A nonlinear bi-level programming approach for product portfolio management.

PubMed

Ma, Shuang

2016-01-01

Product portfolio management (PPM) is a critical decision-making for companies across various industries in today's competitive environment. Traditional studies on PPM problem have been motivated toward engineering feasibilities and marketing which relatively pay less attention to other competitors' actions and the competitive relations, especially in mathematical optimization domain. The key challenge lies in that how to construct a mathematical optimization model to describe this Stackelberg game-based leader-follower PPM problem and the competitive relations between them. The primary work of this paper is the representation of a decision framework and the optimization model to leverage the PPM problem of leader and follower. A nonlinear, integer bi-level programming model is developed based on the decision framework. Furthermore, a bi-level nested genetic algorithm is put forward to solve this nonlinear bi-level programming model for leader-follower PPM problem. A case study of notebook computer product portfolio optimization is reported. Results and analyses reveal that the leader-follower bi-level optimization model is robust and can empower product portfolio optimization.

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

PubMed

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

2012-01-01

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

Optimal design and dispatch of a system of diesel generators, photovoltaics and batteries for remote locations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scioletti, Michael S.; Newman, Alexandra M.; Goodman, Johanna K.

Renewable energy technologies, specifically, solar photovoltaic cells, combined with battery storage and diesel generators, form a hybrid system capable of independently powering remote locations, i.e., those isolated from larger grids. If sized correctly, hybrid systems reduce fuel consumption compared to diesel generator-only alternatives. We present an optimization model for establishing a hybrid power design and dispatch strategy for remote locations, such as a military forward operating base, that models the acquisition of different power technologies as integer variables and their operation using nonlinear expressions. Our cost-minimizing, nonconvex, mixed-integer, nonlinear program contains a detailed battery model. Due to its complexities, wemore » present linearizations, which include exact and convex under-estimation techniques, and a heuristic, which determines an initial feasible solution to serve as a “warm start” for the solver. We determine, in a few hours at most, solutions within 5% of optimality for a candidate set of technologies; these solutions closely resemble those from the nonlinear model. Lastly, our instances contain real data spanning a yearly horizon at hour fidelity and demonstrate that a hybrid system could reduce fuel consumption by as much as 50% compared to a generator-only solution.« less

Optimal design and dispatch of a system of diesel generators, photovoltaics and batteries for remote locations

DOE PAGES

Scioletti, Michael S.; Newman, Alexandra M.; Goodman, Johanna K.; ...

2017-05-08

Renewable energy technologies, specifically, solar photovoltaic cells, combined with battery storage and diesel generators, form a hybrid system capable of independently powering remote locations, i.e., those isolated from larger grids. If sized correctly, hybrid systems reduce fuel consumption compared to diesel generator-only alternatives. We present an optimization model for establishing a hybrid power design and dispatch strategy for remote locations, such as a military forward operating base, that models the acquisition of different power technologies as integer variables and their operation using nonlinear expressions. Our cost-minimizing, nonconvex, mixed-integer, nonlinear program contains a detailed battery model. Due to its complexities, wemore » present linearizations, which include exact and convex under-estimation techniques, and a heuristic, which determines an initial feasible solution to serve as a “warm start” for the solver. We determine, in a few hours at most, solutions within 5% of optimality for a candidate set of technologies; these solutions closely resemble those from the nonlinear model. Lastly, our instances contain real data spanning a yearly horizon at hour fidelity and demonstrate that a hybrid system could reduce fuel consumption by as much as 50% compared to a generator-only solution.« less

Automatic computation of the travelling wave solutions to nonlinear PDEs

NASA Astrophysics Data System (ADS)

Liang, Songxin; Jeffrey, David J.

2008-05-01

Various extensions of the tanh-function method and their implementations for finding explicit travelling wave solutions to nonlinear partial differential equations (PDEs) have been reported in the literature. However, some solutions are often missed by these packages. In this paper, a new algorithm and its implementation called TWS for solving single nonlinear PDEs are presented. TWS is implemented in MAPLE 10. It turns out that, for PDEs whose balancing numbers are not positive integers, TWS works much better than existing packages. Furthermore, TWS obtains more solutions than existing packages for most cases. Program summaryProgram title:TWS Catalogue identifier:AEAM_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAM_v1_0.html Program obtainable from:CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions:Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.:1250 No. of bytes in distributed program, including test data, etc.:78 101 Distribution format:tar.gz Programming language:Maple 10 Computer:A laptop with 1.6 GHz Pentium CPU Operating system:Windows XP Professional RAM:760 Mbytes Classification:5 Nature of problem:Finding the travelling wave solutions to single nonlinear PDEs. Solution method:Based on tanh-function method. Restrictions:The current version of this package can only deal with single autonomous PDEs or ODEs, not systems of PDEs or ODEs. However, the PDEs can have any finite number of independent space variables in addition to time t. Unusual features:For PDEs whose balancing numbers are not positive integers, TWS works much better than existing packages. Furthermore, TWS obtains more solutions than existing packages for most cases. Additional comments:It is easy to use. Running time:Less than 20 seconds for most cases, between 20 to 100 seconds for some cases, over 100 seconds for few cases. References: [1] E.S. Cheb-Terrab, K. von Bulow, Comput. Phys. Comm. 90 (1995) 102. [2] S.A. Elwakil, S.K. El-Labany, M.A. Zahran, R. Sabry, Phys. Lett. A 299 (2002) 179. [3] E. Fan, Phys. Lett. 277 (2000) 212. [4] W. Malfliet, Amer. J. Phys. 60 (1992) 650. [5] W. Malfliet, W. Hereman, Phys. Scripta 54 (1996) 563. [6] E.J. Parkes, B.R. Duffy, Comput. Phys. Comm. 98 (1996) 288.

Solution of the Generalized Noah's Ark Problem.

PubMed

Billionnet, Alain

2013-01-01

The phylogenetic diversity (PD) of a set of species is a measure of the evolutionary distance among the species in the collection, based on a phylogenetic tree. Such a tree is composed of a root, internal nodes, and leaves that correspond to the set of taxa under study. With each edge of the tree is associated a non-negative branch length (evolutionary distance). If a particular survival probability is associated with each taxon, the PD measure becomes the expected PD measure. In the Noah's Ark Problem (NAP) introduced by Weitzman (1998), these survival probabilities can be increased at some cost. The problem is to determine how best to allocate a limited amount of resources to maximize the expected PD of the considered species. It is easy to formulate the NAP as a (difficult) nonlinear 0-1 programming problem. The aim of this article is to show that a general version of the NAP (GNAP) can be solved simply and efficiently with any set of edge weights and any set of survival probabilities by using standard mixed-integer linear programming software. The crucial point to move from a nonlinear program in binary variables to a mixed-integer linear program, is to approximate the logarithmic function by the lower envelope of a set of tangents to the curve. Solving the obtained mixed-integer linear program provides not only a near-optimal solution but also an upper bound on the value of the optimal solution. We also applied this approach to a generalization of the nature reserve problem (GNRP) that consists of selecting a set of regions to be conserved so that the expected PD of the set of species present in these regions is maximized. In this case, the survival probabilities of different taxa are not independent of each other. Computational results are presented to illustrate potentialities of the approach. Near-optimal solutions with hypothetical phylogenetic trees comprising about 4000 taxa are obtained in a few seconds or minutes of computing time for the GNAP, and in about 30 min for the GNRP. In all the cases the average guarantee varies from 0% to 1.20%.

Solving Integer Programs from Dependence and Synchronization Problems

DTIC Science & Technology

1993-03-01

DEFF.NSNE Solving Integer Programs from Dependence and Synchronization Problems Jaspal Subhlok March 1993 CMU-CS-93-130 School of Computer ScienceT IC...method Is an exact and efficient way of solving integer programming problems arising in dependence and synchronization analysis of parallel programs...7/;- p Keywords: Exact dependence tesing, integer programming. parallelilzng compilers, parallel program analysis, synchronization analysis Solving

Extension of the firefly algorithm and preference rules for solving MINLP problems

NASA Astrophysics Data System (ADS)

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

2017-07-01

An extension of the firefly algorithm (FA) for solving mixed-integer nonlinear programming (MINLP) problems is presented. Although penalty functions are nowadays frequently used to handle integrality conditions and inequality and equality constraints, this paper proposes the implementation within the FA of a simple rounded-based heuristic and four preference rules to find and converge to MINLP feasible solutions. Preliminary numerical experiments are carried out to validate the proposed methodology.

Asymptotic stability of a nonlinear Korteweg-de Vries equation with critical lengths

NASA Astrophysics Data System (ADS)

Chu, Jixun; Coron, Jean-Michel; Shang, Peipei

2015-10-01

We study an initial-boundary-value problem of a nonlinear Korteweg-de Vries equation posed on the finite interval (0, 2 kπ) where k is a positive integer. The whole system has Dirichlet boundary condition at the left end-point, and both of Dirichlet and Neumann homogeneous boundary conditions at the right end-point. It is known that the origin is not asymptotically stable for the linearized system around the origin. We prove that the origin is (locally) asymptotically stable for the nonlinear system if the integer k is such that the kernel of the linear Korteweg-de Vries stationary equation is of dimension 1. This is for example the case if k = 1.

Fish Processed Production Planning Using Integer Stochastic Programming Model

NASA Astrophysics Data System (ADS)

Firmansyah, Mawengkang, Herman

2011-06-01

Fish and its processed products are the most affordable source of animal protein in the diet of most people in Indonesia. The goal in production planning is to meet customer demand over a fixed time horizon divided into planning periods by optimizing the trade-off between economic objectives such as production cost and customer satisfaction level. The major decisions are production and inventory levels for each product and the number of workforce in each planning period. In this paper we consider the management of small scale traditional business at North Sumatera Province which performs processing fish into several local seafood products. The inherent uncertainty of data (e.g. demand, fish availability), together with the sequential evolution of data over time leads the production planning problem to a nonlinear mixed-integer stochastic programming model. We use scenario generation based approach and feasible neighborhood search for solving the model. The results which show the amount of each fish processed product and the number of workforce needed in each horizon planning are presented.

Software For Integer Programming

NASA Technical Reports Server (NTRS)

Fogle, F. R.

1992-01-01

Improved Exploratory Search Technique for Pure Integer Linear Programming Problems (IESIP) program optimizes objective function of variables subject to confining functions or constraints, using discrete optimization or integer programming. Enables rapid solution of problems up to 10 variables in size. Integer programming required for accuracy in modeling systems containing small number of components, distribution of goods, scheduling operations on machine tools, and scheduling production in general. Written in Borland's TURBO Pascal.

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

PubMed Central

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

2012-01-01

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

Ground-state energies of the nonlinear sigma model and the Heisenberg spin chains

NASA Technical Reports Server (NTRS)

Zhang, Shoucheng; Schulz, H. J.; Ziman, Timothy

1989-01-01

A theorem on the O(3) nonlinear sigma model with the topological theta term is proved, which states that the ground-state energy at theta = pi is always higher than the ground-state energy at theta = 0, for the same value of the coupling constant g. Provided that the nonlinear sigma model gives the correct description for the Heisenberg spin chains in the large-s limit, this theorem makes a definite prediction relating the ground-state energies of the half-integer and the integer spin chains. The ground-state energies obtained from the exact Bethe ansatz solution for the spin-1/2 chain and the numerical diagonalization on the spin-1, spin-3/2, and spin-2 chains support this prediction.

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

NASA Astrophysics Data System (ADS)

Gao, David Yang

2016-10-01

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

IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS

NASA Technical Reports Server (NTRS)

Fogle, F. R.

1994-01-01

IESIP, an Improved Exploratory Search Technique for Pure Integer Linear Programming Problems, addresses the problem of optimizing an objective function of one or more variables subject to a set of confining functions or constraints by a method called discrete optimization or integer programming. Integer programming is based on a specific form of the general linear programming problem in which all variables in the objective function and all variables in the constraints are integers. While more difficult, integer programming is required for accuracy when modeling systems with small numbers of components such as the distribution of goods, machine scheduling, and production scheduling. IESIP establishes a new methodology for solving pure integer programming problems by utilizing a modified version of the univariate exploratory move developed by Robert Hooke and T.A. Jeeves. IESIP also takes some of its technique from the greedy procedure and the idea of unit neighborhoods. A rounding scheme uses the continuous solution found by traditional methods (simplex or other suitable technique) and creates a feasible integer starting point. The Hook and Jeeves exploratory search is modified to accommodate integers and constraints and is then employed to determine an optimal integer solution from the feasible starting solution. The user-friendly IESIP allows for rapid solution of problems up to 10 variables in size (limited by DOS allocation). Sample problems compare IESIP solutions with the traditional branch-and-bound approach. IESIP is written in Borland's TURBO Pascal for IBM PC series computers and compatibles running DOS. Source code and an executable are provided. The main memory requirement for execution is 25K. This program is available on a 5.25 inch 360K MS DOS format diskette. IESIP was developed in 1990. IBM is a trademark of International Business Machines. TURBO Pascal is registered by Borland International.

Optimization methods for decision making in disease prevention and epidemic control.

PubMed

Deng, Yan; Shen, Siqian; Vorobeychik, Yevgeniy

2013-11-01

This paper investigates problems of disease prevention and epidemic control (DPEC), in which we optimize two sets of decisions: (i) vaccinating individuals and (ii) closing locations, given respective budgets with the goal of minimizing the expected number of infected individuals after intervention. The spread of diseases is inherently stochastic due to the uncertainty about disease transmission and human interaction. We use a bipartite graph to represent individuals' propensities of visiting a set of location, and formulate two integer nonlinear programming models to optimize choices of individuals to vaccinate and locations to close. Our first model assumes that if a location is closed, its visitors stay in a safe location and will not visit other locations. Our second model incorporates compensatory behavior by assuming multiple behavioral groups, always visiting the most preferred locations that remain open. The paper develops algorithms based on a greedy strategy, dynamic programming, and integer programming, and compares the computational efficacy and solution quality. We test problem instances derived from daily behavior patterns of 100 randomly chosen individuals (corresponding to 195 locations) in Portland, Oregon, and provide policy insights regarding the use of the two DPEC models. Copyright © 2013 Elsevier Inc. All rights reserved.

Finite-time stabilisation of a class of switched nonlinear systems with state constraints

NASA Astrophysics Data System (ADS)

Huang, Shipei; Xiang, Zhengrong

2018-06-01

This paper investigates the finite-time stabilisation for a class of switched nonlinear systems with state constraints. Some power orders of the system are allowed to be ratios of positive even integers over odd integers. A Barrier Lyapunov function is introduced to guarantee that the state constraint is not violated at any time. Using the convex combination method and a recursive design approach, a state-dependent switching law and state feedback controllers of individual subsystems are constructed such that the closed-loop system is finite-time stable without violation of the state constraint. Two examples are provided to show the effectiveness of the proposed method.

Optimization techniques applied to spectrum management for communications satellites

NASA Astrophysics Data System (ADS)

Ottey, H. R.; Sullivan, T. M.; Zusman, F. S.

This paper describes user requirements, algorithms and software design features for the application of optimization techniques to the management of the geostationary orbit/spectrum resource. Relevant problems include parameter sensitivity analyses, frequency and orbit position assignment coordination, and orbit position allotment planning. It is shown how integer and nonlinear programming as well as heuristic search techniques can be used to solve these problems. Formalized mathematical objective functions that define the problems are presented. Constraint functions that impart the necessary solution bounds are described. A versatile program structure is outlined, which would allow problems to be solved in stages while varying the problem space, solution resolution, objective function and constraints.

Nonlinear oscillator with power-form elastic-term: Fourier series expansion of the exact solution

NASA Astrophysics Data System (ADS)

Beléndez, Augusto; Francés, Jorge; Beléndez, Tarsicio; Bleda, Sergio; Pascual, Carolina; Arribas, Enrique

2015-05-01

A family of conservative, truly nonlinear, oscillators with integer or non-integer order nonlinearity is considered. These oscillators have only one odd power-form elastic-term and exact expressions for their period and solution were found in terms of Gamma functions and a cosine-Ateb function, respectively. Only for a few values of the order of nonlinearity, is it possible to obtain the periodic solution in terms of more common functions. However, for this family of conservative truly nonlinear oscillators we show in this paper that it is possible to obtain the Fourier series expansion of the exact solution, even though this exact solution is unknown. The coefficients of the Fourier series expansion of the exact solution are obtained as an integral expression in which a regularized incomplete Beta function appears. These coefficients are a function of the order of nonlinearity only and are computed numerically. One application of this technique is to compare the amplitudes for the different harmonics of the solution obtained using approximate methods with the exact ones computed numerically as shown in this paper. As an example, the approximate amplitudes obtained via a modified Ritz method are compared with the exact ones computed numerically.

Optimal reconfiguration strategy for a degradable multimodule computing system

NASA Technical Reports Server (NTRS)

Lee, Yann-Hang; Shin, Kang G.

1987-01-01

The present quantitative approach to the problem of reconfiguring a degradable multimode system assigns some modules to computation and arranges others for reliability. By using expected total reward as the optimal criterion, there emerges an active reconfiguration strategy based not only on the occurrence of failure but the progression of the given mission. This reconfiguration strategy requires specification of the times at which the system should undergo reconfiguration, and the configurations to which the system should change. The optimal reconfiguration problem is converted to integer nonlinear knapsack and fractional programming problems.

A Composite Algorithm for Mixed Integer Constrained Nonlinear Optimization.

DTIC Science & Technology

1980-01-01

de Silva [141, and Weisman and Wood [76). A particular direct search algorithm, the simplex method, has been cited for having the potential for...spaced discrete points on a line which makes the direction suitable for an efficient integer search technique based on Fibonacci numbers. Two...defined by a subset of variables. The complex algorithm is particularly well suited for this subspace search for two reasons. First, the complex method

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

ERIC Educational Resources Information Center

Han, Kyung T.; Rudner, Lawrence M.

2014-01-01

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

Model for the design of distributed data bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ram, S.

This research focuses on developing a model to solve the File Allocation Problem (FAP). The model integrates two major design issues, namely Concurrently Control and Data Distribution. The central node locking mechanism is incorporated in developing a nonlinear integer programming model. Two solution algorithms are proposed, one of which was implemented in FORTRAN.V. The allocation of data bases and programs are examined using this heuristic. Several decision rules were also formulated based on the results of the heuristic. A second more comprehensive heuristic was proposed, based on the knapsack problem. The development and implementation of this algorithm has been leftmore » as a topic for future research.« less

Nonlinear Mixing of Optical Vortices with Fractional Topological Charges in Raman Sideband Generation.

NASA Astrophysics Data System (ADS)

Strohaber, James; Boran, Yakup; Sayrac, Muhammed; Johnson, Lewis; Zhu, Feng; Kolomenskii, Alexandre; Schuessler, Hans

We studied the nonlinear parametric interaction of femtosecond fractionally-charged optical vortices in a Raman-active medium. Propagation of such beams is described using the Kirchhoff-Fresnel integrals by embedding a non-integer 2pi phase step in a Gaussian beam profile. When using fractionally-charged pump or Stokes beams, we observed the production of new topological charge and phase discontinuities in the Raman field. These newly generated fractionally-charged Raman vortex beams were found to follow the same orbital angular momentum algebra derived by for integer vortex beams. This work was funded by the Robert A. Welch Foundation, Grant No. A1546 and the Qatar Foundation under Grants No. NPRP 6-465-1-091.

Optimizing Multi-Product Multi-Constraint Inventory Control Systems with Stochastic Replenishments

NASA Astrophysics Data System (ADS)

Allah Taleizadeh, Ata; Aryanezhad, Mir-Bahador; Niaki, Seyed Taghi Akhavan

Multi-periodic inventory control problems are mainly studied employing two assumptions. The first is the continuous review, where depending on the inventory level orders can happen at any time and the other is the periodic review, where orders can only happen at the beginning of each period. In this study, we relax these assumptions and assume that the periodic replenishments are stochastic in nature. Furthermore, we assume that the periods between two replenishments are independent and identically random variables. For the problem at hand, the decision variables are of integer-type and there are two kinds of space and service level constraints for each product. We develop a model of the problem in which a combination of back-order and lost-sales are considered for the shortages. Then, we show that the model is of an integer-nonlinear-programming type and in order to solve it, a search algorithm can be utilized. We employ a simulated annealing approach and provide a numerical example to demonstrate the applicability of the proposed methodology.

