quantum systems.

David Hocker; Constantin Brif; Matthew D. Grace; Ashley Donovan; Tak-San Ho; Katharine Moore Tibbetts; Rebing Wu; Herschel Rabitz

2014-11-13

443

In this paper, we develop and analyze an optimal control method for a class of discrete-time nonlinear Markov jump systems (MJSs) with unknown system dynamics. Specifically, an identifier is established for the unknown systems to approximate system states, and an optimal control approach for nonlinear MJSs is developed to solve the Hamilton-Jacobi-Bellman equation based on the adaptive dynamic programming technique. We also develop detailed stability analysis of the control approach, including the convergence of the performance index function for nonlinear MJSs and the existence of the corresponding admissible control. Neural network techniques are used to approximate the proposed performance index function and the control law. To demonstrate the effectiveness of our approach, three simulation studies, one linear case, one nonlinear case, and one single link robot arm case, are used to validate the performance of the proposed optimal control method. PMID:25420238

Zhong, Xiangnan; He, Haibo; Zhang, Huaguang; Wang, Zhanshan

2014-12-01

444

NASA Technical Reports Server (NTRS)

A description and applications of a computer capability for determining the ultimate optimal behavior of a dynamically 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 optimization 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 optimization. The report contains user-oriented program documentation in engineering, problem-oriented form. Applications cover a wide variety of dynamics problems including those associated with such diverse configurations as a missile-silo system, impacting freight cars, and an aircraft ride control system.

Pilkey, W. D.; Wang, B. P.; Yoo, Y.; Clark, B.

1973-01-01

445

Scaling and optimization of the radiation temperature in dynamic hohlraums

The authors have constructed a quasi-analytic model of the dynamic 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.

SLUTZ,STEPHEN A.; DOUGLAS,MELISSA R.; LASH,JOEL S.; VESEY,ROGER A.; CHANDLER,GORDON A.; NASH,THOMAS J.; DERZON,MARK S.

2000-04-13

446

According to limitation of traditional methods, a new optimization model of reactive power compensation of power system including distributed generation is proposed, in which investment of the equipment, electrovalence and other factors of the complex power network are considered. According to the optimization model, an optimization scheme of fuzzy dynamic programming is introduced, in which fuzzy theory is used to

Peng Peng; Shi-ping Su; Xi Luo; Li-quan Fan

2008-01-01

447

Optimization of rotor blades for combined structural, dynamic, and aerodynamic properties

NASA Technical Reports Server (NTRS)

Optimal helicopter blade design with computer-based mathematical programming has received more and more attention in recent years. Most of the research has focused on optimum dynamic characteristics of rotor blades to reduce vehicle vibration. There is also work on optimization of aerodynamic performance and on composite structural design. This research has greatly increased our understanding of helicopter optimum design in each of these aspects. Helicopter design is an inherently multidisciplinary process involving strong interactions among various disciplines which can appropriately include aerodynamics; dynamics, both flight dynamics and structural dynamics; aeroelasticity: vibrations and stability; and even acoustics. Therefore, the helicopter design process must satisfy manifold requirements related to the aforementioned diverse disciplines. In our present work, we attempt to combine several of these important effects in a unified manner. First, we design a blade with optimum aerodynamic performance by proper layout of blade planform and spanwise twist. Second, the blade is designed to have natural frequencies that are placed away from integer multiples of the rotor speed for a good dynamic characteristics. Third, the structure is made as light as possible with sufficient rotational inertia to allow for autorotational landing, with safe stress margins and flight fatigue life at each cross-section, and with aeroelastical stability and low vibrations. Finally, a unified optimization refines the solution.

He, Cheng-Jian; Peters, David A.

1990-01-01

448

Multibody dynamics simulations are currently widely accepted as valuable means for dynamic performance analysis of mechanical systems. The evolution of theoretical and computational aspects of the multibody dynamics discipline make it conducive these days for other types of applications, in addition to pure simulations. One very important such application is design optimization. A very important first step towards design optimization is sensitivity analysis of multibody system dynamics. Dynamic sensitivities are often calculated by means of finite differences. Depending of the number of parameters involved, this procedure can be computationally expensive. Moreover, in many cases, the results suffer from low accuracy when real perturbations are used. The main contribution to the state-of-the-art brought by this study is the development of the adjoint sensitivity approach of multibody systems in the context of the penalty formulation. The theory developed is demonstrated on one academic case study, a five-bar mechanism, and on one real-life system, a 14-DOF vehicle model. The five-bar mechanism is used to illustrate the sensitivity approach derived in this paper. The full vehicle model is used to demonstrate the capability of the new approach developed to perform sensitivity analysis and gradient-based optimization for large and complex multibody systems with respect to multiple design parameters.

Yitao Zhu; Daniel Dopico; Corina Sandu; Adrian Sandu

2014-10-30

449

NASA Technical Reports Server (NTRS)

A challenge for the fluid dynamics 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 Optimization (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 Optimization, the MDO technical community focuses on vehicle and system design issues. This paper provides an overview of the MDO technology field from a fluid dynamics perspective, giving emphasis to suggestions of specific applications of recent MDO technologies that can enhance fluid dynamics research itself across the spectrum, from basic flow physics to full configuration aerodynamics.

Zang, Thomas A.; Green, Lawrence L.

1999-01-01

450

Optimal purchasing of raw materials: A data-driven approach

An approach to the optimal 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 mixed integer nonlinear programming (MINLP) optimization 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 optimal purchasing of metallurgical coals for coke making in the steel industry.

Muteki, K.; MacGregor, J.F. [McMaster University, Hamilton, ON (Canada). Dept. of Chemical Engineering

2008-06-15

451

Optimization of the dynamic behavior of strongly nonlinear heterogeneous materials

NASA Astrophysics Data System (ADS)

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 dynamic 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 dynamic 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 powder samples in simulated drop-weight tests. The calculations indicate that the dynamic formation of mesoscale force chains increase the strength of the sample. This is also apparent in three-dimensional finite element calculations of drop-weight test simulations using LS-Dyna despite a higher granular bulk coordination number, and an increased mobility of individual grains.

Herbold, Eric B.

452

Pole vault performance for anthropometric variability via a dynamical optimal control model.

Optimal performance of a dynamical pole vault process was modeled as a constrained nonlinear optimization problem. That is, given a vaulter's anthropomorphic data and approach speed, the vaulter chose a specific take-off angle, pole stiffness and gripping height in order to yield the greatest jumping height compromised by feasible bar-crossing velocities. The optimization problem was solved by nesting a technique of searching an input-to-output mapping arising from the vaulting trajectory and a method of nonlinear sequential quadratic programming (SQP). It was suggested from the optimization results that the body's weight has an important influence on the vaulting performance beside the vaulter's height and approach speed; the less skilled vaulter should gradually adopt a longer pole to improve the performance. PMID:20980004

Liu, Guangyu; Nguang, Sing-Kiong; Zhang, Yanxin

2011-02-01

453

NASA Astrophysics Data System (ADS)

A policy iteration algorithm of adaptive dynamic programming (ADP) is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal 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 optimal 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).

Wei, Qing-Lai; Liu, De-Rong; Xu, Yan-Cai

2015-03-01

454

We present an efficient general approach to first principles molecular dynamics simulations based on 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 reduction of the optimization requirement reduces the computational cost to a minimum, but without causing any significant loss of accuracy or long-term energy drift. The optimization-free first principles molecular dynamics 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 dynamics simulations. The optimization-free limit of extended Lagrangian Born-Oppenheimer molecular dynamics therefore represents an ideal starting point for robust and efficient first principles quantum mechanical molecular dynamics simulations.

Souvatzis, Petros, E-mail: petros.souvatsiz@fysik.uu.se [Department of Physics and Astronomy, Division of Materials Theory, Uppsala University, Box 516, SE-75120, Uppsala (Sweden)] [Department of Physics and Astronomy, Division of Materials Theory, Uppsala University, Box 516, SE-75120, Uppsala (Sweden); Niklasson, Anders M. N., E-mail: amn@lanl.gov [Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States)] [Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States)

2013-12-07

455

Dynamical Arrest, Structural Disorder, and Optimization of Organic Photovoltaic Devices

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 dynamical 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.

Gould, Ian; Dmitry, Matyushov

2014-09-11

456

Drilling optimized by monitoring BHA dynamics with MWD

By measuring the drilling performance of the bottom hole assembly (BHA) in real time, the probability of serious drilling problems can be reduced. A new logging tool and service directly measures bottom hole assembly performance, thus allowing swifter and more accurate corrective measures when necessary. Drilling time savings are realized through improved rates of penetration (ROP), reduced off-bottom time, and increase life of drillstring. Advances in measurement-while-drilling (MWD) technology have facilitated the inclusion of downhole drilling dynamics measurements into the package of MWD data transmitted in real time. Thus, the actual energy input to the bit and the resistance of the formation to drilling can be measured and compared to the surface data. This provides an extremely useful analytical tool for the drilling engineer.