Analysis of the single-vehicle cyclic inventory routing problem

NASA Astrophysics Data System (ADS)

Aghezzaf, El-Houssaine; Zhong, Yiqing; Raa, Birger; Mateo, Manel

2012-11-01

The single-vehicle cyclic inventory routing problem (SV-CIRP) consists of a repetitive distribution of a product from a single depot to a selected subset of customers. For each customer, selected for replenishments, the supplier collects a corresponding fixed reward. The objective is to determine the subset of customers to replenish, the quantity of the product to be delivered to each and to design the vehicle route so that the resulting profit (difference between the total reward and the total logistical cost) is maximised while preventing stockouts at each of the selected customers. This problem appears often as a sub-problem in many logistical problems. In this article, the SV-CIRP is formulated as a mixed-integer program with a nonlinear objective function. After a thorough analysis of the structure of the problem and its features, an exact algorithm for its solution is proposed. This exact algorithm requires only solutions of linear mixed-integer programs. Values of a savings-based heuristic for this problem are compared to the optimal values obtained for a set of some test problems. In general, the gap may get as large as 25%, which justifies the effort to continue exploring and developing exact and approximation algorithms for the SV-CIRP.

Resource allocation in shared spectrum access communications for operators with diverse service requirements

NASA Astrophysics Data System (ADS)

Kibria, Mirza Golam; Villardi, Gabriel Porto; Ishizu, Kentaro; Kojima, Fumihide; Yano, Hiroyuki

2016-12-01

In this paper, we study inter-operator spectrum sharing and intra-operator resource allocation in shared spectrum access communication systems and propose efficient dynamic solutions to address both inter-operator and intra-operator resource allocation optimization problems. For inter-operator spectrum sharing, we present two competent approaches, namely the subcarrier gain-based sharing and fragmentation-based sharing, which carry out fair and flexible allocation of the available shareable spectrum among the operators subject to certain well-defined sharing rules, traffic demands, and channel propagation characteristics. The subcarrier gain-based spectrum sharing scheme has been found to be more efficient in terms of achieved throughput. However, the fragmentation-based sharing is more attractive in terms of computational complexity. For intra-operator resource allocation, we consider resource allocation problem with users' dissimilar service requirements, where the operator supports users with delay constraint and non-delay constraint service requirements, simultaneously. This optimization problem is a mixed-integer non-linear programming problem and non-convex, which is computationally very expensive, and the complexity grows exponentially with the number of integer variables. We propose less-complex and efficient suboptimal solution based on formulating exact linearization, linear approximation, and convexification techniques for the non-linear and/or non-convex objective functions and constraints. Extensive simulation performance analysis has been carried out that validates the efficiency of the proposed solution.

Reduced-Size Integer Linear Programming Models for String Selection Problems: Application to the Farthest String Problem.

PubMed

Zörnig, Peter

2015-08-01

We present integer programming models for some variants of the farthest string problem. The number of variables and constraints is substantially less than that of the integer linear programming models known in the literature. Moreover, the solution of the linear programming-relaxation contains only a small proportion of noninteger values, which considerably simplifies the rounding process. Numerical tests have shown excellent results, especially when a small set of long sequences is given.

Optimal Diet Planning for Eczema Patient Using Integer Programming

NASA Astrophysics Data System (ADS)

Zhen Sheng, Low; Sufahani, Suliadi

2018-04-01

Human diet planning is conducted by choosing appropriate food items that fulfill the nutritional requirements into the diet formulation. This paper discusses the application of integer programming to build the mathematical model of diet planning for eczema patients. The model developed is used to solve the diet problem of eczema patients from young age group. The integer programming is a scientific approach to select suitable food items, which seeks to minimize the costs, under conditions of meeting desired nutrient quantities, avoiding food allergens and getting certain foods into the diet that brings relief to the eczema conditions. This paper illustrates that the integer programming approach able to produce the optimal and feasible solution to deal with the diet problem of eczema patient.

The fate of a gray soliton in a quenched Bose-Einstein condensate

NASA Astrophysics Data System (ADS)

Gamayun, Oleksandr; Bezvershenko, Yulia; Cheianov, Vadim

2015-03-01

We investigate the destiny of a gray soliton in a repulsive one-dimensional Bose-Einstein condensate undergoing a sudden quench of the non-linearity parameter. The outcome of the quench is found to depend dramatically on the ratio η of the final and initial values of the speed of sound. For integer η the soliton splits into exactly 2 η - 1 solitons. For non-integer η the soliton decays into multiple solitons and Bogoliubov modes. The case of integer η is analyzed in detail. The parameters of solitons in the out-state are found explicitly. Our approach exploits the inverse scattering method and can be easily used for the similar quenches in any classical integrable system.

Lossless crossing of a resonance stopband during tune modulation by synchrotron oscillations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, G. M.; Shaftan, T.; Smaluk, V.

Modern high performance circular accelerators require sophisticated corrections of nonlinear lattices. The beam betatron tune footprint may cross many resonances, reducing dynamic aperture and causing particle loss. But, if particles cross a resonance reasonably fast, the beam deterioration may be minimized. This paper describes the experiments with the beam passing through a half-integer resonance stopband via tune modulation by exciting synchrotron oscillations. This is the first time that beam dynamics have been kept under precise control while the beam crosses a half-integer resonance. These results convincingly demonstrate that particles can cross the half-integer resonance without being lost if the passagemore » is reasonably fast and the resonance stopband is sufficiently narrow.« less

Lossless crossing of a resonance stopband during tune modulation by synchrotron oscillations

DOE PAGES

Wang, G. M.; Shaftan, T.; Smaluk, V.; ...

2017-09-14

Modern high performance circular accelerators require sophisticated corrections of nonlinear lattices. The beam betatron tune footprint may cross many resonances, reducing dynamic aperture and causing particle loss. But, if particles cross a resonance reasonably fast, the beam deterioration may be minimized. This paper describes the experiments with the beam passing through a half-integer resonance stopband via tune modulation by exciting synchrotron oscillations. This is the first time that beam dynamics have been kept under precise control while the beam crosses a half-integer resonance. These results convincingly demonstrate that particles can cross the half-integer resonance without being lost if the passagemore » is reasonably fast and the resonance stopband is sufficiently narrow.« less

Hybrid Optimization Parallel Search PACKage

DOE Office of Scientific and Technical Information (OSTI.GOV)

2009-11-10

HOPSPACK is open source software for solving optimization problems without derivatives. Application problems may have a fully nonlinear objective function, bound constraints, and linear and nonlinear constraints. Problem variables may be continuous, integer-valued, or a mixture of both. The software provides a framework that supports any derivative-free type of solver algorithm. Through the framework, solvers request parallel function evaluation, which may use MPI (multiple machines) or multithreading (multiple processors/cores on one machine). The framework provides a Cache and Pending Cache of saved evaluations that reduces execution time and facilitates restarts. Solvers can dynamically create other algorithms to solve subproblems, amore » useful technique for handling multiple start points and integer-valued variables. HOPSPACK ships with the Generating Set Search (GSS) algorithm, developed at Sandia as part of the APPSPACK open source software project.« less

Integrated model for pricing, delivery time setting, and scheduling in make-to-order environments

NASA Astrophysics Data System (ADS)

Garmdare, Hamid Sattari; Lotfi, M. M.; Honarvar, Mahboobeh

2018-03-01

Usually, in make-to-order environments which work only in response to the customer's orders, manufacturers for maximizing the profits should offer the best price and delivery time for an order considering the existing capacity and the customer's sensitivity to both the factors. In this paper, an integrated approach for pricing, delivery time setting and scheduling of new arrival orders are proposed based on the existing capacity and accepted orders in system. In the problem, the acquired market demands dependent on the price and delivery time of both the manufacturer and its competitors. A mixed-integer non-linear programming model is presented for the problem. After converting to a pure non-linear model, it is validated through a case study. The efficiency of proposed model is confirmed by comparing it to both the literature and the current practice. Finally, sensitivity analysis for the key parameters is carried out.

Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

NASA Astrophysics Data System (ADS)

Chen, Wei

2015-07-01

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

Mixed Integer Programming and Heuristic Scheduling for Space Communication

NASA Technical Reports Server (NTRS)

Lee, Charles H.; Cheung, Kar-Ming

2013-01-01

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

Superstructure-based Design and Optimization of Batch Biodiesel Production Using Heterogeneous Catalysts

NASA Astrophysics Data System (ADS)

Nuh, M. Z.; Nasir, N. F.

2017-08-01

Biodiesel as a fuel comprised of mono alkyl esters of long chain fatty acids derived from renewable lipid feedstock, such as vegetable oil and animal fat. Biodiesel production is complex process which need systematic design and optimization. However, no case study using the process system engineering (PSE) elements which are superstructure optimization of batch process, it involves complex problems and uses mixed-integer nonlinear programming (MINLP). The PSE offers a solution to complex engineering system by enabling the use of viable tools and techniques to better manage and comprehend the complexity of the system. This study is aimed to apply the PSE tools for the simulation of biodiesel process and optimization and to develop mathematical models for component of the plant for case A, B, C by using published kinetic data. Secondly, to determine economic analysis for biodiesel production, focusing on heterogeneous catalyst. Finally, the objective of this study is to develop the superstructure for biodiesel production by using heterogeneous catalyst. The mathematical models are developed by the superstructure and solving the resulting mixed integer non-linear model and estimation economic analysis by using MATLAB software. The results of the optimization process with the objective function of minimizing the annual production cost by batch process from case C is 23.2587 million USD. Overall, the implementation a study of process system engineering (PSE) has optimized the process of modelling, design and cost estimation. By optimizing the process, it results in solving the complex production and processing of biodiesel by batch.

A new fractional nonlocal model and its application in free vibration of Timoshenko and Euler-Bernoulli beams

NASA Astrophysics Data System (ADS)

Rahimi, Zaher; Sumelka, Wojciech; Yang, Xiao-Jun

2017-11-01

The application of fractional calculus in fractional models (FMs) makes them more flexible than integer models inasmuch they can conclude all of integer and non-integer operators. In other words FMs let us use more potential of mathematics to modeling physical phenomena due to the use of both integer and fractional operators to present a better modeling of problems, which makes them more flexible and powerful. In the present work, a new fractional nonlocal model has been proposed, which has a simple form and can be used in different problems due to the simple form of numerical solutions. Then the model has been used to govern equations of the motion of the Timoshenko beam theory (TBT) and Euler-Bernoulli beam theory (EBT). Next, free vibration of the Timoshenko and Euler-Bernoulli simply-supported (S-S) beam has been investigated. The Galerkin weighted residual method has been used to solve the non-linear governing equations.

Pole-zero form fractional model identification in frequency domain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mansouri, R.; Djamah, T.; Djennoune, S.

2009-03-05

This paper deals with system identification in the frequency domain using non integer order models given in the pole-zero form. The usual identification techniques cannot be used in this case because of the non integer orders of differentiation which makes the problem strongly nonlinear. A general identification method based on Levenberg-Marquardt algorithm is developed and allows to estimate the (2n+2m+1) parameters of the model. Its application to identify the ''skin effect'' of a squirrel cage induction machine modeling is then presented.

A Bell-Curved Based Algorithm for Mixed Continuous and Discrete Structural Optimization

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.; Weber, Michael; Sobieszczanski-Sobieski, Jaroslaw

2001-01-01

An evolutionary based strategy utilizing two normal distributions to generate children is developed to solve mixed integer nonlinear programming problems. This Bell-Curve Based (BCB) evolutionary algorithm is similar in spirit to (mu + mu) evolutionary strategies and evolutionary programs but with fewer parameters to adjust and no mechanism for self adaptation. First, a new version of BCB to solve purely discrete optimization problems is described and its performance tested against a tabu search code for an actuator placement problem. Next, the performance of a combined version of discrete and continuous BCB is tested on 2-dimensional shape problems and on a minimum weight hub design problem. In the latter case the discrete portion is the choice of the underlying beam shape (I, triangular, circular, rectangular, or U).

Menu-Driven Solver Of Linear-Programming Problems

NASA Technical Reports Server (NTRS)

Viterna, L. A.; Ferencz, D.

1992-01-01

Program assists inexperienced user in formulating linear-programming problems. A Linear Program Solver (ALPS) computer program is full-featured LP analysis program. Solves plain linear-programming problems as well as more-complicated mixed-integer and pure-integer programs. Also contains efficient technique for solution of purely binary linear-programming problems. Written entirely in IBM's APL2/PC software, Version 1.01. Packed program contains licensed material, property of IBM (copyright 1988, all rights reserved).

The use of integer programming to select bulls across breeding companies with volume price discounts.

PubMed

McConnel, M B; Galligan, D T

2004-10-01

Optimization programs are currently used to aid in the selection of bulls to be used in herd breeding programs. While these programs offer a systematic approach to the problem of semen selection, they ignore the impact of volume discounts. Volume discounts are discounts that vary depending on the number of straws purchased. The dynamic nature of volume discounts means that, in order to be adequately accounted for, they must be considered in the optimization routine. Failing to do this creates a missed economic opportunity because the potential benefits of optimally selecting and combining breeding company discount opportunities are not captured. To address these issues, an integer program was created which used binary decision variables to incorporate the effects of quantity discounts into the optimization program. A consistent set of trait criteria was used to select a group of bulls from 3 sample breeding companies. Three different selection programs were used to select the bulls, 2 traditional methods and the integer method. After the discounts were applied using each method, the integer program resulted in the lowest cost portfolio of bulls. A sensitivity analysis showed that the integer program also resulted in a low cost portfolio when the genetic trait goals were changed to be more or less stringent. In the sample application, a net benefit of the new approach over the traditional approaches was a 12.3 to 20.0% savings in semen cost.

A hybrid Jaya algorithm for reliability-redundancy allocation problems

NASA Astrophysics Data System (ADS)

Ghavidel, Sahand; Azizivahed, Ali; Li, Li

2018-04-01

This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching-learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability-redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series-parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30-100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.

ALPS: A Linear Program Solver

NASA Technical Reports Server (NTRS)

Ferencz, Donald C.; Viterna, Larry A.

1991-01-01

ALPS is a computer program which can be used to solve general linear program (optimization) problems. ALPS was designed for those who have minimal linear programming (LP) knowledge and features a menu-driven scheme to guide the user through the process of creating and solving LP formulations. Once created, the problems can be edited and stored in standard DOS ASCII files to provide portability to various word processors or even other linear programming packages. Unlike many math-oriented LP solvers, ALPS contains an LP parser that reads through the LP formulation and reports several types of errors to the user. ALPS provides a large amount of solution data which is often useful in problem solving. In addition to pure linear programs, ALPS can solve for integer, mixed integer, and binary type problems. Pure linear programs are solved with the revised simplex method. Integer or mixed integer programs are solved initially with the revised simplex, and the completed using the branch-and-bound technique. Binary programs are solved with the method of implicit enumeration. This manual describes how to use ALPS to create, edit, and solve linear programming problems. Instructions for installing ALPS on a PC compatible computer are included in the appendices along with a general introduction to linear programming. A programmers guide is also included for assistance in modifying and maintaining the program.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graf, Peter; Dykes, Katherine; Scott, George

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

A mixed integer program to model spatial wildfire behavior and suppression placement decisions

Treesearch

Erin J. Belval; Yu Wei; Michael Bevers

2015-01-01

Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...

An Integer Programming Model for Multi-Echelon Supply Chain Decision Problem Considering Inventories

NASA Astrophysics Data System (ADS)

Harahap, Amin; Mawengkang, Herman; Siswadi; Effendi, Syahril

2018-01-01

In this paper we address a problem that is of significance to the industry, namely the optimal decision of a multi-echelon supply chain and the associated inventory systems. By using the guaranteed service approach to model the multi-echelon inventory system, we develop a mixed integer; programming model to simultaneously optimize the transportation, inventory and network structure of a multi-echelon supply chain. To solve the model we develop a direct search approach using a strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points.

A Structural Weight Estimation Program (SWEEP) for Aircraft. Volume 11 - Flexible Airloads Stand-Alone Program

DTIC Science & Technology

1974-06-01

stiffness, lb-in. I Integer used to designate wing strip number 2 I Airplanw pitching moment of inertia, slug ft 2 I Airplane yawing moment of inertia...slug ft J Integer used to designated wing-loading distribution, i.e., J-l, loading due to angle of attack J=2> loading due to flap deflection J-3...moment at intersection of load reference line and body interface station (for vertical tail), in.-lb Integer used to designate type of wing airload

Seismic Retrofit for Electric Power Systems

DOE PAGES

Romero, Natalia; Nozick, Linda K.; Dobson, Ian; ...

2015-05-01

Our paper develops a two-stage stochastic program and solution procedure to optimize the selection of seismic retrofit strategies to increase the resilience of electric power systems against earthquake hazards. The model explicitly considers the range of earthquake events that are possible and, for each, an approximation of the distribution of damage experienced. Furthermore, this is important because electric power systems are spatially distributed and so their performance is driven by the distribution of component damage. We also test this solution procedure against the nonlinear integer solver in LINGO 13 and apply the formulation and solution strategy to the Eastern Interconnection,more » where seismic hazard stems from the New Madrid seismic zone.« less

Mathematical programming formulations for satellite synthesis

NASA Technical Reports Server (NTRS)

Bhasin, Puneet; Reilly, Charles H.

1987-01-01

The problem of satellite synthesis can be described as optimally allotting locations and sometimes frequencies and polarizations, to communication satellites so that interference from unwanted satellite signals does not exceed a specified threshold. In this report, mathematical programming models and optimization methods are used to solve satellite synthesis problems. A nonlinear programming formulation which is solved using Zoutendijk's method and a gradient search method is described. Nine mixed integer programming models are considered. Results of computer runs with these nine models and five geographically compatible scenarios are presented and evaluated. A heuristic solution procedure is also used to solve two of the models studied. Heuristic solutions to three large synthesis problems are presented. The results of our analysis show that the heuristic performs very well, both in terms of solution quality and solution time, on the two models to which it was applied. It is concluded that the heuristic procedure is the best of the methods considered for solving satellite synthesis problems.

Forced convective heat transfer in boundary layer flow of Sisko fluid over a nonlinear stretching sheet.

PubMed

Munir, Asif; Shahzad, Azeem; Khan, Masood

2014-01-01

The major focus of this article is to analyze the forced convective heat transfer in a steady boundary layer flow of Sisko fluid over a nonlinear stretching sheet. Two cases are studied, namely (i) the sheet with variable temperature (PST case) and (ii) the sheet with variable heat flux (PHF case). The heat transfer aspects are investigated for both integer and non-integer values of the power-law index. The governing partial differential equations are reduced to a system of nonlinear ordinary differential equations using appropriate similarity variables and solved numerically. The numerical results are obtained by the shooting method using adaptive Runge Kutta method with Broyden's method in the domain[Formula: see text]. The numerical results for the temperature field are found to be strongly dependent upon the power-law index, stretching parameter, wall temperature parameter, material parameter of the Sisko fluid and Prandtl number. In addition, the local Nusselt number versus wall temperature parameter is also graphed and tabulated for different values of pertaining parameters. Further, numerical results are validated by comparison with exact solutions as well as previously published results in the literature.

Comparisons of linear and nonlinear pyramid schemes for signal and image processing

NASA Astrophysics Data System (ADS)

Morales, Aldo W.; Ko, Sung-Jea

1997-04-01

Linear filters banks are being used extensively in image and video applications. New research results in wavelet applications for compression and de-noising are constantly appearing in the technical literature. On the other hand, non-linear filter banks are also being used regularly in image pyramid algorithms. There are some inherent advantages in using non-linear filters instead of linear filters when non-Gaussian processes are present in images. However, a consistent way of comparing performance criteria between these two schemes has not been fully developed yet. In this paper a recently discovered tool, sample selection probabilities, is used to compare the behavior of linear and non-linear filters. In the conversion from weights of order statistics (OS) filters to coefficients of the impulse response is obtained through these probabilities. However, the reverse problem: the conversion from coefficients of the impulse response to the weights of OS filters is not yet fully understood. One of the reasons for this difficulty is the highly non-linear nature of the partitions and generating function used. In the present paper the problem is posed as an optimization of integer linear programming subject to constraints directly obtained from the coefficients of the impulse response. Although the technique to be presented in not completely refined, it certainly appears to be promising. Some results will be shown.

Multiple object tracking using the shortest path faster association algorithm.

PubMed

Xi, Zhenghao; Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

PubMed Central

Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time. PMID:25215322

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis :

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adams, Brian M.; Ebeida, Mohamed Salah; Eldred, Michael S.

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components requiredmore » for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.« less

Coordinated Control Method of Voltage and Reactive Power for Active Distribution Networks Based on Soft Open Point

DOE PAGES

Li, Peng; Ji, Haoran; Wang, Chengshan; ...

2017-03-22

The increasing penetration of distributed generators (DGs) exacerbates the risk of voltage violations in active distribution networks (ADNs). The conventional voltage regulation devices limited by the physical constraints are difficult to meet the requirement of real-time voltage and VAR control (VVC) with high precision when DGs fluctuate frequently. But, soft open point (SOP), a flexible power electronic device, can be used as the continuous reactive power source to realize the fast voltage regulation. Considering the cooperation of SOP and multiple regulation devices, this paper proposes a coordinated VVC method based on SOP for ADNs. Firstly, a time-series model of coordi-natedmore » VVC is developed to minimize operation costs and eliminate voltage violations of ADNs. Then, by applying the linearization and conic relaxation, the original nonconvex mixed-integer non-linear optimization model is converted into a mixed-integer second-order cone programming (MISOCP) model which can be efficiently solved to meet the requirement of voltage regulation rapidity. Here, we carried out some case studies on the IEEE 33-node system and IEEE 123-node system to illustrate the effectiveness of the proposed method.« less

Optimising multi-product multi-chance-constraint inventory control system with stochastic period lengths and total discount under fuzzy purchasing price and holding costs

NASA Astrophysics Data System (ADS)

Allah Taleizadeh, Ata; Niaki, Seyed Taghi Akhavan; Aryanezhad, Mir-Bahador

2010-10-01

While the usual assumptions in multi-periodic inventory control problems are that the orders are placed at the beginning of each period (periodic review) or depending on the inventory level they can happen at any time (continuous review), in this article, we relax these assumptions and assume that the periods between two replenishments of the products are independent and identically distributed random variables. Furthermore, assuming that the purchasing price are triangular fuzzy variables, the quantities of the orders are of integer-type and that there are space and service level constraints, total discount are considered to purchase products and a combination of back-order and lost-sales are taken into account for the shortages. We show that the model of this problem is a fuzzy mixed-integer nonlinear programming type and in order to solve it, a hybrid meta-heuristic intelligent algorithm is proposed. At the end, a numerical example is given to demonstrate the applicability of the proposed methodology and to compare its performance with one of the existing algorithms in real world inventory control problems.

Coordinated Control Method of Voltage and Reactive Power for Active Distribution Networks Based on Soft Open Point

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Peng; Ji, Haoran; Wang, Chengshan

The increasing penetration of distributed generators (DGs) exacerbates the risk of voltage violations in active distribution networks (ADNs). The conventional voltage regulation devices limited by the physical constraints are difficult to meet the requirement of real-time voltage and VAR control (VVC) with high precision when DGs fluctuate frequently. But, soft open point (SOP), a flexible power electronic device, can be used as the continuous reactive power source to realize the fast voltage regulation. Considering the cooperation of SOP and multiple regulation devices, this paper proposes a coordinated VVC method based on SOP for ADNs. Firstly, a time-series model of coordi-natedmore » VVC is developed to minimize operation costs and eliminate voltage violations of ADNs. Then, by applying the linearization and conic relaxation, the original nonconvex mixed-integer non-linear optimization model is converted into a mixed-integer second-order cone programming (MISOCP) model which can be efficiently solved to meet the requirement of voltage regulation rapidity. Here, we carried out some case studies on the IEEE 33-node system and IEEE 123-node system to illustrate the effectiveness of the proposed method.« less

Optimal multi-floor plant layout based on the mathematical programming and particle swarm optimization.

PubMed

Lee, Chang Jun

2015-01-01

In the fields of researches associated with plant layout optimization, the main goal is to minimize the costs of pipelines and pumping between connecting equipment under various constraints. However, what is the lacking of considerations in previous researches is to transform various heuristics or safety regulations into mathematical equations. For example, proper safety distances between equipments have to be complied for preventing dangerous accidents on a complex plant. Moreover, most researches have handled single-floor plant. However, many multi-floor plants have been constructed for the last decade. Therefore, the proper algorithm handling various regulations and multi-floor plant should be developed. In this study, the Mixed Integer Non-Linear Programming (MINLP) problem including safety distances, maintenance spaces, etc. is suggested based on mathematical equations. The objective function is a summation of pipeline and pumping costs. Also, various safety and maintenance issues are transformed into inequality or equality constraints. However, it is really hard to solve this problem due to complex nonlinear constraints. Thus, it is impossible to use conventional MINLP solvers using derivatives of equations. In this study, the Particle Swarm Optimization (PSO) technique is employed. The ethylene oxide plant is illustrated to verify the efficacy of this study.

Synthesizing optimal waste blends

DOE Office of Scientific and Technical Information (OSTI.GOV)

Narayan, V.; Diwekar, W.M.; Hoza, M.

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 thismore » 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.« less

Inverse halftoning via robust nonlinear filtering

NASA Astrophysics Data System (ADS)

Shen, Mei-Yin; Kuo, C.-C. Jay

1999-10-01

A new blind inverse halftoning algorithm based on a nonlinear filtering technique of low computational complexity and low memory requirement is proposed in this research. It is called blind since we do not require the knowledge of the halftone kernel. The proposed scheme performs nonlinear filtering in conjunction with edge enhancement to improve the quality of an inverse halftoned image. Distinct features of the proposed approach include: efficiently smoothing halftone patterns in large homogeneous areas, additional edge enhancement capability to recover the edge quality and an excellent PSNR performance with only local integer operations and a small memory buffer.

Wind Farm Turbine Type and Placement Optimization

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Wind farm turbine type and placement optimization

DOE PAGES

Graf, Peter; Dykes, Katherine; Scott, George; ...

2016-10-03

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

Stability Analysis of Distributed Order Fractional Chen System

PubMed Central

Aminikhah, H.; Refahi Sheikhani, A.; Rezazadeh, H.

2013-01-01

We first investigate sufficient and necessary conditions of stability of nonlinear distributed order fractional system and then we generalize the integer-order Chen system into the distributed order fractional domain. Based on the asymptotic stability theory of nonlinear distributed order fractional systems, the stability of distributed order fractional Chen system is discussed. In addition, we have found that chaos exists in the double fractional order Chen system. Numerical solutions are used to verify the analytical results. PMID:24489508

A multiobjective optimization model and an orthogonal design-based hybrid heuristic algorithm for regional urban mining management problems.

PubMed

Wu, Hao; Wan, Zhong

2018-02-01

In this paper, a multiobjective mixed-integer piecewise nonlinear programming model (MOMIPNLP) is built to formulate the management problem of urban mining system, where the decision variables are associated with buy-back pricing, choices of sites, transportation planning, and adjustment of production capacity. Different from the existing approaches, the social negative effect, generated from structural optimization of the recycling system, is minimized in our model, as well as the total recycling profit and utility from environmental improvement are jointly maximized. For solving the problem, the MOMIPNLP model is first transformed into an ordinary mixed-integer nonlinear programming model by variable substitution such that the piecewise feature of the model is removed. Then, based on technique of orthogonal design, a hybrid heuristic algorithm is developed to find an approximate Pareto-optimal solution, where genetic algorithm is used to optimize the structure of search neighborhood, and both local branching algorithm and relaxation-induced neighborhood search algorithm are employed to cut the searching branches and reduce the number of variables in each branch. Numerical experiments indicate that this algorithm spends less CPU (central processing unit) time in solving large-scale regional urban mining management problems, especially in comparison with the similar ones available in literature. By case study and sensitivity analysis, a number of practical managerial implications are revealed from the model. Since the metal stocks in society are reliable overground mineral sources, urban mining has been paid great attention as emerging strategic resources in an era of resource shortage. By mathematical modeling and development of efficient algorithms, this paper provides decision makers with useful suggestions on the optimal design of recycling system in urban mining. For example, this paper can answer how to encourage enterprises to join the recycling activities by government's support and subsidies, whether the existing recycling system can meet the developmental requirements or not, and what is a reasonable adjustment of production capacity.

Dynamic UNITY

DTIC Science & Technology

2002-01-01

UNITY program that implements exactly the same algorithm as Specification 1.1. The correctness of this program is proven in amanner sim- 4 program...chapter, we introduce the Dynamic UNITY formalism, which allows us to reason about algorithms and protocols in which the sets of participating processes...implements Euclid’s algorithm for calculating the greatest common divisor (GCD) of two integers; it repeat- edly reads an integer message from each of its

Stochastic Semidefinite Programming: Applications and Algorithms

DTIC Science & Technology

2012-03-03

doi: 2011/09/07 13:38:21 13 TOTAL: 1 Number of Papers published in non peer-reviewed journals: Baha M. Alzalg and K. A. Ariyawansa, Stochastic...symmetric programming over integers. International Conference on Scientific Computing, Las Vegas, Nevada, July 18--21, 2011. Baha M. Alzalg. On recent...Proceeding publications (other than abstracts): PaperReceived Baha M. Alzalg, K. A. Ariyawansa. Stochastic mixed integer second-order cone programming

Comparison of Integer Programming (IP) Solvers for Automated Test Assembly (ATA). Research Report. ETS RR-15-05

ERIC Educational Resources Information Center

Donoghue, John R.

2015-01-01

At the heart of van der Linden's approach to automated test assembly (ATA) is a linear programming/integer programming (LP/IP) problem. A variety of IP solvers are available, ranging in cost from free to hundreds of thousands of dollars. In this paper, I compare several approaches to solving the underlying IP problem. These approaches range from…

Concurrent airline fleet allocation and aircraft design with profit modeling for multiple airlines

NASA Astrophysics Data System (ADS)

Govindaraju, Parithi

A "System of Systems" (SoS) approach is particularly beneficial in analyzing complex large scale systems comprised of numerous independent systems -- each capable of independent operations in their own right -- that when brought in conjunction offer capabilities and performance beyond the constituents of the individual systems. The variable resource allocation problem is a type of SoS problem, which includes the allocation of "yet-to-be-designed" systems in addition to existing resources and systems. The methodology presented here expands upon earlier work that demonstrated a decomposition approach that sought to simultaneously design a new aircraft and allocate this new aircraft along with existing aircraft in an effort to meet passenger demand at minimum fleet level operating cost for a single airline. The result of this describes important characteristics of the new aircraft. The ticket price model developed and implemented here enables analysis of the system using profit maximization studies instead of cost minimization. A multiobjective problem formulation has been implemented to determine characteristics of a new aircraft that maximizes the profit of multiple airlines to recognize the fact that aircraft manufacturers sell their aircraft to multiple customers and seldom design aircraft customized to a single airline's operations. The route network characteristics of two simple airlines serve as the example problem for the initial studies. The resulting problem formulation is a mixed-integer nonlinear programming problem, which is typically difficult to solve. A sequential decomposition strategy is applied as a solution methodology by segregating the allocation (integer programming) and aircraft design (non-linear programming) subspaces. After solving a simple problem considering two airlines, the decomposition approach is then applied to two larger airline route networks representing actual airline operations in the year 2005. The decomposition strategy serves as a promising technique for future detailed analyses. Results from the profit maximization studies favor a smaller aircraft in terms of passenger capacity due to its higher yield generation capability on shorter routes while results from the cost minimization studies favor a larger aircraft due to its lower direct operating cost per seat mile.

Optimal Facility Location Tool for Logistics Battle Command (LBC)

DTIC Science & Technology

2015-08-01

64 Appendix B. VBA Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Appendix C. Story...should city planners have located emergency service facilities so that all households (the demand) had equal access to coverage?” The critical...programming language called Visual Basic for Applications ( VBA ). CPLEX is a commercial solver for linear, integer, and mixed integer linear programming problems

A Treatment of Computational Precision, Number Representation, and Large Integers in an Introductory Fortran Course

ERIC Educational Resources Information Center

Richardson, William H., Jr.

2006-01-01

Computational precision is sometimes given short shrift in a first programming course. Treating this topic requires discussing integer and floating-point number representations and inaccuracies that may result from their use. An example of a moderately simple programming problem from elementary statistics was examined. It forced students to…

An Integer Programming Approach to School District Financial Management.

ERIC Educational Resources Information Center

Dembowski, Frederick L.

Because of the nature of school district cash flows, there are opportunities for investing surplus cash and the necessity to borrow cash in deficit periods. The term structure of interest rates makes the manual determination of the optimal financial package impossible. In this research, an integer programming model of this cash management process…

Currency Arbitrage Detection Using a Binary Integer Programming Model

ERIC Educational Resources Information Center

Soon, Wanmei; Ye, Heng-Qing

2011-01-01

In this article, we examine the use of a new binary integer programming (BIP) model to detect arbitrage opportunities in currency exchanges. This model showcases an excellent application of mathematics to the real world. The concepts involved are easily accessible to undergraduate students with basic knowledge in Operations Research. Through this…

Towards Lagrangian formulations of mixed-symmetry higher spin fields on AdS-space within BFV-BRST formalism

NASA Astrophysics Data System (ADS)

Reshetnyak, A. A.

2010-11-01

The spectrum of superstring theory on the AdS 5 × S 5 Ramond-Ramond background in tensionless limit contains integer and half-integer higher-spin fields subject at most to two-rows Young tableaux Y( s 1, s 2). We review the details of a gauge-invariant Lagrangian description of such massive and massless higher-spin fields in anti-de-Sitter spaces with arbitrary dimensions. The procedure is based on the construction of Verma modules, its oscillator realizations and of a BFV-BRST operator for non-linear algebras encoding unitary irreducible representations of AdS group.

MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics.

PubMed

Egea, Jose A; Henriques, David; Cokelaer, Thomas; Villaverde, Alejandro F; MacNamara, Aidan; Danciu, Diana-Patricia; Banga, Julio R; Saez-Rodriguez, Julio

2014-05-10

Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools. We present MEIGO, an R and Matlab optimization toolbox (also available in Python via a wrapper of the R version), that implements metaheuristics capable of solving diverse problems arising in systems biology and bioinformatics. The toolbox includes the enhanced scatter search method (eSS) for continuous nonlinear programming (cNLP) and mixed-integer programming (MINLP) problems, and variable neighborhood search (VNS) for Integer Programming (IP) problems. Additionally, the R version includes BayesFit for parameter estimation by Bayesian inference. The eSS and VNS methods can be run on a single-thread or in parallel using a cooperative strategy. The code is supplied under GPLv3 and is available at http://www.iim.csic.es/~gingproc/meigo.html. Documentation and examples are included. The R package has been submitted to BioConductor. We evaluate MEIGO against optimization benchmarks, and illustrate its applicability to a series of case studies in bioinformatics and systems biology where it outperforms other state-of-the-art methods. MEIGO provides a free, open-source platform for optimization that can be applied to multiple domains of systems biology and bioinformatics. It includes efficient state of the art metaheuristics, and its open and modular structure allows the addition of further methods.

MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics

PubMed Central

2014-01-01

Background Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools. Results We present MEIGO, an R and Matlab optimization toolbox (also available in Python via a wrapper of the R version), that implements metaheuristics capable of solving diverse problems arising in systems biology and bioinformatics. The toolbox includes the enhanced scatter search method (eSS) for continuous nonlinear programming (cNLP) and mixed-integer programming (MINLP) problems, and variable neighborhood search (VNS) for Integer Programming (IP) problems. Additionally, the R version includes BayesFit for parameter estimation by Bayesian inference. The eSS and VNS methods can be run on a single-thread or in parallel using a cooperative strategy. The code is supplied under GPLv3 and is available at http://www.iim.csic.es/~gingproc/meigo.html. Documentation and examples are included. The R package has been submitted to BioConductor. We evaluate MEIGO against optimization benchmarks, and illustrate its applicability to a series of case studies in bioinformatics and systems biology where it outperforms other state-of-the-art methods. Conclusions MEIGO provides a free, open-source platform for optimization that can be applied to multiple domains of systems biology and bioinformatics. It includes efficient state of the art metaheuristics, and its open and modular structure allows the addition of further methods. PMID:24885957

Puerto Rico water resources planning model program description

USGS Publications Warehouse

Moody, D.W.; Maddock, Thomas; Karlinger, M.R.; Lloyd, J.J.

1973-01-01

Because the use of the Mathematical Programming System -Extended (MPSX) to solve large linear and mixed integer programs requires the preparation of many input data cards, a matrix generator program to produce the MPSX input data from a much more limited set of data may expedite the use of the mixed integer programming optimization technique. The Model Definition and Control Program (MODCQP) is intended to assist a planner in preparing MPSX input data for the Puerto Rico Water Resources Planning Model. The model utilizes a mixed-integer mathematical program to identify a minimum present cost set of water resources projects (diversions, reservoirs, ground-water fields, desalinization plants, water treatment plants, and inter-basin transfers of water) which will meet a set of future water demands and to determine their sequence of construction. While MODCOP was specifically written to generate MPSX input data for the planning model described in this report, the program can be easily modified to reflect changes in the model's mathematical structure.

Lyapunov functions for a class of nonlinear systems using Caputo derivative

NASA Astrophysics Data System (ADS)

Fernandez-Anaya, G.; Nava-Antonio, G.; Jamous-Galante, J.; Muñoz-Vega, R.; Hernández-Martínez, E. G.

2017-02-01

This paper presents an extension of recent results that allow proving the stability of Caputo nonlinear and time-varying systems, by means of the fractional order Lyapunov direct method, using quadratic Lyapunov functions. This article introduces a new way of building polynomial Lyapunov functions of any positive integer order as a way of determining the stability of a greater variety of systems when the order of the derivative is 0 < α < 1. Some examples are given to validate these results.

Data Sufficiency Assessment and Pumping Test Design for Groundwater Prediction Using Decision Theory and Genetic Algorithms

NASA Astrophysics Data System (ADS)

McPhee, J.; William, Y. W.

2005-12-01

This work presents a methodology for pumping test design based on the reliability requirements of a groundwater model. Reliability requirements take into consideration the application of the model results in groundwater management, expressed in this case as a multiobjective management model. The pumping test design is formulated as a mixed-integer nonlinear programming (MINLP) problem and solved using a combination of genetic algorithm (GA) and gradient-based optimization. Bayesian decision theory provides a formal framework for assessing the influence of parameter uncertainty over the reliability of the proposed pumping test. The proposed methodology is useful for selecting a robust design that will outperform all other candidate designs under most potential 'true' states of the system

Dynamic analysis for solid waste management systems: an inexact multistage integer programming approach.