Sutcliffe, B. (Teleco Oilfield Services Inc., Aberdeen (GB)); Sim, D. (Teleco Oilfield Services Inc., Meriden, CT (US))

1991-03-25

457

NASA Astrophysics Data System (ADS)

The dynamically dimensioned search (DDS) continuous global optimization algorithm by Tolson and Shoemaker (2007) is modified to solve discrete, single-objective, constrained water distribution system (WDS) design problems. The new global optimization algorithm for WDS optimization is called hybrid discrete dynamically dimensioned search (HD-DDS) and combines two local search heuristics with a discrete DDS search strategy adapted from the continuous DDS algorithm. The main advantage of the HD-DDS algorithm compared with other heuristic global optimization algorithms, such as genetic and ant colony algorithms, is that its searching capability (i.e., the ability to find near globally optimal solutions) is as good, if not better, while being significantly more computationally efficient. The algorithm's computational efficiency is due to a number of factors, including the fact that it is not a population-based algorithm and only requires computationally expensive hydraulic simulations to be conducted for a fraction of the solutions evaluated. This paper introduces and evaluates the algorithm by comparing its performance with that of three other algorithms (specific versions of the genetic algorithm, ant colony optimization, and particle swarm optimization) on four WDS case studies (21- to 454-dimensional optimization problems) on which these algorithms have been found to perform well. The results obtained indicate that the HD-DDS algorithm outperforms the state-of-the-art existing algorithms in terms of searching ability and computational efficiency. In addition, the algorithm is easier to use, as it does not require any parameter tuning and automatically adjusts its search to find good solutions given the available computational budget.

Tolson, Bryan A.; Asadzadeh, Masoud; Maier, Holger R.; Zecchin, Aaron

2009-12-01

458

NASA Astrophysics Data System (ADS)

Based on the National Climate Center (NCC) of China operational seasonal prediction model results for the period 1983-2009 and the US National Weather Service Climate Prediction Center merged analysis of precipitation in the same period, together with the 74 circulation indices of NCC Climate System Diagnostic Division and 40 climate indices of NOAA of US during 1951-2009, an analogue-dynamical technique for objective and quantitative prediction of monsoon precipitation in Northeast China is proposed and implemented. Useful information is extracted from the historical data to estimate the model forecast errors. Dominant predictors and the predictors that exhibit evolving analogues are identified through cross validating the anomaly correlation coefficients (ACC) among single predictors, meanwhile with reference of the results from the dynamic analogue bias correction using four analogue samples. Next, an optimal configuration of multiple predictors is set up and compared with historical optimal multi-predictor configurations and then dynamically adjusted. Finally, the model errors are evaluated and utilized to correct the NCC operational seasonal prediction model results, and the forecast of monsoon precipitation is obtained at last. The independent sample validation shows that this technique has effectively improved the monsoon precipitation prediction skill during 2005-2009. This study demonstrates that the analogue-dynamical approach is feasible in operational prediction of monsoon precipitation.

Xiong, Kaiguo; Feng, Guolin; Huang, Jianping; Chou, Jifan

2011-06-01

459

Synthesizing optimal waste blends

Vitrification of tank wastes to form glass is a technique that will be used for the disposal of high-level waste at Hanford. Process and storage economics show that minimizing the total number of glass logs produced is the key to keeping cost as low as possible. The amount of glass produced can be reduced by blending of the wastes. The optimal way to combine the tanks to minimize the vole of glass can be determined from a discrete blend calculation. However, this problem results in a combinatorial explosion as the number of tanks increases. Moreover, the property constraints make this problem highly nonconvex where many algorithms get trapped in local minima. In this paper the authors examine the use of different combinatorial optimization approaches to solve this problem. A two-stage approach using a combination of simulated annealing and nonlinear programming (NLP) is developed. The results of different methods such as the heuristics approach based on human knowledge and judgment, the mixed integer nonlinear programming (MINLP) approach with GAMS, and branch and bound with lower bound derived from the structure of the given blending problem are compared with this coupled simulated annealing and NLP approach.

Narayan, V.; Diwekar, W.M. [Carnegie Mellon Univ., Pittsburgh, PA (United States)] [Carnegie Mellon Univ., Pittsburgh, PA (United States); Hoza, M. [Pacific Northwest Lab., Richland, WA (United States)] [Pacific Northwest Lab., Richland, WA (United States)

1996-10-01

460

Optimizing electromagnetic induction sensors for dynamic munitions classification surveys

NASA Astrophysics Data System (ADS)

Standard protocol for detection and classification of Unexploded Ordnance (UXO) comprises a two-step process that includes an initial digital geophysical mapping (DGM) survey to detect magnetic field anomalies followed by a cued survey at each anomaly location that enables classification of these anomalies. The initial DGM survey is typically performed using a low resolution single axis electromagnetic induction (EMI) sensor while the follow-up cued survey requires revisiting each anomaly location with a multi-axis high resolution EMI sensor. The DGM survey comprises data collection in tightly spaced transects over the entire survey area. Once data collection in this area is complete, a threshold analysis is applied to the resulting magnetic field anomaly map to identify anomalies corresponding to potential targets of interest (TOI). The cued sensor is deployed in static mode where this higher resolution sensor is placed over the location of each anomaly to record a number of soundings that may be stacked and averaged to produce low noise data. These data are of sufficient quality to subsequently classify the object as either TOI or clutter. While this approach has demonstrated success in producing effective classification of UXO, conducting successive surveys is time consuming. Additionally, the low resolution of the initial DGM survey often produces errors in the target picking process that results in poor placement of the cued sensor and often requires several revisits to the anomaly location to ensure adequate characterization of the target space. We present data and test results from an advanced multi-axis EMI sensor optimized to provide both detection and classification from a single survey. We demonstrate how the large volume of data from this sensor may be used to produce effective detection and classification decisions while only requiring one survey of the munitions response area.

Miller, Jonathan S.; Keranen, Joe; Schultz, Gregory

2014-06-01

461

In this work we explicitly provide the first ever optimal, with respect to the Zheng-Tse diversity multiplexing gain (D-MG) tradeoff, cooperative diversity schemes for wireless relay networks. The schemes are based on variants of perfect space-time codes and are optimal for any number of users and all statistically symmetric (and in some cases, asymmetric) fading distributions. We deduce that, with

Petros Elia; P. Vijay Kumar

2005-01-01

462

Simulating the Dynamics of Scale-Free Networks via Optimization

We deal here with the issue of complex network evolution. The analysis of topological evolution of complex networks plays a crucial role in predicting their future. While an impressive amount of work has been done on the issue, very little attention has been so far devoted to the investigation of how information theory quantifiers can be applied to characterize networks evolution. With the objective of dynamically capture the topological changes of a network's evolution, we propose a model able to quantify and reproduce several characteristics of a given network, by using the square root of the Jensen-Shannon divergence in combination with the mean degree and the clustering coefficient. To support our hypothesis, we test the model by copying the evolution of well-known models and real systems. The results show that the methodology was able to mimic the test-networks. By using this copycat model, the user is able to analyze the networks behavior over time, and also to conjecture about the main drivers of its evolution, also providing a framework to predict its evolution. PMID:24353752

Schieber, Tiago Alves; Ravetti, Martín Gómez

2013-01-01

463

Long term dynamics and optimal control of nano-satellite deorbit using a short electrodynamic tether

NASA Astrophysics Data System (ADS)

This paper studies the long term dynamics and optimal 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 optimal 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 optimal trajectory derived in the first phase by a finite receding horizon control method while considering a full dynamic model of electrodynamic tether system. Both optimal 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 optimal balance between the libration stability and a fast deorbit of satellite with minimum control efforts is achieved.

Zhong, R.; Zhu, Z. H.

2013-10-01

464

Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

NASA Technical Reports Server (NTRS)

A chance-constrained dynamic programming algorithm was developed that is capable of making optimal 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 dynamic programming (DP) provides a general framework for optimal 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 optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

Ono, Masahiro; Kuwata, Yoshiaki

2013-01-01

465

Optimal preventive maintenance of a nuclear plant subsystem using dynamic programming

Dynamic programming (DP) techniques are powerful tools for solving optimization problems involving nonlinear objective functions and/or constraints. Although DP algorithms have been utilized for determining optimal system maintenance policies, it is reported that DP may not be computationally feasible for systems with more than four structural units due to the large number of system states that need to be considered. This paper shows the way that a class of maintenance problems can be formulated to reduce the system state space. The approach is illustrated on a nuclear power plant subsystem consisting of six structural units.