PubMed

Li, Yongping; Huang, Guohe

2009-03-01

In this study, a dynamic analysis approach based on an inexact multistage integer programming (IMIP) model is developed for supporting municipal solid waste (MSW) management under uncertainty. Techniques of interval-parameter programming and multistage stochastic programming are incorporated within an integer-programming framework. The developed IMIP can deal with uncertainties expressed as probability distributions and interval numbers, and can reflect the dynamics in terms of decisions for waste-flow allocation and facility-capacity expansion over a multistage context. Moreover, the IMIP can be used for analyzing various policy scenarios that are associated with different levels of economic consequences. The developed method is applied to a case study of long-term waste-management planning. The results indicate that reasonable solutions have been generated for binary and continuous variables. They can help generate desired decisions of system-capacity expansion and waste-flow allocation with a minimized system cost and maximized system reliability.

The CMC/3DPNS computer program for prediction of three-dimensional, subsonic, turbulent aerodynamic juncture region flow. Volume 3: Programmers' manual

NASA Technical Reports Server (NTRS)

Orzechowski, J. A.

1982-01-01

The CMC fluid mechanics program system was developed to transmit the theoretical evolution of finite element numerical solution methodology, applied to nonlinear field problems into a versatile computer code for comprehensive flow field analysis. A detailed view of the code from the standpoint of a computer programmer's use is presented. A system macroflow chart and detailed flow charts of several routines necessary to interact with a theoretican/user to modify the operation of this program are presented. All subroutines and details of usage, primarily for input and output routines are described. Integer and real scalars and a cross reference list denoting subroutine usage for these scalars are outlined. Entry points in dynamic storage vector IZ; the lengths of each vector accompanying the scalar definitions are described. A listing of the routines peculiar to the standard test case and a listing of the input deck and printout for this case are included.

Airborne Tactical Crossload Planner

DTIC Science & Technology

2017-12-01

set out in the Airborne Standard Operating Procedure (ASOP). 14. SUBJECT TERMS crossload, airborne, optimization, integer linear programming ...they land to their respective sub-mission locations. In this thesis, we formulate and implement an integer linear program called the Tactical...to meet any desired crossload objectives. xiv We demonstrate TCP with two real-world tactical problems from recent airborne operations: one by the

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

DOE PAGES

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

2016-05-01

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

Logic integer programming models for signaling networks.

PubMed

Haus, Utz-Uwe; Niermann, Kathrin; Truemper, Klaus; Weismantel, Robert

2009-05-01

We propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this, we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in molecular biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.

A logic-based method for integer programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hooker, J.; Natraj, N.R.

1994-12-31

We propose a logic-based approach to integer programming that replaces traditional branch-and-cut techniques with logical analogs. Integer variables are regarded as atomic propositions. The constraints give rise to logical formulas that are analogous to separating cuts. No continuous relaxation is used. Rather, the cuts are selected so that they can be easily solved as a discrete relaxation. (In fact, defining a relaxation and generating cuts are best seen as the same problem.) We experiment with relaxations that have a k-tree structure and can be solved by nonserial dynamic programming. We also present logic-based analogs of facet-defining cuts, Chv{acute a}tal rank,more » etc. We conclude with some preliminary computational results.« less

Advances in fractal germanium micro/nanoclusters induced by gold: microstructures and properties.

PubMed

Chen, Zhiwen; Shek, Chan-Hung; Wu, C M Lawrence; Lai, Joseph K L

2014-02-01

Germanium materials are a class of unique semiconductor materials with widespread technological applications because of their valuable semiconducting, electrical, optical, and thermoelectric power properties in the fields of macro/mesoscopic materials and micro/nanodevices. In this review, we describe the efforts toward understanding the microstructures and various properties of the fractal germanium micro/nanoclusters induced by gold prepared by high vacuum thermal evaporation techniques, highlighting contributions from our laboratory. First, we present the integer and non-integer dimensional germanium micro/nanoclusters such as nanoparticles, nanorings, and nanofractals induced by gold and annealing. In particular, the nonlinear electrical behavior of a gold/germanium bilayer film with the interesting nanofractal is discussed in detail. In addition, the third-order optical nonlinearities of the fractal germanium nanocrystals embedded in gold matrix will be summarized by using the sensitive and reliable Z-scan techniques aimed to determine the nonlinear absorption coefficient and nonlinear refractive index. Finally, we emphasize the thermoelectric power properties of the gold/germanium bilayer films. The thermoelectric power measurement is considered to be a more effective method than the conductivity for investigating superlocalization in a percolating system. This research may provide a novel insight to modulate their competent performance and promote rational design of micro/nanodevices. Once mastered, germanium thin films with a variety of fascinating micro/nanoclusters will offer vast and unforeseen opportunities in the semiconductor industry as well as in other fields of science and technology.

Fate of a gray soliton in a quenched Bose-Einstein condensate

NASA Astrophysics Data System (ADS)

Gamayun, O.; Bezvershenko, Yu. V.; Cheianov, V.

2015-03-01

We investigate the destiny of a gray soliton in a repulsive one-dimensional Bose-Einstein condensate undergoing a sudden quench of the nonlinearity parameter. The outcome of the quench is found to depend dramatically on the ratio η of the final and initial values of the speed of sound. For integer η the soliton splits into exactly 2 η -1 solitons. For noninteger η the soliton decays into multiple solitons and Bogoliubov modes. The case of integer η is analyzed in detail. The parameters of solitons in the out state are found explicitly. Our approach exploits the inverse scattering method and can be easily used for similar quenches in any classical integrable system.

Complex motion of a vehicle through a series of signals controlled by power-law phase

NASA Astrophysics Data System (ADS)

Nagatani, Takashi

2017-07-01

We study the dynamic motion of a vehicle moving through the series of traffic signals controlled by the position-dependent phase of power law. All signals are controlled by both cycle time and position-dependent phase. The dynamic model of the vehicular motion is described in terms of the nonlinear map. The vehicular motion varies in a complex manner by varying cycle time for various values of the power of the position-dependent phase. The vehicle displays the periodic motion with a long cycle for the integer power of the phase, while the vehicular motion exhibits the very complex behavior for the non-integer power of the phase.

Determination of optimum values for maximizing the profit in bread production: Daily bakery Sdn Bhd

NASA Astrophysics Data System (ADS)

Muda, Nora; Sim, Raymond

2015-02-01

An integer programming problem is a mathematical optimization or feasibility program in which some or all of the variables are restricted to be integers. In many settings the term refers to integer linear programming (ILP), in which the objective function and the constraints (other than the integer constraints) are linear. An ILP has many applications in industrial production, including job-shop modelling. A possible objective is to maximize the total production, without exceeding the available resources. In some cases, this can be expressed in terms of a linear program, but variables must be constrained to be integer. It concerned with the optimization of a linear function while satisfying a set of linear equality and inequality constraints and restrictions. It has been used to solve optimization problem in many industries area such as banking, nutrition, agriculture, and bakery and so on. The main purpose of this study is to formulate the best combination of all ingredients in producing different type of bread in Daily Bakery in order to gain maximum profit. This study also focuses on the sensitivity analysis due to changing of the profit and the cost of each ingredient. The optimum result obtained from QM software is RM 65,377.29 per day. This study will be benefited for Daily Bakery and also other similar industries. By formulating a combination of all ingredients make up, they can easily know their total profit in producing bread everyday.

Pattern Formation and Complexity Emergence

NASA Astrophysics Data System (ADS)

Berezin, Alexander A.

2001-03-01

Success of nonlinear modelling of pattern formation and self-organization encourages speculations on informational and number theoretical foundations of complexity emergence. Pythagorean "unreasonable effectiveness of integers" in natural processes is perhaps extrapolatable even to universal emergence "out-of-nothing" (Leibniz, Wheeler). Because rational numbers (R = M/N) are everywhere dense on real axis, any digital string (hence any "book" from "Library of Babel" of J.L.Borges) is "recorded" infinitely many times in arbitrary many rationals. Furthermore, within any arbitrary small interval there are infinitely many Rs for which (either or both) integers (Ms and Ns) "carry" any given string of any given length. Because any iterational process (such as generation of fractal features of Mandelbrot Set) is arbitrary closely approximatable with rational numbers, the infinite pattern of integers expresses itself in generation of complexity of the world, as well as in emergence of the world itself. This "tunnelling" from Platonic World ("Platonia" of J.Barbour) to a real (physical) world is modern recast of Leibniz's motto ("for deriving all from nothing there suffices a single principle").

Design of supply chain in fuzzy environment

NASA Astrophysics Data System (ADS)

Rao, Kandukuri Narayana; Subbaiah, Kambagowni Venkata; Singh, Ganja Veera Pratap

2013-05-01

Nowadays, customer expectations are increasing and organizations are prone to operate in an uncertain environment. Under this uncertain environment, the ultimate success of the firm depends on its ability to integrate business processes among supply chain partners. Supply chain management emphasizes cross-functional links to improve the competitive strategy of organizations. Now, companies are moving from decoupled decision processes towards more integrated design and control of their components to achieve the strategic fit. In this paper, a new approach is developed to design a multi-echelon, multi-facility, and multi-product supply chain in fuzzy environment. In fuzzy environment, mixed integer programming problem is formulated through fuzzy goal programming in strategic level with supply chain cost and volume flexibility as fuzzy goals. These fuzzy goals are aggregated using minimum operator. In tactical level, continuous review policy for controlling raw material inventories in supplier echelon and controlling finished product inventories in plant as well as distribution center echelon is considered as fuzzy goals. A non-linear programming model is formulated through fuzzy goal programming using minimum operator in the tactical level. The proposed approach is illustrated with a numerical example.

Multi-Item Multiperiodic Inventory Control Problem with Variable Demand and Discounts: A Particle Swarm Optimization Algorithm

PubMed Central

Mousavi, Seyed Mohsen; Niaki, S. T. A.; Bahreininejad, Ardeshir; Musa, Siti Nurmaya

2014-01-01

A multi-item multiperiod inventory control model is developed for known-deterministic variable demands under limited available budget. Assuming the order quantity is more than the shortage quantity in each period, the shortage in combination of backorder and lost sale is considered. The orders are placed in batch sizes and the decision variables are assumed integer. Moreover, all unit discounts for a number of products and incremental quantity discount for some other items are considered. While the objectives are to minimize both the total inventory cost and the required storage space, the model is formulated into a fuzzy multicriteria decision making (FMCDM) framework and is shown to be a mixed integer nonlinear programming type. In order to solve the model, a multiobjective particle swarm optimization (MOPSO) approach is applied. A set of compromise solution including optimum and near optimum ones via MOPSO has been derived for some numerical illustration, where the results are compared with those obtained using a weighting approach. To assess the efficiency of the proposed MOPSO, the model is solved using multi-objective genetic algorithm (MOGA) as well. A large number of numerical examples are generated at the end, where graphical and statistical approaches show more efficiency of MOPSO compared with MOGA. PMID:25093195

Computer Corner: Spreadsheets, Power Series, Generating Functions, and Integers.

ERIC Educational Resources Information Center

Snow, Donald R.

1989-01-01

Implements a table algorithm on a spreadsheet program and obtains functions for several number sequences such as the Fibonacci and Catalan numbers. Considers other applications of the table algorithm to integers represented in various number bases. (YP)

A Hybrid Tabu Search Heuristic for a Bilevel Competitive Facility Location Model

NASA Astrophysics Data System (ADS)

Küçükaydın, Hande; Aras, Necati; Altınel, I. Kuban

We consider a problem in which a firm or franchise enters a market by locating new facilities where there are existing facilities belonging to a competitor. The firm aims at finding the location and attractiveness of each facility to be opened so as to maximize its profit. The competitor, on the other hand, can react by adjusting the attractiveness of its existing facilities, opening new facilities and/or closing existing ones with the objective of maximizing its own profit. The demand is assumed to be aggregated at certain points in the plane and the facilities of the firm can be located at prespecified candidate sites. We employ Huff's gravity-based rule in modeling the behavior of the customers where the fraction of customers at a demand point that visit a certain facility is proportional to the facility attractiveness and inversely proportional to the distance between the facility site and demand point. We formulate a bilevel mixed-integer nonlinear programming model where the firm entering the market is the leader and the competitor is the follower. In order to find a feasible solution of this model, we develop a hybrid tabu search heuristic which makes use of two exact methods as subroutines: a gradient ascent method and a branch-and-bound algorithm with nonlinear programming relaxation.

Adaptive Resampling Particle Filters for GPS Carrier-Phase Navigation and Collision Avoidance System

NASA Astrophysics Data System (ADS)

Hwang, Soon Sik

This dissertation addresses three problems: 1) adaptive resampling technique (ART) for Particle Filters, 2) precise relative positioning using Global Positioning System (GPS) Carrier-Phase (CP) measurements applied to nonlinear integer resolution problem for GPS CP navigation using Particle Filters, and 3) collision detection system based on GPS CP broadcasts. First, Monte Carlo filters, called Particle Filters (PF), are widely used where the system is non-linear and non-Gaussian. In real-time applications, their estimation accuracies and efficiencies are significantly affected by the number of particles and the scheduling of relocating weights and samples, the so-called resampling step. In this dissertation, the appropriate number of particles is estimated adaptively such that the error of the sample mean and variance stay in bounds. These bounds are given by the confidence interval of a normal probability distribution for a multi-variate state. Two required number of samples maintaining the mean and variance error within the bounds are derived. The time of resampling is determined when the required sample number for the variance error crosses the required sample number for the mean error. Second, the PF using GPS CP measurements with adaptive resampling is applied to precise relative navigation between two GPS antennas. In order to make use of CP measurements for navigation, the unknown number of cycles between GPS antennas, the so called integer ambiguity, should be resolved. The PF is applied to this integer ambiguity resolution problem where the relative navigation states estimation involves nonlinear observations and nonlinear dynamics equation. Using the PF, the probability density function of the states is estimated by sampling from the position and velocity space and the integer ambiguities are resolved without using the usual hypothesis tests to search for the integer ambiguity. The ART manages the number of position samples and the frequency of the resampling step for real-time kinematics GPS navigation. The experimental results demonstrate the performance of the ART and the insensitivity of the proposed approach to GPS CP cycle-slips. Third, the GPS has great potential for the development of new collision avoidance systems and is being considered for the next generation Traffic alert and Collision Avoidance System (TCAS). The current TCAS equipment, is capable of broadcasting GPS code information to nearby airplanes, and also, the collision avoidance system using the navigation information based on GPS code has been studied by researchers. In this dissertation, the aircraft collision detection system using GPS CP information is addressed. The PF with position samples is employed for the CP based relative position estimation problem and the same algorithm can be used to determine the vehicle attitude if multiple GPS antennas are used. For a reliable and enhanced collision avoidance system, three dimensional trajectories are projected using the estimates of the relative position, velocity, and the attitude. It is shown that the performance of GPS CP based collision detecting algorithm meets the accuracy requirements for a precise approach of flight for auto landing with significantly less unnecessary collision false alarms and no miss alarms.

Fractional Order and Dynamic Simulation of a System Involving an Elastic Wide Plate

NASA Astrophysics Data System (ADS)

David, S. A.; Balthazar, J. M.; Julio, B. H. S.; Oliveira, C.

2011-09-01

Numerous researchers have studied about nonlinear dynamics in several areas of science and engineering. However, in most cases, these concepts have been explored mainly from the standpoint of analytical and computational methods involving integer order calculus (IOC). In this paper we have examined the dynamic behavior of an elastic wide plate induced by two electromagnets of a point of view of the fractional order calculus (FOC). The primary focus of this study is on to help gain a better understanding of nonlinear dynamic in fractional order systems.

DAKOTA Design Analysis Kit for Optimization and Terascale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adams, Brian M.; Dalbey, Keith R.; Eldred, Michael S.

2010-02-24

The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes (computational models) and iterative analysis methods. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and analysis of computational models on high performance computers.A user provides a set of DAKOTA commands in an input file and launches DAKOTA. DAKOTA invokes instances of the computational models, collects their results, and performs systems analyses. DAKOTA contains algorithms for optimization with gradient and nongradient-basedmore » methods; uncertainty quantification with sampling, reliability, polynomial chaos, stochastic collocation, and epistemic methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as hybrid optimization, surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. Services for parallel computing, simulation interfacing, approximation modeling, fault tolerance, restart, and graphics are also included.« less

Implementation of software-based sensor linearization algorithms on low-cost microcontrollers.

PubMed

Erdem, Hamit

2010-10-01

Nonlinear sensors and microcontrollers are used in many embedded system designs. As the input-output characteristic of most sensors is nonlinear in nature, obtaining data from a nonlinear sensor by using an integer microcontroller has always been a design challenge. This paper discusses the implementation of six software-based sensor linearization algorithms for low-cost microcontrollers. The comparative study of the linearization algorithms is performed by using a nonlinear optical distance-measuring sensor. The performance of the algorithms is examined with respect to memory space usage, linearization accuracy and algorithm execution time. The implementation and comparison results can be used for selection of a linearization algorithm based on the sensor transfer function, expected linearization accuracy and microcontroller capacity. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Special class of nonlinear damping models in flexible space structures

NASA Technical Reports Server (NTRS)

Hu, Anren; Singh, Ramendra P.; Taylor, Lawrence W.

1991-01-01

A special class of nonlinear damping models is investigated in which the damping force is proportional to the product of positive integer or the fractional power of the absolute values of displacement and velocity. For a one-degree-of-freedom system, the classical Krylov-Bogoliubov 'averaging' method is used, whereas for a distributed system, both an ad hoc perturbation technique and the finite difference method are employed to study the effects of nonlinear damping. The results are compared with linear viscous damping models. The amplitude decrement of free vibration for a single mode system with nonlinear models depends not only on the damping ratio but also on the initial amplitude, the time to measure the response, the frequency of the system, and the powers of displacement and velocity. For the distributed system, the action of nonlinear damping is found to reduce the energy of the system and to pass energy to lower modes.

Vortex and half-vortex dynamics in a nonlinear spinor quantum fluid

PubMed Central

Dominici, Lorenzo; Dagvadorj, Galbadrakh; Fellows, Jonathan M.; Ballarini, Dario; De Giorgi, Milena; Marchetti, Francesca M.; Piccirillo, Bruno; Marrucci, Lorenzo; Bramati, Alberto; Gigli, Giuseppe; Szymańska, Marzena H.; Sanvitto, Daniele

2015-01-01

Vortices are archetypal objects that recur in the universe across the scale of complexity, from subatomic particles to galaxies and black holes. Their appearance is connected with spontaneous symmetry breaking and phase transitions. In Bose-Einstein condensates and superfluids, vortices are both point-like and quantized quasiparticles. We use a two-dimensional (2D) fluid of polaritons, bosonic particles constituted by hybrid photonic and electronic oscillations, to study quantum vortex dynamics. Polaritons benefit from easiness of wave function phase detection, a spinor nature sustaining half-integer vorticity, strong nonlinearity, and tuning of the background disorder. We can directly generate by resonant pulsed excitations a polariton condensate carrying either a full or half-integer vortex as initial condition and follow their coherent evolution using ultrafast imaging on the picosecond scale. The observations highlight a rich phenomenology, such as the spiraling of the half-vortex and the joint path of the twin charges of a full vortex, until the moment of their splitting. Furthermore, we observe the ordered branching into newly generated secondary couples, associated with the breaking of radial and azimuthal symmetries. This allows us to devise the interplay of nonlinearity and sample disorder in shaping the fluid and driving the vortex dynamics. In addition, our observations suggest that phase singularities may be seen as fundamental particles whose quantized events span from pair creation and recombination to 2D+t topological vortex strings. PMID:26665174

Vortex and half-vortex dynamics in a nonlinear spinor quantum fluid.

PubMed

Dominici, Lorenzo; Dagvadorj, Galbadrakh; Fellows, Jonathan M; Ballarini, Dario; De Giorgi, Milena; Marchetti, Francesca M; Piccirillo, Bruno; Marrucci, Lorenzo; Bramati, Alberto; Gigli, Giuseppe; Szymańska, Marzena H; Sanvitto, Daniele

2015-12-01

Vortices are archetypal objects that recur in the universe across the scale of complexity, from subatomic particles to galaxies and black holes. Their appearance is connected with spontaneous symmetry breaking and phase transitions. In Bose-Einstein condensates and superfluids, vortices are both point-like and quantized quasiparticles. We use a two-dimensional (2D) fluid of polaritons, bosonic particles constituted by hybrid photonic and electronic oscillations, to study quantum vortex dynamics. Polaritons benefit from easiness of wave function phase detection, a spinor nature sustaining half-integer vorticity, strong nonlinearity, and tuning of the background disorder. We can directly generate by resonant pulsed excitations a polariton condensate carrying either a full or half-integer vortex as initial condition and follow their coherent evolution using ultrafast imaging on the picosecond scale. The observations highlight a rich phenomenology, such as the spiraling of the half-vortex and the joint path of the twin charges of a full vortex, until the moment of their splitting. Furthermore, we observe the ordered branching into newly generated secondary couples, associated with the breaking of radial and azimuthal symmetries. This allows us to devise the interplay of nonlinearity and sample disorder in shaping the fluid and driving the vortex dynamics. In addition, our observations suggest that phase singularities may be seen as fundamental particles whose quantized events span from pair creation and recombination to 2D+t topological vortex strings.

Effects of low sampling rate in the digital data-transition tracking loop

NASA Technical Reports Server (NTRS)

Mileant, A.; Million, S.; Hinedi, S.

1994-01-01

This article describes the performance of the all-digital data-transition tracking loop (DTTL) with coherent and noncoherent sampling using nonlinear theory. The effects of few samples per symbol and of noncommensurate sampling and symbol rates are addressed and analyzed. Their impact on the probability density and variance of the phase error are quantified through computer simulations. It is shown that the performance of the all-digital DTTL approaches its analog counterpart when the sampling and symbol rates are noncommensurate (i.e., the number of samples per symbol is an irrational number). The loop signal-to-noise ratio (SNR) (inverse of phase error variance) degrades when the number of samples per symbol is an odd integer but degrades even further for even integers.

Topology versus Anderson localization: Nonperturbative solutions in one dimension

NASA Astrophysics Data System (ADS)

Altland, Alexander; Bagrets, Dmitry; Kamenev, Alex

2015-02-01

We present an analytic theory of quantum criticality in quasi-one-dimensional topological Anderson insulators. We describe these systems in terms of two parameters (g ,χ ) representing localization and topological properties, respectively. Certain critical values of χ (half-integer for Z classes, or zero for Z2 classes) define phase boundaries between distinct topological sectors. Upon increasing system size, the two parameters exhibit flow similar to the celebrated two-parameter flow of the integer quantum Hall insulator. However, unlike the quantum Hall system, an exact analytical description of the entire phase diagram can be given in terms of the transfer-matrix solution of corresponding supersymmetric nonlinear sigma models. In Z2 classes we uncover a hidden supersymmetry, present at the quantum critical point.

Diophantine Equations as a Context for Technology-Enhanced Training in Conjecturing and Proving

ERIC Educational Resources Information Center

Abramovich, Sergei; Sugden, Stephen J.

2008-01-01

Solving indeterminate algebraic equations in integers is a classic topic in the mathematics curricula across grades. At the undergraduate level, the study of solutions of non-linear equations of this kind can be motivated by the use of technology. This article shows how the unity of geometric contextualization and spreadsheet-based amplification…

Currency arbitrage detection using a binary integer programming model

NASA Astrophysics Data System (ADS)

Soon, Wanmei; Ye, Heng-Qing

2011-04-01

In this article, we examine the use of a new binary integer programming (BIP) model to detect arbitrage opportunities in currency exchanges. This model showcases an excellent application of mathematics to the real world. The concepts involved are easily accessible to undergraduate students with basic knowledge in Operations Research. Through this work, students can learn to link several types of basic optimization models, namely linear programming, integer programming and network models, and apply the well-known sensitivity analysis procedure to accommodate realistic changes in the exchange rates. Beginning with a BIP model, we discuss how it can be reduced to an equivalent but considerably simpler model, where an efficient algorithm can be applied to find the arbitrages and incorporate the sensitivity analysis procedure. A simple comparison is then made with a different arbitrage detection model. This exercise helps students learn to apply basic Operations Research concepts to a practical real-life example, and provides insights into the processes involved in Operations Research model formulations.

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Lee, Charles H.

2012-01-01

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

An Interactive Artificial Cutting Plane Method for Bicriterion Integer Programming Problems

DTIC Science & Technology

1992-08-01

AUTHOR(S) Diane Breivik Allen, 1st Lt 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER AFIT Student Attending...INTERACTIVE ARTIFICIAL CUTTING PLANE METHOD FOR BICRITERION INTEGER PROGRAMMING PROBLEMS By Diane Breivik Allen A Thesis Submitted to the Faculty of...ITfiSRA&1 DTIC TAB 0 Unannounced 0 Justirication By BY Diane Breivik Allen Distributlon/ Availability CQdes Avail and/or Dist Special Approved: DTI

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.

PubMed

Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

2016-08-01

This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.

Chromosome structures: reduction of certain problems with unequal gene content and gene paralogs to integer linear programming.

PubMed

Lyubetsky, Vassily; Gershgorin, Roman; Gorbunov, Konstantin

2017-12-06

Chromosome structure is a very limited model of the genome including the information about its chromosomes such as their linear or circular organization, the order of genes on them, and the DNA strand encoding a gene. Gene lengths, nucleotide composition, and intergenic regions are ignored. Although highly incomplete, such structure can be used in many cases, e.g., to reconstruct phylogeny and evolutionary events, to identify gene synteny, regulatory elements and promoters (considering highly conserved elements), etc. Three problems are considered; all assume unequal gene content and the presence of gene paralogs. The distance problem is to determine the minimum number of operations required to transform one chromosome structure into another and the corresponding transformation itself including the identification of paralogs in two structures. We use the DCJ model which is one of the most studied combinatorial rearrangement models. Double-, sesqui-, and single-operations as well as deletion and insertion of a chromosome region are considered in the model; the single ones comprise cut and join. In the reconstruction problem, a phylogenetic tree with chromosome structures in the leaves is given. It is necessary to assign the structures to inner nodes of the tree to minimize the sum of distances between terminal structures of each edge and to identify the mutual paralogs in a fairly large set of structures. A linear algorithm is known for the distance problem without paralogs, while the presence of paralogs makes it NP-hard. If paralogs are allowed but the insertion and deletion operations are missing (and special constraints are imposed), the reduction of the distance problem to integer linear programming is known. Apparently, the reconstruction problem is NP-hard even in the absence of paralogs. The problem of contigs is to find the optimal arrangements for each given set of contigs, which also includes the mutual identification of paralogs. We proved that these problems can be reduced to integer linear programming formulations, which allows an algorithm to redefine the problems to implement a very special case of the integer linear programming tool. The results were tested on synthetic and biological samples. Three well-known problems were reduced to a very special case of integer linear programming, which is a new method of their solutions. Integer linear programming is clearly among the main computational methods and, as generally accepted, is fast on average; in particular, computation systems specifically targeted at it are available. The challenges are to reduce the size of the corresponding integer linear programming formulations and to incorporate a more detailed biological concept in our model of the reconstruction.

Optimal satisfaction degree in energy harvesting cognitive radio networks

NASA Astrophysics Data System (ADS)

Li, Zan; Liu, Bo-Yang; Si, Jiang-Bo; Zhou, Fu-Hui

2015-12-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).

Study of travelling wave solutions for some special-type nonlinear evolution equations

NASA Astrophysics Data System (ADS)

Song, Junquan; Hu, Lan; Shen, Shoufeng; Ma, Wen-Xiu

2018-07-01

The tanh-function expansion method has been improved and used to construct travelling wave solutions of the form U={\\sum }j=0n{a}j{\\tanh }jξ for some special-type nonlinear evolution equations, which have a variety of physical applications. The positive integer n can be determined by balancing the highest order linear term with the nonlinear term in the evolution equations. We improve the tanh-function expansion method with n = 0 by introducing a new transform U=-W\\prime (ξ )/{W}2. A nonlinear wave equation with source terms, and mKdV-type equations, are considered in order to show the effectiveness of the improved scheme. We also propose the tanh-function expansion method of implicit function form, and apply it to a Harry Dym-type equation as an example.

Waste management under multiple complexities: inexact piecewise-linearization-based fuzzy flexible programming.

PubMed

Sun, Wei; Huang, Guo H; Lv, Ying; Li, Gongchen

2012-06-01

To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP's advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP's solutions demonstrate its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities. Copyright © 2012 Elsevier Ltd. All rights reserved.

Mining the preferences of patients for ubiquitous clinic recommendation.

PubMed

Chen, Tin-Chih Toly; Chiu, Min-Chi

2018-03-06

A challenge facing all ubiquitous clinic recommendation systems is that patients often have difficulty articulating their requirements. To overcome this problem, a ubiquitous clinic recommendation mechanism was designed in this study by mining the clinic preferences of patients. Their preferences were defined using the weights in the ubiquitous clinic recommendation mechanism. An integer nonlinear programming problem was solved to tune the values of the weights on a rolling basis. In addition, since it may take a long time to adjust the values of weights to their asymptotic values, the back propagation network (BPN)-response surface method (RSM) method is applied to estimate the asymptotic values of weights. The proposed methodology was tested in a regional study. Experimental results indicated that the ubiquitous clinic recommendation system outperformed several existing methods in improving the successful recommendation rate.

Pricing and location decisions in multi-objective facility location problem with M/M/m/k queuing systems

NASA Astrophysics Data System (ADS)

Tavakkoli-Moghaddam, Reza; Vazifeh-Noshafagh, Samira; Taleizadeh, Ata Allah; Hajipour, Vahid; Mahmoudi, Amin

2017-01-01

This article presents a new multi-objective model for a facility location problem with congestion and pricing policies. This model considers situations in which immobile service facilities are congested by a stochastic demand following M/M/m/k queues. The presented model belongs to the class of mixed-integer nonlinear programming models and NP-hard problems. To solve such a hard model, a new multi-objective optimization algorithm based on a vibration theory, namely multi-objective vibration damping optimization (MOVDO), is developed. In order to tune the algorithms parameters, the Taguchi approach using a response metric is implemented. The computational results are compared with those of the non-dominated ranking genetic algorithm and non-dominated sorting genetic algorithm. The outputs demonstrate the robustness of the proposed MOVDO in large-sized problems.

Managing time-substitutable electricity usage using dynamic controls

DOEpatents

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

2017-02-07

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

Managing time-substitutable electricity usage using dynamic controls

DOEpatents

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

2017-02-21

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

Alternative mathematical programming formulations for FSS synthesis

NASA Technical Reports Server (NTRS)

Reilly, C. H.; Mount-Campbell, C. A.; Gonsalvez, D. J. A.; Levis, C. A.

1986-01-01

A variety of mathematical programming models and two solution strategies are suggested for the problem of allocating orbital positions to (synthesizing) satellites in the Fixed Satellite Service. Mixed integer programming and almost linear programming formulations are presented in detail for each of two objectives: (1) positioning satellites as closely as possible to specified desired locations, and (2) minimizing the total length of the geostationary arc allocated to the satellites whose positions are to be determined. Computational results for mixed integer and almost linear programming models, with the objective of positioning satellites as closely as possible to their desired locations, are reported for three six-administration test problems and a thirteen-administration test problem.

Optimization of Energy Efficiency and Conservation in Green Building Design Using Duelist, Killer-Whale and Rain-Water Algorithms

NASA Astrophysics Data System (ADS)

Biyanto, T. R.; Matradji; Syamsi, M. N.; Fibrianto, H. Y.; Afdanny, N.; Rahman, A. H.; Gunawan, K. S.; Pratama, J. A. D.; Malwindasari, A.; Abdillah, A. I.; Bethiana, T. N.; Putra, Y. A.

2017-11-01

The development of green building has been growing in both design and quality. The development of green building was limited by the issue of expensive investment. Actually, green building can reduce the energy usage inside the building especially in utilization of cooling system. External load plays major role in reducing the usage of cooling system. External load is affected by type of wall sheathing, glass and roof. The proper selection of wall, type of glass and roof material are very important to reduce external load. Hence, the optimization of energy efficiency and conservation in green building design is required. Since this optimization consist of integer and non-linear equations, this problem falls into Mixed-Integer-Non-Linear-Programming (MINLP) that required global optimization technique such as stochastic optimization algorithms. In this paper the optimized variables i.e. type of glass and roof were chosen using Duelist, Killer-Whale and Rain-Water Algorithms to obtain the optimum energy and considering the minimal investment. The optimization results exhibited the single glass Planibel-G with the 3.2 mm thickness and glass wool insulation provided maximum ROI of 36.8486%, EUI reduction of 54 kWh/m2·year, CO2 emission reduction of 486.8971 tons/year and reduce investment of 4,078,905,465 IDR.

Aerospace Applications of Integer and Combinatorial Optimization

NASA Technical Reports Server (NTRS)

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

1995-01-01

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.

Aerospace applications on integer and combinatorial optimization

NASA Technical Reports Server (NTRS)

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

1995-01-01

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.

Integration of progressive hedging and dual decomposition in stochastic integer programs

DOE PAGES

Watson, Jean -Paul; Guo, Ge; Hackebeil, Gabriel; ...

2015-04-07

We present a method for integrating the Progressive Hedging (PH) algorithm and the Dual Decomposition (DD) algorithm of Carøe and Schultz for stochastic mixed-integer programs. Based on the correspondence between lower bounds obtained with PH and DD, a method to transform weights from PH to Lagrange multipliers in DD is found. Fast progress in early iterations of PH speeds up convergence of DD to an exact solution. As a result, we report computational results on server location and unit commitment instances.

Performance comparison of genetic algorithms and particle swarm optimization for model integer programming bus timetabling problem

NASA Astrophysics Data System (ADS)

Wihartiko, F. D.; Wijayanti, H.; Virgantari, F.

2018-03-01

Genetic Algorithm (GA) is a common algorithm used to solve optimization problems with artificial intelligence approach. Similarly, the Particle Swarm Optimization (PSO) algorithm. Both algorithms have different advantages and disadvantages when applied to the case of optimization of the Model Integer Programming for Bus Timetabling Problem (MIPBTP), where in the case of MIPBTP will be found the optimal number of trips confronted with various constraints. The comparison results show that the PSO algorithm is superior in terms of complexity, accuracy, iteration and program simplicity in finding the optimal solution.

Solving the Water Jugs Problem by an Integer Sequence Approach

ERIC Educational Resources Information Center

Man, Yiu-Kwong

2012-01-01

In this article, we present an integer sequence approach to solve the classic water jugs problem. The solution steps can be obtained easily by additions and subtractions only, which is suitable for manual calculation or programming by computer. This approach can be introduced to secondary and undergraduate students, and also to teachers and…

Fast scaffolding with small independent mixed integer programs

PubMed Central

Salmela, Leena; Mäkinen, Veli; Välimäki, Niko; Ylinen, Johannes; Ukkonen, Esko

2011-01-01

Motivation: Assembling genomes from short read data has become increasingly popular, but the problem remains computationally challenging especially for larger genomes. We study the scaffolding phase of sequence assembly where preassembled contigs are ordered based on mate pair data. Results: We present MIP Scaffolder that divides the scaffolding problem into smaller subproblems and solves these with mixed integer programming. The scaffolding problem can be represented as a graph and the biconnected components of this graph can be solved independently. We present a technique for restricting the size of these subproblems so that they can be solved accurately with mixed integer programming. We compare MIP Scaffolder to two state of the art methods, SOPRA and SSPACE. MIP Scaffolder is fast and produces better or as good scaffolds as its competitors on large genomes. Availability: The source code of MIP Scaffolder is freely available at http://www.cs.helsinki.fi/u/lmsalmel/mip-scaffolder/. Contact: leena.salmela@cs.helsinki.fi PMID:21998153

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. Tomore » alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.« less

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

PubMed

Wang, S; Huang, G H

2013-03-15

Flood disasters have been extremely severe in recent decades, and they account for about one third of all natural catastrophes throughout the world. In this study, a two-stage mixed-integer fuzzy programming with interval-valued membership functions (TMFP-IMF) approach is developed for flood-diversion planning under uncertainty. TMFP-IMF integrates the fuzzy flexible programming, two-stage stochastic programming, and integer programming within a general framework. A concept of interval-valued fuzzy membership function is introduced to address complexities of system uncertainties. TMFP-IMF can not only deal with uncertainties expressed as fuzzy sets and probability distributions, but also incorporate pre-regulated water-diversion policies directly into its optimization process. TMFP-IMF is applied to a hypothetical case study of flood-diversion planning for demonstrating its applicability. Results indicate that reasonable solutions can be generated for binary and continuous variables. A variety of flood-diversion and capacity-expansion schemes can be obtained under four scenarios, which enable decision makers (DMs) to identify the most desired one based on their perceptions and attitudes towards the objective-function value and constraints. Copyright © 2013 Elsevier Ltd. All rights reserved.

Non-Born-Oppenheimer Spectroscopy of Cyclic Triatomics

DTIC Science & Technology

2011-10-11

n nmnm mn m nm nm nm nm ss n IV E 2/ if,2/1 2/ if, ])2/1()/[( )2/1()/( 2 1 12 22 222 22 2/,,4 23 )3(   Here ZPE ...integer values of m . The perturbation theory expression gives us seven parameters for a non-linear fitting problem: ZPE , 0I , 1I , 2I , 3V , 6V and

Solving Fuzzy Fractional Differential Equations Using Zadeh's Extension Principle

PubMed Central

Ahmad, M. Z.; Hasan, M. K.; Abbasbandy, S.

2013-01-01

We study a fuzzy fractional differential equation (FFDE) and present its solution using Zadeh's extension principle. The proposed study extends the case of fuzzy differential equations of integer order. We also propose a numerical method to approximate the solution of FFDEs. To solve nonlinear problems, the proposed numerical method is then incorporated into an unconstrained optimisation technique. Several numerical examples are provided. PMID:24082853

A Comparison of the DISASTER (Trademark) Scheduling Software with a Simultaneous Scheduling Algorithm for Minimizing Maximum Tardiness in Job Shops

DTIC Science & Technology

1993-09-01

goal ( Heizer , Render , and Stair, 1993:94). Integer Prgronmming. Integer programming is a general purpose approach used to optimally solve job shop...Scheduling," Operations Research Journal. 29, No 4: 646-667 (July-August 1981). Heizer , Jay, Barry Render and Ralph M. Stair, Jr. Production and Operations

An integer programming model to optimize resource allocation for wildfire containment.

Treesearch

Geoffrey H. Donovan; Douglas B. Rideout

2003-01-01

Determining the specific mix of fire-fighting resources for a given fire is a necessary condition for identifying the minimum of the Cost Plus Net Value Change (C+NVC) function. Current wildland fire management models may not reliably do so. The problem of identifying the most efficient wildland fire organization is characterized mathematically using integer-...

RSM 1.0 - A RESUPPLY SCHEDULER USING INTEGER OPTIMIZATION

NASA Technical Reports Server (NTRS)

Viterna, L. A.

1994-01-01

RSM, Resupply Scheduling Modeler, is a fully menu-driven program that uses integer programming techniques to determine an optimum schedule for replacing components on or before the end of a fixed replacement period. Although written to analyze the electrical power system on the Space Station Freedom, RSM is quite general and can be used to model the resupply of almost any system subject to user-defined resource constraints. RSM is based on a specific form of the general linear programming problem in which all variables in the objective function and all variables in the constraints are integers. While more computationally intensive, integer programming was required for accuracy when modeling systems with small quantities of components. Input values for component life cane be real numbers, RSM converts them to integers by dividing the lifetime by the period duration, then reducing the result to the next lowest integer. For each component, there is a set of constraints that insure that it is replaced before its lifetime expires. RSM includes user-defined constraints such as transportation mass and volume limits, as well as component life, available repair crew time and assembly sequences. A weighting factor allows the program to minimize factors such as cost. The program then performs an iterative analysis, which is displayed during the processing. A message gives the first period in which resources are being exceeded on each iteration. If the scheduling problem is unfeasible, the final message will also indicate the first period in which resources were exceeded. RSM is written in APL2 for IBM PC series computers and compatibles. A stand-alone executable version of RSM is provided; however, this is a "packed" version of RSM which can only utilize the memory within the 640K DOS limit. This executable requires at least 640K of memory and DOS 3.1 or higher. Source code for an APL2/PC workspace version is also provided. This version of RSM can make full use of any installed extended memory but must be run with the APL2 interpreter; and it requires an 80486 based microcomputer or an 80386 based microcomputer with an 80387 math coprocessor, at least 2Mb of extended memory, and DOS 3.3 or higher. The standard distribution medium for this package is one 5.25 inch 360K MS-DOS format diskette. RSM was developed in 1991. APL2 and IBM PC are registered trademarks of International Business Machines Corporation. MS-DOS is a registered trademark of Microsoft Corporation.