Harunuzzaman, M.; Aldemir, T.

1988-01-01

466

Approximate dynamic programming for optimal stationary control with control-dependent noise.

This brief studies the stochastic optimal control problem via reinforcement learning and approximate/adaptive dynamic programming (ADP). A policy iteration algorithm is derived in the presence of both additive and multiplicative noise using Itô calculus. The expectation of the approximated cost matrix is guaranteed to converge to the solution of some algebraic Riccati equation that gives rise to the optimal cost value. Moreover, the covariance of the approximated cost matrix can be reduced by increasing the length of time interval between two consecutive iterations. Finally, a numerical example is given to illustrate the efficiency of the proposed ADP methodology. PMID:21954203

Jiang, Yu; Jiang, Zhong-Ping

2011-12-01

467

Reduced-Order Model for Dynamic Optimization of Pressure Swing Adsorption

The last few decades have seen a considerable increase in the applications of adsorptive gas separation technologies, such as pressure swing adsorption (PSA). From an economic and environmental point of view, hydrogen separation and carbon dioxide capture from flue gas streams are the most promising applications of PSA. With extensive industrial applications, there is a significant interest for an efficient modeling, simulation, and optimization strategy. However, the design and optimization of the PSA processes have largely remained an experimental effort because of the complex nature of the mathematical models describing practical PSA processes. 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 and high nonlinearities arising from non-isothermal effects. The computational effort required to solve such systems is usually quite expensive and prohibitively time consuming. Besides this, stringent product specifications, required by many industrial processes, often lead to convergence failures of the optimizers. The solution of this coupled stiff PDE system is governed by steep concentrations and temperature fronts moving with time. As a result, the optimization of such systems for either design or operation represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Sophisticated optimization strategies have been developed and applied to PSA systems with significant improvement in the performance of the process. However, most of these approaches have been quite time consuming. This gives a strong motivation to develop cost-efficient and robust optimization strategies for PSA processes. Moreover, in case of flowsheet optimization, if dynamic PSA models are incorporated with other steady state models in the flowsheet then it will require much faster approaches for integrated optimization.

Agarwal, Anshul (Carnegie Mellon Univ., Pittsburgh, PA); Biegler, L.T. (Carnegie Mellon Univ., Pittsburgh, PA); Zitney, S.E.

2007-11-01

468

Analysis and formulation of a class of complex dynamic optimization problems

NASA Astrophysics Data System (ADS)

The Direct Transcription approach, also known as the direct simultaneous approach, is a widely used solution strategy for the solution of dynamic optimization 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 dynamic optimization and optimal 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 optimal 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 optimization inside the framework of dynamic optimization. As an effort to extend the applicability of the direct simultaneous approach to a wider class of problems, a PDE-constrained optimal control problem, the spatial discretization of which results in a DAE-constrained problem with an arbitrarily high-index inequality constraint, is studied. Optimal control problems with high-index path constraints are very hard to solve, numerically. Contrary to the intuitive belief that the direct transcription approach would not work for the high-index optimal control problem, an analysis is performed to show that NLP-based methods have flexibility with respect to constraint qualifications, and this can be put to use in the context of high-index inequality path-constrained problems to obtain meaningful solutions. (Abstract shortened by UMI.)

Kameswaran, Shivakumar

469

An enhanced integrated aerodynamic load/dynamic optimization procedure for helicopter rotor blades

NASA Technical Reports Server (NTRS)

An enhanced integrated aerodynamic load/dynamic optimization procedure is developed to minimize vibratory root shears and moments. The optimization 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 optimization. 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 optimizer, which consists of the program CONMIN and an approximate analysis, to obtain optimum designs. The optimization 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 optimization.

Chattopadhyay, Aditi; Chiu, Y. Danny

1990-01-01

470

A dynamic combinatorial library of potential anion receptors was generated from a cyclic peptide disulfide dimer and a series of dithiol spacers. Exposing the library to KI or K2SO4 led to the amplification of two new neutral receptors that bind anions through hydrogen bonding with up to micromolar affinity in aqueous solution. Thermodynamic studies suggest that these second-generation receptors outclass the previously described first-generation receptor, largely as a result of a more favorable enthalpy of binding. These results demonstrate that dynamic combinatorial optimization of designed hosts can be a powerful strategy, bringing synthetic receptors that approach the efficiencies of proteins one step closer. PMID:12822990

Otto, Sijbren; Kubik, Stefan

2003-07-01

471

A dynamic optimization for operation of a compressed air energy storage system

A mathematical model is derived, simulating the dynamic behavior of a cavern-type (constant volume) compressed air energy storage system (CAES). With the aid of the model, optimal control of the system decision variables such as charging and discharging timing and duration and the fuel injection policy are determined by periodic dynamic programming method. The performance criterion is maximizing the net benefits over the operation cycle. An algorithm for numerical solution of the problem is presented and computational results for an example representing a real plant are given.

Weiner, D. (Israel Electric Corp. Ltd., Haifa (Israel). Research and Development Div.)

1989-03-01

472

An Approach for Dynamic Optimization of Prevention Program Implementation in Stochastic Environments

NASA Astrophysics Data System (ADS)

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 dynamic processes. Specifically, we propose Markov Decision Process (MDP) for modeling and dynamic optimization of such EBP implementations. We illustrate these concepts using simple numerical examples and discuss potential challenges in using such approaches in practice.

Kang, Yuncheol; Prabhu, Vittal

473

Human motion planning based on recursive dynamics and optimal control techniques

NASA Technical Reports Server (NTRS)

This paper presents an efficient optimal control and recursive dynamics-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 dynamics are derived using a matrix exponential formulation and Lie algebra. Cubic spline functions are used to make the search space for an optimal 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.

Lo, Janzen; Huang, Gang; Metaxas, Dimitris

2002-01-01

474

Optimal dynamic discrimination of similar quantum systems with time series data

NASA Astrophysics Data System (ADS)

Optimal dynamic discrimination (ODD) was proposed [Li et al., J. Phys. Chem. B 106, 8125 (2002)] as a paradigm for discriminating noninteracting similar quantum systems in a mixture. This paper extends the ODD concept to optimize a laser control pulse for guiding similar quantum systems such that each exhibits a distinct time series signal for maximum discrimination. The use of temporal data addresses various experimental difficulties, including noise in the laser pulse, signal detection errors, and finite time resolution in the signal. Simulations of ODD with time series data are presented to explore these effects. It is found that the use of an optimally chosen control pulse can significantly enhance the discrimination quality. The ODD technique is also adapted to the case where the sample contains an unknown background species.

Li, Baiqing; Rabitz, Herschel; Wolf, J. P.

2005-04-01

475

Optimal control study for the Space Station Solar Dynamic power module

NASA Technical Reports Server (NTRS)

The authors present the design of an optimal control system for the Space Station Freedom's Solar Dynamic 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 optimal 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 optimal 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.

Papadopoulos, P. M.; Laub, A. J.; Kenney, C. S.; Pandey, P.; Ianculescu, G.; Ly, J.

1991-01-01

476

NASA Astrophysics Data System (ADS)

Tensor network states (TNS) methods combined with the Monte Carlo (MC) technique have been proven a powerful algorithm for simulating quantum many-body systems. However, because the ground state energy is a highly non-linear function of the tensors, it is easy to get stuck in local minima when optimizing the TNS of the simulated physical systems. To overcome this difficulty, we introduce a replica-exchange molecular dynamics optimization algorithm to obtain the TNS ground state, based on the MC sampling technique, by mapping the energy function of the TNS to that of a classical mechanical system. The method is expected to effectively avoid local minima. We make benchmark tests on a 1D Hubbard model based on matrix product states (MPS) and a Heisenberg J1–J2 model on square lattice based on string bond states (SBS). The results show that the optimization method is robust and efficient compared to the existing results.