Waste management under multiple complexities: Inexact piecewise-linearization-based fuzzy flexible programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun Wei; Huang, Guo H., E-mail: huang@iseis.org; Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan, S4S 0A2

2012-06-15

Highlights: Black-Right-Pointing-Pointer Inexact piecewise-linearization-based fuzzy flexible programming is proposed. Black-Right-Pointing-Pointer It's the first application to waste management under multiple complexities. Black-Right-Pointing-Pointer It tackles nonlinear economies-of-scale effects in interval-parameter constraints. Black-Right-Pointing-Pointer It estimates costs more accurately than the linear-regression-based model. Black-Right-Pointing-Pointer Uncertainties are decreased and more satisfactory interval solutions are obtained. - Abstract: To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerancemore » intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP's advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP's solutions demonstrate its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities.« less

A generalized interval fuzzy mixed integer programming model for a multimodal transportation problem under uncertainty

NASA Astrophysics Data System (ADS)

Tian, Wenli; Cao, Chengxuan

2017-03-01

A generalized interval fuzzy mixed integer programming model is proposed for the multimodal freight transportation problem under uncertainty, in which the optimal mode of transport and the optimal amount of each type of freight transported through each path need to be decided. For practical purposes, three mathematical methods, i.e. the interval ranking method, fuzzy linear programming method and linear weighted summation method, are applied to obtain equivalents of constraints and parameters, and then a fuzzy expected value model is presented. A heuristic algorithm based on a greedy criterion and the linear relaxation algorithm are designed to solve the model.

Coordinative Voltage Control Strategy with Multiple Resources for Distribution Systems of High PV Penetration: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Xiangqi; Zhang, Yingchen

This paper presents an optimal voltage control methodology with coordination among different voltage-regulating resources, including controllable loads, distributed energy resources such as energy storage and photovoltaics (PV), and utility voltage-regulating devices such as voltage regulators and capacitors. The proposed methodology could effectively tackle the overvoltage and voltage regulation device distortion problems brought by high penetrations of PV to improve grid operation reliability. A voltage-load sensitivity matrix and voltage-regulator sensitivity matrix are used to deploy the resources along the feeder to achieve the control objectives. Mixed-integer nonlinear programming is used to solve the formulated optimization control problem. The methodology has beenmore » tested on the IEEE 123-feeder test system, and the results demonstrate that the proposed approach could actively tackle the voltage problem brought about by high penetrations of PV and improve the reliability of distribution system operation.« less

Integrated optimization of planetary rover layout and exploration routes

NASA Astrophysics Data System (ADS)

Lee, Dongoo; Ahn, Jaemyung

2018-01-01

This article introduces an optimization framework for the integrated design of a planetary surface rover and its exploration route that is applicable to the initial phase of a planetary exploration campaign composed of multiple surface missions. The scientific capability and the mobility of a rover are modelled as functions of the science weight fraction, a key parameter characterizing the rover. The proposed problem is formulated as a mixed-integer nonlinear program that maximizes the sum of profits obtained through a planetary surface exploration mission by simultaneously determining the science weight fraction of the rover, the sites to visit and their visiting sequences under resource consumption constraints imposed on each route and collectively on a mission. A solution procedure for the proposed problem composed of two loops (the outer loop and the inner loop) is developed. The results of test cases demonstrating the effectiveness of the proposed framework are presented.

MIDACO on MINLP space applications

NASA Astrophysics Data System (ADS)

Schlueter, Martin; Erb, Sven O.; Gerdts, Matthias; Kemble, Stephen; Rückmann, Jan-J.

2013-04-01

A numerical study on two challenging mixed-integer non-linear programming (MINLP) space applications and their optimization with MIDACO, a recently developed general purpose optimization software, is presented. These applications are the optimal control of the ascent of a multiple-stage space launch vehicle and the space mission trajectory design from Earth to Jupiter using multiple gravity assists. Additionally, an NLP aerospace application, the optimal control of an F8 aircraft manoeuvre, is discussed and solved. In order to enhance the optimization performance of MIDACO a hybridization technique, coupling MIDACO with an SQP algorithm, is presented for two of these three applications. The numerical results show, that the applications can be solved to their best known solution (or even new best solution) in a reasonable time by the considered approach. Since using the concept of MINLP is still a novelty in the field of (aero)space engineering, the demonstrated capabilities are seen as very promising.

Hybridization with a twist: Hidden (hastatic) order in URu2Si2

NASA Astrophysics Data System (ADS)

Flint, Rebecca

The hidden order developing below 17.5K in the heavy fermion material URu2Si2 has eluded identification for over thirty years. A number of recent experiments have shed new light on the nature of this phase. In particular, de Haas-van Alphen measurements indicate nearly perfectly Ising quasiparticles deep in the hidden order phase, and recent nonlinear susceptibility measurements show that this strong Ising anisotropy persists up to and above the hidden order transition itself. Along with other features, this Ising anisotropy implies that the conduction electrons hybridize with a local Ising moment - a 5f2 state of the uranium atom with integer spin. As the hybridization mixes states of integer and half-integer spin, it is itself a spinor and this ``hastatic'' (hasta: [Latin] spear) order parameter therefore breaks both time-reversal and double time-reversal symmetries. A microscopic theory of hastatic order naturally unites a number of disparate experimental results from the large entropy of condensation to the spin rotational symmetry breaking seen in torque magnetometry, and provides a number of experimental predictions. Moreover, this new spinorial order parameter provides a window into a number of new heavy fermion phases.

A Mixed-Integer Linear Programming Problem which is Efficiently Solvable.

DTIC Science & Technology

1987-10-01

INTEGER LINEAR PROGRAMMING PROBLEM WHICH IS EFFICIENTLY SOLVABLE 12. PERSONAL AUTHOR(S) Leiserson, Charles, and Saxe, James B. 13a. TYPE OF REPORT j13b TIME...ger prongramn rg versions or the problem is not ac’hievable in genieral for sparse inistancves of’ P rolem(r Mi. Th le remrai nder or thris paper is...rClazes c:oIh edge (i,I*) by comlpli urg +- rnirr(z 3, ,x + a,j). A sirnI) le analysis (11 vto Nei [131 indicates why whe Iellinan-Ford algorithm works

Development of a Menu Driven Materials Data Base for Use on Personal Computers

DTIC Science & Technology

1992-07-01

written permission. Copyright Is the responsibility of the Director Publishing and Marketing , AGPS. Enquiries should be directed to the Manager, AGPS...PROGRAM LISTING A-2-1 Program MOB; uses crt; label levell,level2,level3,shutdown,dis;play; var options,code, nlines ,nmeflitemp,i,j4,k :integer; w,chl,ch2,ch3...char; menus :array [I. .1001 of st~ring[801; nline :array [l. .100] of integer; s2 :string[21; control :string[4]; aline :string[801; inm,iflt :text

A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities

DOE PAGES

Liu, Jianfeng; Laird, Carl Damon

2017-09-22

Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem thatmore » requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.« less

A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Jianfeng; Laird, Carl Damon

Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem thatmore » requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.« less

Autonomous and driven dynamics of spin torque nano-oscillators

NASA Astrophysics Data System (ADS)

Urazhdin, Sergei

2012-02-01

Understanding the dynamical properties of autonomous spin torque nano-oscillators (STNO) and their response to external perturbations is important for their applications as nanoscale microwave sources. We used spectroscopic measurements to study the dynamical characteristics of nanopillar- and point contact-based STNOs incorporating a microstrip in close proximity to the active magnetic layer. By applying microwave current at frequency fext to the microstrip, we were able to generate large microwave fields of more than 30 Oe rms at the location of STNO. We demonstrate that for a wide range of fext, STNO exhibits multiple synchronization regimes with integer and non-integer rational ratios between fext and the oscillation frequency f. We show that the synchronization ranges are determined by the symmetry of the oscillation orbit and the orientation of the driving field relative to the symmetry axis of the orbit. We observe synchronization hysteresis, i.e. a dependence of the synchronization limits on the dynamical history caused by the nonlinearity of STNO. We also show that the oscillation can be parametrically excited in the subcritical regime of STNO by a microwave field at twice the frequency of the oscillation. By measuring the threshold and the frequency range of parametric excitation, we determine damping, spin-polarization efficiency, and coupling to the microwave signal. In addition, by measuring the frequency range of parametric synchronization in the auto-oscillation regime, we determine the dynamic nonlinearity of the nanomagnet. Thus, analysis of the driven oscillations provides complete information about the dynamical characteristics of STNO. Finally, we discuss several unusual dynamical behaviors of STNO caused by their strong nonlinearity.

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

NASA Astrophysics Data System (ADS)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

Split diversity in constrained conservation prioritization using integer linear programming.

PubMed

Chernomor, Olga; Minh, Bui Quang; Forest, Félix; Klaere, Steffen; Ingram, Travis; Henzinger, Monika; von Haeseler, Arndt

2015-01-01

Phylogenetic diversity (PD) is a measure of biodiversity based on the evolutionary history of species. Here, we discuss several optimization problems related to the use of PD, and the more general measure split diversity (SD), in conservation prioritization.Depending on the conservation goal and the information available about species, one can construct optimization routines that incorporate various conservation constraints. We demonstrate how this information can be used to select sets of species for conservation action. Specifically, we discuss the use of species' geographic distributions, the choice of candidates under economic pressure, and the use of predator-prey interactions between the species in a community to define viability constraints.Despite such optimization problems falling into the area of NP hard problems, it is possible to solve them in a reasonable amount of time using integer programming. We apply integer linear programming to a variety of models for conservation prioritization that incorporate the SD measure.We exemplarily show the results for two data sets: the Cape region of South Africa and a Caribbean coral reef community. Finally, we provide user-friendly software at http://www.cibiv.at/software/pda.

Rarity-weighted richness: a simple and reliable alternative to integer programming and heuristic algorithms for minimum set and maximum coverage problems in conservation planning.

PubMed

Albuquerque, Fabio; Beier, Paul

2015-01-01

Here we report that prioritizing sites in order of rarity-weighted richness (RWR) is a simple, reliable way to identify sites that represent all species in the fewest number of sites (minimum set problem) or to identify sites that represent the largest number of species within a given number of sites (maximum coverage problem). We compared the number of species represented in sites prioritized by RWR to numbers of species represented in sites prioritized by the Zonation software package for 11 datasets in which the size of individual planning units (sites) ranged from <1 ha to 2,500 km2. On average, RWR solutions were more efficient than Zonation solutions. Integer programming remains the only guaranteed way find an optimal solution, and heuristic algorithms remain superior for conservation prioritizations that consider compactness and multiple near-optimal solutions in addition to species representation. But because RWR can be implemented easily and quickly in R or a spreadsheet, it is an attractive alternative to integer programming or heuristic algorithms in some conservation prioritization contexts.

Integer programming for improving radiotherapy treatment efficiency.

PubMed

Lv, Ming; Li, Yi; Kou, Bo; Zhou, Zhili

2017-01-01

Patients received by radiotherapy departments are diverse and may be diagnosed with different cancers. Therefore, they need different radiotherapy treatment plans and thus have different needs for medical resources. This research aims to explore the best method of scheduling the admission of patients receiving radiotherapy so as to reduce patient loss and maximize the usage efficiency of service resources. A mix integer programming (MIP) model integrated with special features of radiotherapy is constructed. The data used here is based on the historical data collected and we propose an exact method to solve the MIP model. Compared with the traditional First Come First Served (FCFS) method, the new method has boosted patient admission as well as the usage of linear accelerators (LINAC) and beds. The integer programming model can be used to describe the complex problem of scheduling radio-receiving patients, to identify the bottleneck resources that hinder patient admission, and to obtain the optimal LINAC-bed radio under the current data conditions. Different management strategies can be implemented by adjusting the settings of the MIP model. The computational results can serve as a reference for the policy-makers in decision making.

Mixed Integer Linear Programming model for Crude Palm Oil Supply Chain Planning

NASA Astrophysics Data System (ADS)

Sembiring, Pasukat; Mawengkang, Herman; Sadyadharma, Hendaru; Bu'ulolo, F.; Fajriana

2018-01-01

The production process of crude palm oil (CPO) can be defined as the milling process of raw materials, called fresh fruit bunch (FFB) into end products palm oil. The process usually through a series of steps producing and consuming intermediate products. The CPO milling industry considered in this paper does not have oil palm plantation, therefore the FFB are supplied by several public oil palm plantations. Due to the limited availability of FFB, then it is necessary to choose from which plantations would be appropriate. This paper proposes a mixed integer linear programming model the supply chain integrated problem, which include waste processing. The mathematical programming model is solved using neighborhood search approach.

A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing

NASA Technical Reports Server (NTRS)

Takaki, Mitsuo; Cavalcanti, Diego; Gheyi, Rohit; Iyoda, Juliano; dAmorim, Marcelo; Prudencio, Ricardo

2009-01-01

The complexity of constraints is a major obstacle for constraint-based software verification. Automatic constraint solvers are fundamentally incomplete: input constraints often build on some undecidable theory or some theory the solver does not support. This paper proposes and evaluates several randomized solvers to address this issue. We compare the effectiveness of a symbolic solver (CVC3), a random solver, three hybrid solvers (i.e., mix of random and symbolic), and two heuristic search solvers. We evaluate the solvers on two benchmarks: one consisting of manually generated constraints and another generated with a concolic execution of 8 subjects. In addition to fully decidable constraints, the benchmarks include constraints with non-linear integer arithmetic, integer modulo and division, bitwise arithmetic, and floating-point arithmetic. As expected symbolic solving (in particular, CVC3) subsumes the other solvers for the concolic execution of subjects that only generate decidable constraints. For the remaining subjects the solvers are complementary.

The Ablowitz–Ladik system on a finite set of integers

NASA Astrophysics Data System (ADS)

Xia, Baoqiang

2018-07-01

We show how to solve initial-boundary value problems for integrable nonlinear differential–difference equations on a finite set of integers. The method we employ is the discrete analogue of the unified transform (Fokas method). The implementation of this method to the Ablowitz–Ladik system yields the solution in terms of the unique solution of a matrix Riemann–Hilbert problem, which has a jump matrix with explicit -dependence involving certain functions referred to as spectral functions. Some of these functions are defined in terms of the initial value, while the remaining spectral functions are defined in terms of two sets of boundary values. These spectral functions are not independent but satisfy an algebraic relation called global relation. We analyze the global relation to characterize the unknown boundary values in terms of the given initial and boundary values. We also discuss the linearizable boundary conditions.

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

DOE PAGES

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

2016-11-27

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

An Integer Programming Model for the Management of a Forest in the North of Portugal

NASA Astrophysics Data System (ADS)

Cerveira, Adelaide; Fonseca, Teresa; Mota, Artur; Martins, Isabel

2011-09-01

This study aims to develop an approach for the management of a forest of maritime pine located in the north region of Portugal. The forest is classified into five public lands, the so-called baldios, extending over 4432 ha. These baldios are co-managed by the Official Forest Services and the local communities mainly for timber production purposes. The forest planning involves non-spatial and spatial constraints. Spatial constraints dictate a maximum clearcut area and an exclusion time. An integer programming model is presented and the computational results are discussed.

Nonlinear viscoelastic characterization of human vocal fold tissues under large-amplitude oscillatory shear (LAOS)

PubMed Central

Chan, Roger W.

2018-01-01

Viscoelastic shear properties of human vocal fold tissues were previously quantified by the shear moduli (G′ and G″). Yet these small-strain linear measures were unable to describe any nonlinear tissue behavior. This study attempted to characterize the nonlinear viscoelastic response of the vocal fold lamina propria under large-amplitude oscillatory shear (LAOS) with a stress decomposition approach. Human vocal fold cover and vocal ligament specimens from eight subjects were subjected to LAOS rheometric testing with a simple-shear rheometer. The empirical total stress response was decomposed into elastic and viscous stress components, based on odd-integer harmonic decomposition approach with Fourier transform. Nonlinear viscoelastic measures derived from the decomposition were plotted in Pipkin space and as rheological fingerprints to observe the onset of nonlinearity and the type of nonlinear behavior. Results showed that both the vocal fold cover and the vocal ligament experienced intercycle strain softening, intracycle strain stiffening, as well as shear thinning both intercycle and intracycle. The vocal ligament appeared to demonstrate an earlier onset of nonlinearity at phonatory frequencies, and higher sensitivity to changes in frequency and strain. In summary, the stress decomposition approach provided much better insights into the nonlinear viscoelastic behavior of the vocal fold lamina propria than the traditional linear measures. PMID:29780189

Nonlinear viscoelastic characterization of human vocal fold tissues under large-amplitude oscillatory shear (LAOS).

PubMed

Chan, Roger W

2018-05-01

Viscoelastic shear properties of human vocal fold tissues were previously quantified by the shear moduli ( G' and G″ ). Yet these small-strain linear measures were unable to describe any nonlinear tissue behavior. This study attempted to characterize the nonlinear viscoelastic response of the vocal fold lamina propria under large-amplitude oscillatory shear (LAOS) with a stress decomposition approach. Human vocal fold cover and vocal ligament specimens from eight subjects were subjected to LAOS rheometric testing with a simple-shear rheometer. The empirical total stress response was decomposed into elastic and viscous stress components, based on odd-integer harmonic decomposition approach with Fourier transform. Nonlinear viscoelastic measures derived from the decomposition were plotted in Pipkin space and as rheological fingerprints to observe the onset of nonlinearity and the type of nonlinear behavior. Results showed that both the vocal fold cover and the vocal ligament experienced intercycle strain softening, intracycle strain stiffening, as well as shear thinning both intercycle and intracycle. The vocal ligament appeared to demonstrate an earlier onset of nonlinearity at phonatory frequencies, and higher sensitivity to changes in frequency and strain. In summary, the stress decomposition approach provided much better insights into the nonlinear viscoelastic behavior of the vocal fold lamina propria than the traditional linear measures.

Existence and uniqueness theorems for impulsive fractional differential equations with the two-point and integral boundary conditions.

PubMed

Mardanov, M J; Mahmudov, N I; Sharifov, Y A

2014-01-01

We study a boundary value problem for the system of nonlinear impulsive fractional differential equations of order α (0 < α ≤ 1) involving the two-point and integral boundary conditions. Some new results on existence and uniqueness of a solution are established by using fixed point theorems. Some illustrative examples are also presented. We extend previous results even in the integer case α = 1.