Liu, Wenyuan; Wang, Chao; Li, Yanbin; Lao, Yuyang; Han, Yongjian; Guo, Guang-Can; Zhao, Yong-Hua; He, Lixin

2015-03-01

477

Evolutionary genetic optimization of the injector beam dynamics for the ERL test facility at IHEP

The energy recovery linac test facility (ERL-TF), a compact ERL-FEL (free electron laser) two-purpose machine, was proposed at the Institute of High Energy Physics, Beijing. As one important component of the ERL-TF, the photo-injector started with a photocathode direct-current gun was designed and preliminarily optimized. In this paper an evolutionary genetic method, non-dominated sorting genetic algorithm II, is applied to optimize the injector beam dynamics, especially in the high-charge operation mode. Study shows that using an incident laser with rms transverse size of 1~1.2 mm, the normalized emittance of the electron beam can be kept below 1 mm.mrad at the end of the injector. This work, together with the previous optimization for the low-charge operation mode by using the iterative scan method, provides guidance and confidence for future constructing and commissioning of the ERL-TF injector.

Yi, Jiao

2013-01-01

478

Optimal dynamic pricing of water in the presence of waterlogging and spatial heterogeneity of land

NASA Astrophysics Data System (ADS)

Agricultural production is a major contributor to numerous environmental problems. Most of these problems have a dynamic aspect, and moreover, the magnitude of these environmental problems depends on the distribution of the characteristics of the land. Therefore policies designed to establish the social outcome need to be simultaneously targeted site specifically and time specifically. This paper integrates both aspects and presents a theoretical model that allows us to determine the socially optimal outcome over time and space. Moreover, the applicability of our approach, defined as optimal control in two stages, is demonstrated by reformulating the mathematical model such that it can be solved with standard mathematical software. For this purpose, we present an empirical study based on the cotton produced in the San Joaquin Valley in California and determine the socially optimal water price in the presence of waterlogging.

Xabadia, A.; Goetz, R.; Zilberman, D.

2004-07-01

479

Evolutionary genetic optimization of the injector beam dynamics for the ERL test facility at IHEP

NASA Astrophysics Data System (ADS)

The energy recovery linac test facility (ERL-TF), a compact ERL-FEL (free electron laser) two-purpose machine, has been proposed at the Institute of High Energy Physics, Beijing. As one important component of the ERL-TF, the photo-injector was designed and preliminarily optimized. In this paper an evolutionary genetic method, non-dominated sorting genetic algorithm II, is applied to optimize the injector beam dynamics, especially in the high-charge operation mode. Study shows that using an incident laser with rms transverse size of 1-1.2 mm, the normalized emittance of the electron beam can be kept below 1 mm·mrad at the end of the injector. This work, together with the previous optimization of the low-charge operation mode by using the iterative scan method, provides guidance and confidence for future construction and commissioning of the ERL-TF injector.

Jiao, Yi

2014-08-01

480

In this paper we present an algorithmic framework for solving a class of combinatorial optimization problems on graphs with bounded pathwidth. The problems are NP-hard in general, but solvable in linear time on this type of graphs. The problems are relevant for assessing network reliability and improving the network's performance and fault tolerance. The main technique considered in this paper is dynamic programming.

Andreica, Mugurel Ionut

2008-01-01

481

Optimal dynamical processes in tubular reactor with deactivation of multi-run moving catalyst

The dynamic unsteady-state reactor process in a cocurrent tubular reactor with single-run reagents (continuous phase) and with multi-run catalyst (dispersed phase) has been investigated. For the temperature-dependent catalyst deactivation the reactor process has been considered in which after optimal number B of catalyst residences in the reactor the whole amount of catalyst leaves the system; then the fresh catalyst is

Zbigniew Szwast; Stanislaw Sieniutycz

2004-01-01

482

In a processor having multiple clusters which operate in parallel, the number of clusters in use can be varied dynamically. At the start of each program phase, the configuration option for an interval is run to determine the optimal 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.

Balasubramonian, Rajeev (Sandy, UT); Dwarkadas, Sandhya (Rochester, NY); Albonesi, David (Ithaca, NY)

2012-01-24

483

Solving the blocking flow shop scheduling problem by a dynamic multi-swarm particle swarm optimizer

This paper presents a dynamic multi-swarm particle swarm optimizer (DMS-PSO) for solving the blocking flow shop scheduling\\u000a problem with the objective to minimize makespan. To maintain good global search ability, small swarms and a regrouping schedule\\u000a were used in the presented DMS-PSO. Each small swarm performed searching according to its own historical information, whereas\\u000a the regrouping schedule was employed to

J. J. Liang; Quan-Ke Pan; Chen Tiejun; Ling Wang

2011-01-01

484

A Dynamic Multi-swarm Particle Swarm Optimizer for blocking flow shop scheduling

This paper presents a Dynamic Multi-Swarm Particle Swarm