A Mixed Integer Efficient Global Optimization Framework: Applied to the Simultaneous Aircraft Design, Airline Allocation and Revenue Management Problem

NASA Astrophysics Data System (ADS)

Roy, Satadru

Traditional approaches to design and optimize a new system, often, use a system-centric objective and do not take into consideration how the operator will use this new system alongside of other existing systems. This "hand-off" between the design of the new system and how the new system operates alongside other systems might lead to a sub-optimal performance with respect to the operator-level objective. In other words, the system that is optimal for its system-level objective might not be best for the system-of-systems level objective of the operator. Among the few available references that describe attempts to address this hand-off, most follow an MDO-motivated subspace decomposition approach of first designing a very good system and then provide this system to the operator who decides the best way to use this new system along with the existing systems. The motivating example in this dissertation presents one such similar problem that includes aircraft design, airline operations and revenue management "subspaces". The research here develops an approach that could simultaneously solve these subspaces posed as a monolithic optimization problem. The monolithic approach makes the problem a Mixed Integer/Discrete Non-Linear Programming (MINLP/MDNLP) problem, which are extremely difficult to solve. The presence of expensive, sophisticated engineering analyses further aggravate the problem. To tackle this challenge problem, the work here presents a new optimization framework that simultaneously solves the subspaces to capture the "synergism" in the problem that the previous decomposition approaches may not have exploited, addresses mixed-integer/discrete type design variables in an efficient manner, and accounts for computationally expensive analysis tools. The framework combines concepts from efficient global optimization, Kriging partial least squares, and gradient-based optimization. This approach then demonstrates its ability to solve an 11 route airline network problem consisting of 94 decision variables including 33 integer and 61 continuous type variables. This application problem is a representation of an interacting group of systems and provides key challenges to the optimization framework to solve the MINLP problem, as reflected by the presence of a moderate number of integer and continuous type design variables and expensive analysis tool. The result indicates simultaneously solving the subspaces could lead to significant improvement in the fleet-level objective of the airline when compared to the previously developed sequential subspace decomposition approach. In developing the approach to solve the MINLP/MDNLP challenge problem, several test problems provided the ability to explore performance of the framework. While solving these test problems, the framework showed that it could solve other MDNLP problems including categorically discrete variables, indicating that the framework could have broader application than the new aircraft design-fleet allocation-revenue management problem.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burchett, Deon L.; Chen, Richard Li-Yang; Phillips, Cynthia A.

This report summarizes the work performed under the project project Next-Generation Algo- rithms for Assessing Infrastructure Vulnerability and Optimizing System Resilience. The goal of the project was to improve mathematical programming-based optimization technology for in- frastructure protection. In general, the owner of a network wishes to design a network a network that can perform well when certain transportation channels are inhibited (e.g. destroyed) by an adversary. These are typically bi-level problems where the owner designs a system, an adversary optimally attacks it, and then the owner can recover by optimally using the remaining network. This project funded three years ofmore » Deon Burchett's graduate research. Deon's graduate advisor, Professor Jean-Philippe Richard, and his Sandia advisors, Richard Chen and Cynthia Phillips, supported Deon on other funds or volunteer time. This report is, therefore. essentially a replication of the Ph.D. dissertation it funded [12] in a format required for project documentation. The thesis had some general polyhedral research. This is the study of the structure of the feasi- ble region of mathematical programs, such as integer programs. For example, an integer program optimizes a linear objective function subject to linear constraints, and (nonlinear) integrality con- straints on the variables. The feasible region without the integrality constraints is a convex polygon. Careful study of additional valid constraints can significantly improve computational performance. Here is the abstract from the dissertation: We perform a polyhedral study of a multi-commodity generalization of variable upper bound flow models. In particular, we establish some relations between facets of single- and multi- commodity models. We then introduce a new family of inequalities, which generalizes traditional flow cover inequalities to the multi-commodity context. We present encouraging numerical results. We also consider the directed edge-failure resilient network design problem (DRNDP). This problem entails the design of a directed multi-commodity flow network that is capable of fulfilling a specified percentage of demands in the event that any G arcs are destroyed, where G is a constant parameter. We present a formulation of DRNDP and solve it in a branch-column-cut framework. We present computational results.« less

Solving the water jugs problem by an integer sequence approach

NASA Astrophysics Data System (ADS)

Man, Yiu-Kwong

2012-01-01

In this article, we present an integer sequence approach to solve the classic water jugs problem. The solution steps can be obtained easily by additions and subtractions only, which is suitable for manual calculation or programming by computer. This approach can be introduced to secondary and undergraduate students, and also to teachers and lecturers involved in teaching mathematical problem solving, recreational mathematics, or elementary number theory.

New Approaches for Very Large-Scale Integer Programming

DTIC Science & Technology

2016-06-24

existing algorithms. This research has been presented at several conferences and has and will appear in archival journals. 15. SUBJECT TERMS integer...This research has been presented at several conferences and has and will appear in archival journals. Distribution Statement This is block 12 on the...pdf Upload a Report Document, if any. The maximum file size for the Report Document is 50MB. Archival Publications (published) during reporting

Khater method for nonlinear Sharma Tasso-Olever (STO) equation of fractional order

NASA Astrophysics Data System (ADS)

Bibi, Sadaf; Mohyud-Din, Syed Tauseef; Khan, Umar; Ahmed, Naveed

In this work, we have implemented a direct method, known as Khater method to establish exact solutions of nonlinear partial differential equations of fractional order. Number of solutions provided by this method is greater than other traditional methods. Exact solutions of nonlinear fractional order Sharma Tasso-Olever (STO) equation are expressed in terms of kink, travelling wave, periodic and solitary wave solutions. Modified Riemann-Liouville derivative and Fractional complex transform have been used for compatibility with fractional order sense. Solutions have been graphically simulated for understanding the physical aspects and importance of the method. A comparative discussion between our established results and the results obtained by existing ones is also presented. Our results clearly reveal that the proposed method is an effective, powerful and straightforward technique to work out new solutions of various types of differential equations of non-integer order in the fields of applied sciences and engineering.

Energy and Transmissibility in Nonlinear Viscous Base Isolators

NASA Astrophysics Data System (ADS)

Markou, Athanasios A.; Manolis, George D.

2016-09-01

High damping rubber bearings (HDRB) are the most commonly used base isolators in buildings and are often combined with other systems, such as sliding bearings. Their mechanical behaviour is highly nonlinear and dependent on a number of factors. At first, a physical process is suggested here to explain the empirical formula introduced by J.M. Kelly in 1991, where the dissipated energy of a HDRB under cyclic testing, at constant frequency, is proportional to the amplitude of the shear strain, raised to a power of approximately 1.50. This physical process is best described by non-Newtonian fluid behaviour, originally developed by F.H. Norton in 1929 to describe creep in steel at high-temperatures. The constitutive model used includes a viscous term, that depends on the absolute value of the velocity, raised to a non-integer power. The identification of a three parameter Kelvin model, the simplest possible system with nonlinear viscosity, is also suggested here. Furthermore, a more advanced model with variable damping coefficient is implemented to better model in this complex mechanical process. Next, the assumption of strain-rate dependence in their rubber layers under cyclic loading is examined in order to best interpret experimental results on the transmission of motion between the upper and lower surfaces of HDRB. More specifically, the stress-relaxation phenomenon observed with time in HRDB can be reproduced numerically, only if the constitutive model includes a viscous term, that depends on the absolute value of the velocity raised to a non-integer power, i. e., the Norton fluid previously mentioned. Thus, it becomes possible to compute the displacement transmissibility function between the top and bottom surfaces of HDRB base isolator systems and to draw engineering-type conclusions, relevant to their design under time-harmonic loads.

Exploring 4D quantum Hall physics with a 2D topological charge pump

NASA Astrophysics Data System (ADS)

Lohse, Michael; Schweizer, Christian; Price, Hannah M.; Zilberberg, Oded; Bloch, Immanuel

2018-01-01

The discovery of topological states of matter has greatly improved our understanding of phase transitions in physical systems. Instead of being described by local order parameters, topological phases are described by global topological invariants and are therefore robust against perturbations. A prominent example is the two-dimensional (2D) integer quantum Hall effect: it is characterized by the first Chern number, which manifests in the quantized Hall response that is induced by an external electric field. Generalizing the quantum Hall effect to four-dimensional (4D) systems leads to the appearance of an additional quantized Hall response, but one that is nonlinear and described by a 4D topological invariant—the second Chern number. Here we report the observation of a bulk response with intrinsic 4D topology and demonstrate its quantization by measuring the associated second Chern number. By implementing a 2D topological charge pump using ultracold bosonic atoms in an angled optical superlattice, we realize a dynamical version of the 4D integer quantum Hall effect. Using a small cloud of atoms as a local probe, we fully characterize the nonlinear response of the system via in situ imaging and site-resolved band mapping. Our findings pave the way to experimentally probing higher-dimensional quantum Hall systems, in which additional strongly correlated topological phases, exotic collective excitations and boundary phenomena such as isolated Weyl fermions are predicted.

Exploring 4D quantum Hall physics with a 2D topological charge pump.

PubMed

Lohse, Michael; Schweizer, Christian; Price, Hannah M; Zilberberg, Oded; Bloch, Immanuel

2018-01-03

The discovery of topological states of matter has greatly improved our understanding of phase transitions in physical systems. Instead of being described by local order parameters, topological phases are described by global topological invariants and are therefore robust against perturbations. A prominent example is the two-dimensional (2D) integer quantum Hall effect: it is characterized by the first Chern number, which manifests in the quantized Hall response that is induced by an external electric field. Generalizing the quantum Hall effect to four-dimensional (4D) systems leads to the appearance of an additional quantized Hall response, but one that is nonlinear and described by a 4D topological invariant-the second Chern number. Here we report the observation of a bulk response with intrinsic 4D topology and demonstrate its quantization by measuring the associated second Chern number. By implementing a 2D topological charge pump using ultracold bosonic atoms in an angled optical superlattice, we realize a dynamical version of the 4D integer quantum Hall effect. Using a small cloud of atoms as a local probe, we fully characterize the nonlinear response of the system via in situ imaging and site-resolved band mapping. Our findings pave the way to experimentally probing higher-dimensional quantum Hall systems, in which additional strongly correlated topological phases, exotic collective excitations and boundary phenomena such as isolated Weyl fermions are predicted.

Integer programming of cement distribution by train

NASA Astrophysics Data System (ADS)

Indarsih

2018-01-01

Cement industry in Central Java distributes cement by train to meet daily demand in Yogyakarta and Central Java area. There are five destination stations. For each destination station, there is a warehouse to load cements. Decision maker of cement industry have a plan to redesign the infrastructure and transportation system. The aim is to determine how many locomotives, train wagons, and containers and how to arrange train schedules with subject to the delivery time. For this purposes, we consider an integer programming to minimize the total of operational cost. Further, we will discuss a case study and the solution the problem can be calculated by LINGO software.

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

DOE PAGES

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

2016-04-02

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

An integer programming model for distal humerus fracture fixation planning.

PubMed

Maratt, Joseph D; Peaks, Ya-Sin A; Doro, Lisa Case; Karunakar, Madhav A; Hughes, Richard E

2008-05-01

To demonstrate the feasibility of an integer programming model to assist in pre-operative planning for open reduction and internal fixation of a distal humerus fracture. We describe an integer programming model based on the objective of maximizing the reward for screws placed while satisfying the requirements for sound internal fixation. The model maximizes the number of bicortical screws placed while avoiding screw collision and favoring screws of greater length that cross multiple fracture planes. The model was tested on three types of total articular fractures of the distal humerus. Solutions were generated using 5, 9, 21 and 33 possible screw orientations per hole. Solutions generated using 33 possible screw orientations per hole and five screw lengths resulted in the most clinically relevant fixation plan and required the calculation of 1,191,975 pairs of screws that resulted in collision. At this level of complexity, the pre-processor took 104 seconds to generate the constraints for the solver, and a solution was generated in under one minute in all three cases. Despite the large size of this problem, it can be solved in a reasonable amount of time, making use of the model practical in pre-surgical planning.

Mixed-Integer Conic Linear Programming: Challenges and Perspectives

DTIC Science & Technology

2013-10-01

The novel DCCs for MISOCO may be used in branch- and-cut algorithms when solving MISOCO problems. The experimental software CICLO was developed to...perform limited, but rigorous computational experiments. The CICLO solver utilizes continuous SOCO solvers, MOSEK, CPLES or SeDuMi, builds on the open...submitted Fall 2013. Software: 1. CICLO : Integer conic linear optimization package. Authors: J.C. Góez, T.K. Ralphs, Y. Fu, and T. Terlaky

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming.

PubMed

Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

2017-08-01

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs. The software is implemented in Matlab, and is provided as supplementary information . hyunseob.song@pnnl.gov. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.

Fuzzy multiobjective models for optimal operation of a hydropower system

NASA Astrophysics Data System (ADS)

Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.

2013-06-01

Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.

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

NASA Astrophysics Data System (ADS)

Sakakibara, Kazutoshi; Tian, Yajie; Nishikawa, Ikuko

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

Optimal design of zero-water discharge rinsing systems.

PubMed

Thöming, Jorg

2002-03-01

This paper is about zero liquid discharge in processes that use water for rinsing. Emphasis was given to those systems that contaminate process water with valuable process liquor and compounds. The approach involved the synthesis of optimal rinsing and recycling networks (RRN) that had a priori excluded water discharge. The total annualized costs of the RRN were minimized by the use of a mixed-integer nonlinear program (MINLP). This MINLP was based on a hyperstructure of the RRN and contained eight counterflow rinsing stages and three regenerator units: electrodialysis, reverse osmosis, and ion exchange columns. A "large-scale nickel plating process" case study showed that by means of zero-water discharge and optimized rinsing the total waste could be reduced by 90.4% at a revenue of $448,000/yr. Furthermore, with the optimized RRN, the rinsing performance can be improved significantly at a low-cost increase. In all the cases, the amount of valuable compounds reclaimed was above 99%.

A green vehicle routing problem with customer satisfaction criteria

NASA Astrophysics Data System (ADS)

Afshar-Bakeshloo, M.; Mehrabi, A.; Safari, H.; Maleki, M.; Jolai, F.

2016-12-01

This paper develops an MILP model, named Satisfactory-Green Vehicle Routing Problem. It consists of routing a heterogeneous fleet of vehicles in order to serve a set of customers within predefined time windows. In this model in addition to the traditional objective of the VRP, both the pollution and customers' satisfaction have been taken into account. Meanwhile, the introduced model prepares an effective dashboard for decision-makers that determines appropriate routes, the best mixed fleet, speed and idle time of vehicles. Additionally, some new factors evaluate the greening of each decision based on three criteria. This model applies piecewise linear functions (PLFs) to linearize a nonlinear fuzzy interval for incorporating customers' satisfaction into other linear objectives. We have presented a mixed integer linear programming formulation for the S-GVRP. This model enriches managerial insights by providing trade-offs between customers' satisfaction, total costs and emission levels. Finally, we have provided a numerical study for showing the applicability of the model.

Optimizing Constrained Single Period Problem under Random Fuzzy Demand

NASA Astrophysics Data System (ADS)

Taleizadeh, Ata Allah; Shavandi, Hassan; Riazi, Afshin

2008-09-01

In this paper, we consider the multi-product multi-constraint newsboy problem with random fuzzy demands and total discount. The demand of the products is often stochastic in the real word but the estimation of the parameters of distribution function may be done by fuzzy manner. So an appropriate option to modeling the demand of products is using the random fuzzy variable. The objective function of proposed model is to maximize the expected profit of newsboy. We consider the constraints such as warehouse space and restriction on quantity order for products, and restriction on budget. We also consider the batch size for products order. Finally we introduce a random fuzzy multi-product multi-constraint newsboy problem (RFM-PM-CNP) and it is changed to a multi-objective mixed integer nonlinear programming model. Furthermore, a hybrid intelligent algorithm based on genetic algorithm, Pareto and TOPSIS is presented for the developed model. Finally an illustrative example is presented to show the performance of the developed model and algorithm.

Design Considerations for Proposed Fermilab Integrable RCS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eldred, Jeffrey; Valishev, Alexander

2017-03-02

Integrable optics is an innovation in particle accelerator design that provides strong nonlinear focusing while avoiding parametric resonances. One promising application of integrable optics is to overcome the traditional limits on accelerator intensity imposed by betatron tune-spread and collective instabilities. The efficacy of high-intensity integrable accelerators will be undergo comprehensive testing over the next several years at the Fermilab Integrable Optics Test Accelerator (IOTA) and the University of Maryland Electron Ring (UMER). We propose an integrable Rapid-Cycling Synchrotron (iRCS) as a replacement for the Fermilab Booster to achieve multi-MW beam power for the Fermilab high-energy neutrino program. We provide amore » overview of the machine parameters and discuss an approach to lattice optimization. Integrable optics requires arcs with integer-pi phase advance followed by drifts with matched beta functions. We provide an example integrable lattice with features of a modern RCS - long dispersion-free drifts, low momentum compaction, superperiodicity, chromaticity correction, separate-function magnets, and bounded beta functions.« less

Online Appointment Scheduling for a Nuclear Medicine Department in a Chinese Hospital

PubMed Central

Feng, Ya-bing

2018-01-01

Nuclear medicine, a subspecialty of radiology, plays an important role in proper diagnosis and timely treatment. Multiple resources, especially short-lived radiopharmaceuticals involved in the process of nuclear medical examination, constitute a unique problem in appointment scheduling. Aiming at achieving scientific and reasonable appointment scheduling in the West China Hospital (WCH), a typical class A tertiary hospital in China, we developed an online appointment scheduling algorithm based on an offline nonlinear integer programming model which considers multiresources allocation, the time window constraints imposed by short-lived radiopharmaceuticals, and the stochastic nature of the patient requests when scheduling patients. A series of experiments are conducted to show the effectiveness of the proposed strategy based on data provided by the WCH. The results show that the examination amount increases by 29.76% compared with the current one with a significant increase in the resource utilization and timely rate. Besides, it also has a high stability for stochastic factors and bears the advantage of convenient and economic operation. PMID:29849748

Ubiquitous Multicriteria Clinic Recommendation System.

PubMed

Chen, Toly

2016-05-01

Advancements in information, communication, and sensor technologies have led to new opportunities in medical care and education. Patients in general prefer visiting the nearest clinic, attempt to avoid waiting for treatment, and have unequal preferences for different clinics and doctors. Therefore, to enable patients to compare multiple clinics, this study proposes a ubiquitous multicriteria clinic recommendation system. In this system, patients can send requests through their cell phones to the system server to obtain a clinic recommendation. Once the patient sends this information to the system, the system server first estimates the patient's speed according to the detection results of a global positioning system. It then applies a fuzzy integer nonlinear programming-ordered weighted average approach to assess four criteria and finally recommends a clinic with maximal utility to the patient. The proposed methodology was tested in a field experiment, and the experimental results showed that it is advantageous over two existing methods in elevating the utilities of recommendations. In addition, such an advantage was shown to be statistically significant.

Nonlinear resonances and antiresonances of a forced sonic vacuum

DOE PAGES

Pozharskiy, D.; Zhang, Y.; Williams, M. O.; ...

2015-12-23

We consider a harmonically driven acoustic medium in the form of a (finite length) highly nonlinear granular crystal with an amplitude- and frequency-dependent boundary drive. Despite the absence of a linear spectrum in the system, we identify resonant periodic propagation whereby the crystal responds at integer multiples of the drive period and observe that this can lead to local maxima of transmitted force at its fixed boundary. In addition, we identify and discuss minima of the transmitted force (“antiresonances”) between these resonances. Representative one-parameter complex bifurcation diagrams involve period doublings and Neimark-Sacker bifurcations as well as multiple isolas (e.g., ofmore » period-3, -4, or -5 solutions entrained by the forcing). We combine them in a more detailed, two-parameter bifurcation diagram describing the stability of such responses to both frequency and amplitude variations of the drive. This picture supports a notion of a (purely) “nonlinear spectrum” in a system which allows no sound wave propagation (due to zero sound speed: the so-called sonic vacuum). As a result, we rationalize this behavior in terms of purely nonlinear building blocks: apparent traveling and standing nonlinear waves.« less

Harmonic mixing characteristics of metal-barrier-metal junctions as predicted by electron tunneling

NASA Technical Reports Server (NTRS)

Faris, S. M.; Gustafson, T. K.

1974-01-01

The bias dependence of the nonlinear mixing characteristics of metal-barrier-metal junction currents is deduced assuming an electron tunneling model. The difference-frequency beat voltage at frequency omega sub 1 - (n x omega sub 2), when n is an integer and omega sub 1 and omega sub 2 are the assumed frequencies of two induced currents, is found to have n zeros as the diode bias is varied. Recent experimental observations have demonstrated such characteristics.

Swinging atwood machine. Far- and near-resonance region

NASA Astrophysics Data System (ADS)

Roy Chowdhury, A.; Debnath, M.

1988-11-01

The swinging Atwood machine, a prototype nonlinear dynamical system, is analyzed following an idea of Bogoliubov and Mitropolsky. A series solution is found for the radial and angular displacement as functions of time. The analysis is repeated in the resonance case, when the frequency of the driving force maintains a fixed ratio to that of the free motion. The condition of resonance requires the mass ratio μ to be equal to 2 j 2-1, where j is an integer not equal to one.

A chance-constrained stochastic approach to intermodal container routing problems.

PubMed

Zhao, Yi; Liu, Ronghui; Zhang, Xi; Whiteing, Anthony

2018-01-01

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost.

A chance-constrained stochastic approach to intermodal container routing problems

PubMed Central

Zhao, Yi; Zhang, Xi; Whiteing, Anthony

2018-01-01

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost. PMID:29438389

Edit distance for marked point processes revisited: An implementation by binary integer programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hirata, Yoshito; Aihara, Kazuyuki

2015-12-15

We implement the edit distance for marked point processes [Suzuki et al., Int. J. Bifurcation Chaos 20, 3699–3708 (2010)] as a binary integer program. Compared with the previous implementation using minimum cost perfect matching, the proposed implementation has two advantages: first, by using the proposed implementation, we can apply a wide variety of software and hardware, even spin glasses and coherent ising machines, to calculate the edit distance for marked point processes; second, the proposed implementation runs faster than the previous implementation when the difference between the numbers of events in two time windows for a marked point process ismore » large.« less

SSP: an interval integer linear programming for de novo transcriptome assembly and isoform discovery of RNA-seq reads.

PubMed

Safikhani, Zhaleh; Sadeghi, Mehdi; Pezeshk, Hamid; Eslahchi, Changiz

2013-01-01

Recent advances in the sequencing technologies have provided a handful of RNA-seq datasets for transcriptome analysis. However, reconstruction of full-length isoforms and estimation of the expression level of transcripts with a low cost are challenging tasks. We propose a novel de novo method named SSP that incorporates interval integer linear programming to resolve alternatively spliced isoforms and reconstruct the whole transcriptome from short reads. Experimental results show that SSP is fast and precise in determining different alternatively spliced isoforms along with the estimation of reconstructed transcript abundances. The SSP software package is available at http://www.bioinf.cs.ipm.ir/software/ssp. © 2013.

A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems.

PubMed

Abouelseoud, Gehan; Abouelseoud, Yasmine; Shoukry, Amin; Ismail, Nour; Mekky, Jaidaa

2018-02-01

Electrical stimulation optimization is a challenging problem. Even when a single region is targeted for excitation, the problem remains a constrained multi-objective optimization problem. The constrained nature of the problem results from safety concerns while its multi-objectives originate from the requirement that non-targeted regions should remain unaffected. In this paper, we propose a mixed integer linear programming formulation that can successfully address the challenges facing this problem. Moreover, the proposed framework can conclusively check the feasibility of the stimulation goals. This helps researchers to avoid wasting time trying to achieve goals that are impossible under a chosen stimulation setup. The superiority of the proposed framework over alternative methods is demonstrated through simulation examples.

Integer Linear Programming in Computational Biology

NASA Astrophysics Data System (ADS)

Althaus, Ernst; Klau, Gunnar W.; Kohlbacher, Oliver; Lenhof, Hans-Peter; Reinert, Knut

Computational molecular biology (bioinformatics) is a young research field that is rich in NP-hard optimization problems. The problem instances encountered are often huge and comprise thousands of variables. Since their introduction into the field of bioinformatics in 1997, integer linear programming (ILP) techniques have been successfully applied to many optimization problems. These approaches have added much momentum to development and progress in related areas. In particular, ILP-based approaches have become a standard optimization technique in bioinformatics. In this review, we present applications of ILP-based techniques developed by members and former members of Kurt Mehlhorn’s group. These techniques were introduced to bioinformatics in a series of papers and popularized by demonstration of their effectiveness and potential.

Integer programming applications: Bond trading, mortgage backed security financing, and FASB 115 accounting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nauss, R.

1994-12-31

In this review we describe three integer programming applications involving fixed income securities. A bond trading model is presented that features a number of possible different objectives and collections of constraints including future interest rate scenarios. A mortgage backed security (MBS) financing model that accounts for potential defaults in the MBS is also presented. Finally we describe an approach to allocate collections of bank securities into three categories: hold to maturity, available for sale, or trading. Placement of securities in these categories affects the capital, net income, and liquidity of a bank according to new accounting rules promulgated by themore » Financial Accounting Standards Board.« less

Hastatic order in URu2Si2 : Hybridization with a twist

NASA Astrophysics Data System (ADS)

Chandra, Premala; Coleman, Piers; Flint, Rebecca

2015-05-01

The broken symmetry that develops below 17.5 K in the heavy fermion compound URu2Si2 has long eluded identification. Here we argue that the recent observation of Ising quasiparticles in URu2Si2 results from a spinor hybridization order parameter that breaks double time-reversal symmetry by mixing states of integer and half-integer spin. Such "hastatic order" (hasta: [Latin] spear) hybridizes Kramers conduction electrons with Ising, non-Kramers 5 f2 states of the uranium atoms to produce Ising quasiparticles. The development of a spinorial hybridization at 17.5 K accounts for both the large entropy of condensation and the magnetic anomaly observed in torque magnetometry. This paper develops the theory of hastatic order in detail, providing the mathematical development of its key concepts. Hastatic order predicts a tiny transverse moment in the conduction sea, a colossal Ising anisotropy in the nonlinear susceptibility anomaly and a resonant energy-dependent nematicity in the tunneling density of states.

Intelligent Tutoring for Programming Tasks: Using Plan Analysis to Generate Better Hints.

DTIC Science & Technology

1982-03-01

construction and execution of a BASIC proqram that assiqns an integer value to a variable and then prints the value of that integer. - ARTICHOKE : assign...the string " ARTICHOKE " to a string variable, assiqn the value of that variable to a second variable, and print the second variable. -SINOP: qet two...the first five tasks: GREENFLAG, ARTICHOKE , SINOP, NINOP, and TWOS. Because the protocols are very lonq, it was necessary to condense them into a

Determining the Surface-to-Air Missile Requirement for Western and Southern Part of the Turkish Air Defense System

DTIC Science & Technology

2008-03-01

been shown to yield success in such applications as well. ( Daskin ,1995). LP optimization, matrix row reduction, a combination of both, or cutting...integer solution (Current, 2002). If the LP relaxation of the SCLP results in a fractional solution, Current, Daskin , and Schilling (2002) recommend...coverage for a given number of SAM sites. The model is formulated as an integer program, and the LINGO 10 software package is used to solve the model

Aerospace applications of integer and combinatorial optimization

NASA Technical Reports Server (NTRS)

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

1995-01-01

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.

Results of the Clarus Regional Demonstrations : Evaluation of Enhanced Road Weather Forecasting

DOT National Transportation Integrated Search

2012-01-01

The Clarus Initiative is a research effort of the U.S. Department of Transportation Intelligent Transportation Systems Joint Program Office and the Federal Highway Administrations Road Weather Management Program to develop and demonstrate an integ...

Determining on-fault earthquake magnitude distributions from integer programming

NASA Astrophysics Data System (ADS)

Geist, Eric L.; Parsons, Tom

2018-02-01

Earthquake magnitude distributions among faults within a fault system are determined from regional seismicity and fault slip rates using binary integer programming. A synthetic earthquake catalog (i.e., list of randomly sampled magnitudes) that spans millennia is first formed, assuming that regional seismicity follows a Gutenberg-Richter relation. Each earthquake in the synthetic catalog can occur on any fault and at any location. The objective is to minimize misfits in the target slip rate for each fault, where slip for each earthquake is scaled from its magnitude. The decision vector consists of binary variables indicating which locations are optimal among all possibilities. Uncertainty estimates in fault slip rates provide explicit upper and lower bounding constraints to the problem. An implicit constraint is that an earthquake can only be located on a fault if it is long enough to contain that earthquake. A general mixed-integer programming solver, consisting of a number of different algorithms, is used to determine the optimal decision vector. A case study is presented for the State of California, where a 4 kyr synthetic earthquake catalog is created and faults with slip ≥3 mm/yr are considered, resulting in >106 variables. The optimal magnitude distributions for each of the faults in the system span a rich diversity of shapes, ranging from characteristic to power-law distributions.

Operations research applications in nuclear energy

NASA Astrophysics Data System (ADS)

Johnson, Benjamin Lloyd

This dissertation consists of three papers; the first is published in Annals of Operations Research, the second is nearing submission to INFORMS Journal on Computing, and the third is the predecessor of a paper nearing submission to Progress in Nuclear Energy. We apply operations research techniques to nuclear waste disposal and nuclear safeguards. Although these fields are different, they allow us to showcase some benefits of using operations research techniques to enhance nuclear energy applications. The first paper, "Optimizing High-Level Nuclear Waste Disposal within a Deep Geologic Repository," presents a mixed-integer programming model that determines where to place high-level nuclear waste packages in a deep geologic repository to minimize heat load concentration. We develop a heuristic that increases the size of solvable model instances. The second paper, "Optimally Configuring a Measurement System to Detect Diversions from a Nuclear Fuel Cycle," introduces a simulation-optimization algorithm and an integer-programming model to find the best, or near-best, resource-limited nuclear fuel cycle measurement system with a high degree of confidence. Given location-dependent measurement method precisions, we (i) optimize the configuration of n methods at n locations of a hypothetical nuclear fuel cycle facility, (ii) find the most important location at which to improve method precision, and (iii) determine the effect of measurement frequency on near-optimal configurations and objective values. Our results correspond to existing outcomes but we obtain them at least an order of magnitude faster. The third paper, "Optimizing Nuclear Material Control and Accountability Measurement Systems," extends the integer program from the second paper to locate measurement methods in a larger, hypothetical nuclear fuel cycle scenario given fixed purchase and utilization budgets. This paper also presents two mixed-integer quadratic programming models to increase the precision of existing methods given a fixed improvement budget and to reduce the measurement uncertainty in the system while limiting improvement costs. We quickly obtain similar or better solutions compared to several intuitive analyses that take much longer to perform.

Investigating Integer Restrictions in Linear Programming

ERIC Educational Resources Information Center

Edwards, Thomas G.; Chelst, Kenneth R.; Principato, Angela M.; Wilhelm, Thad L.

2015-01-01

Linear programming (LP) is an application of graphing linear systems that appears in many Algebra 2 textbooks. Although not explicitly mentioned in the Common Core State Standards for Mathematics, linear programming blends seamlessly into modeling with mathematics, the fourth Standard for Mathematical Practice (CCSSI 2010, p. 7). In solving a…

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis version 6.0 theory manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adams, Brian M.; Ebeida, Mohamed Salah; Eldred, Michael S

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components requiredmore » for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quanti cation, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.« less

A multiobjective optimization framework for multicontaminant industrial water network design.

PubMed

Boix, Marianne; Montastruc, Ludovic; Pibouleau, Luc; Azzaro-Pantel, Catherine; Domenech, Serge

2011-07-01

The optimal design of multicontaminant industrial water networks according to several objectives is carried out in this paper. The general formulation of the water allocation problem (WAP) is given as a set of nonlinear equations with binary variables representing the presence of interconnections in the network. For optimization purposes, three antagonist objectives are considered: F(1), the freshwater flow-rate at the network entrance, F(2), the water flow-rate at inlet of regeneration units, and F(3), the number of interconnections in the network. The multiobjective problem is solved via a lexicographic strategy, where a mixed-integer nonlinear programming (MINLP) procedure is used at each step. The approach is illustrated by a numerical example taken from the literature involving five processes, one regeneration unit and three contaminants. The set of potential network solutions is provided in the form of a Pareto front. Finally, the strategy for choosing the best network solution among those given by Pareto fronts is presented. This Multiple Criteria Decision Making (MCDM) problem is tackled by means of two approaches: a classical TOPSIS analysis is first implemented and then an innovative strategy based on the global equivalent cost (GEC) in freshwater that turns out to be more efficient for choosing a good network according to a practical point of view. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Retrofit Puzzle Extended: Optimal Fleet Owner Behavior over Multiple Time Periods

DOT National Transportation Integrated Search

2009-08-04

In "The Retrofit Puzzle: Optimal Fleet Owner Behavior in the Context of Diesel Retrofit Incentive Programs" (1) an integer program was developed to model profit-maximizing diesel fleet owner behavior when selecting pollution reduction retrofits. Flee...

NEWTONP - CUMULATIVE BINOMIAL PROGRAMS

NASA Technical Reports Server (NTRS)

Bowerman, P. N.

1994-01-01

The cumulative binomial program, NEWTONP, is one of a set of three programs which calculate cumulative binomial probability distributions for arbitrary inputs. The three programs, NEWTONP, CUMBIN (NPO-17555), and CROSSER (NPO-17557), can be used independently of one another. NEWTONP can be used by statisticians and users of statistical procedures, test planners, designers, and numerical analysts. The program has been used for reliability/availability calculations. NEWTONP calculates the probably p required to yield a given system reliability V for a k-out-of-n system. It can also be used to determine the Clopper-Pearson confidence limits (either one-sided or two-sided) for the parameter p of a Bernoulli distribution. NEWTONP can determine Bayesian probability limits for a proportion (if the beta prior has positive integer parameters). It can determine the percentiles of incomplete beta distributions with positive integer parameters. It can also determine the percentiles of F distributions and the midian plotting positions in probability plotting. NEWTONP is designed to work well with all integer values 0 < k <= n. To run the program, the user simply runs the executable version and inputs the information requested by the program. NEWTONP is not designed to weed out incorrect inputs, so the user must take care to make sure the inputs are correct. Once all input has been entered, the program calculates and lists the result. It also lists the number of iterations of Newton's method required to calculate the answer within the given error. The NEWTONP program is written in C. It was developed on an IBM AT with a numeric co-processor using Microsoft C 5.0. Because the source code is written using standard C structures and functions, it should compile correctly with most C compilers. The program format is interactive. It has been implemented under DOS 3.2 and has a memory requirement of 26K. NEWTONP was developed in 1988.

HAL/S programmer's guide. [space shuttle flight software language

NASA Technical Reports Server (NTRS)

Newbold, P. M.; Hotz, R. L.

1974-01-01

HAL/S is a programming language developed to satisfy the flight software requirements for the space shuttle program. The user's guide explains pertinent language operating procedures and described the various HAL/S facilities for manipulating integer, scalar, vector, and matrix data types.

Are you ready? Managing transportation resources through the Y2K weekend

DOT National Transportation Integrated Search

2011-01-01

The Clarus Initiative, a joint effort of the U.S. Department of Transportation Intelligent Transportation Systems (ITS) Joint Program Office and FHWAs Road Weather Management Program (RWMP), is a six-year effort to develop and demonstrate an integ...

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

PubMed

Guo, P; Huang, G H

2009-01-01

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

The nonlinear evolution of modes on unstable stratified shear layers

NASA Technical Reports Server (NTRS)

Blackaby, Nicholas; Dando, Andrew; Hall, Philip

1993-01-01

The nonlinear development of disturbances in stratified shear flows (having a local Richardson number of value less than one quarter) is considered. Such modes are initially fast growing but, like related studies, we assume that the viscous, non-parallel spreading of the shear layer results in them evolving in a linear fashion until they reach a position where their amplitudes are large enough and their growth rates have diminished sufficiently so that amplitude equations can be derived using weakly nonlinear and non-equilibrium critical-layer theories. Four different basic integro-differential amplitude equations are possible, including one due to a novel mechanism; the relevant choice of amplitude equation, at a particular instance, being dependent on the relative sizes of the disturbance amplitude, the growth rate of the disturbance, its wavenumber, and the viscosity of the fluid. This richness of choice of possible nonlinearities arises mathematically from the indicial Frobenius roots of the governing linear inviscid equation (the Taylor-Goldstein equation) not, in general, differing by an integer. The initial nonlinear evolution of a mode will be governed by an integro-differential amplitude equations with a cubic nonlinearity but the resulting significant increase in the size of the disturbance's amplitude leads on to the next stage of the evolution process where the evolution of the mode is governed by an integro-differential amplitude equations with a quintic nonlinearity. Continued growth of the disturbance amplitude is expected during this stage, resulting in the effects of nonlinearity spreading to outside the critical level, by which time the flow has become fully nonlinear.

GLOBAL SOLUTIONS TO FOLDED CONCAVE PENALIZED NONCONVEX LEARNING

PubMed Central

Liu, Hongcheng; Yao, Tao; Li, Runze

2015-01-01

This paper is concerned with solving nonconvex learning problems with folded concave penalty. Despite that their global solutions entail desirable statistical properties, there lack optimization techniques that guarantee global optimality in a general setting. In this paper, we show that a class of nonconvex learning problems are equivalent to general quadratic programs. This equivalence facilitates us in developing mixed integer linear programming reformulations, which admit finite algorithms that find a provably global optimal solution. We refer to this reformulation-based technique as the mixed integer programming-based global optimization (MIPGO). To our knowledge, this is the first global optimization scheme with a theoretical guarantee for folded concave penalized nonconvex learning with the SCAD penalty (Fan and Li, 2001) and the MCP penalty (Zhang, 2010). Numerical results indicate a significant outperformance of MIPGO over the state-of-the-art solution scheme, local linear approximation, and other alternative solution techniques in literature in terms of solution quality. PMID:27141126

RSM 1.0 user's guide: A resupply scheduler using integer optimization

NASA Technical Reports Server (NTRS)

Viterna, Larry A.; Green, Robert D.; Reed, David M.

1991-01-01

The Resupply Scheduling Model (RSM) is a PC based, fully menu-driven computer program. It uses integer programming techniques to determine an optimum schedule to replace components on or before a fixed replacement period, subject to user defined constraints such as transportation mass and volume limits or available repair crew time. Principal input for RSJ includes properties such as mass and volume and an assembly sequence. Resource constraints are entered for each period corresponding to the component properties. Though written to analyze the electrical power system on the Space Station Freedom, RSM is quite general and can be used to model the resupply of almost any system subject to user defined resource constraints. Presented here is a step by step procedure for preparing the input, performing the analysis, and interpreting the results. Instructions for installing the program and information on the algorithms are given.

An integer programming approach to a real-world recyclable waste collection problem in Argentina.

PubMed

Braier, Gustavo; Durán, Guillermo; Marenco, Javier; Wesner, Francisco

2017-05-01

This article reports on the use of mathematical programming techniques to optimise the routes of a recyclable waste collection system servicing Morón, a large municipality outside Buenos Aires, Argentina. The truck routing problem posed by the system is a particular case of the generalised directed open rural postman problem. An integer programming model is developed with a solving procedure built around a subtour-merging algorithm and the addition of subtour elimination constraints. The route solutions generated by the proposed methodology perform significantly better than the previously used, manually designed routes, the main improvement being that coverage of blocks within the municipality with the model solutions is 100% by construction, whereas with the manual routes as much as 16% of the blocks went unserviced. The model-generated routes were adopted by the municipality in 2014 and the national government is planning to introduce the methodology elsewhere in the country.

A hybrid approach to modeling and control of vehicle height for electronically controlled air suspension

NASA Astrophysics Data System (ADS)

Sun, Xiaoqiang; Cai, Yingfeng; Wang, Shaohua; Liu, Yanling; Chen, Long

2016-01-01

The control problems associated with vehicle height adjustment of electronically controlled air suspension (ECAS) still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical (MLD) modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller (HMPC) is tuned based on online mixed-integer quadratic optimization (MIQP). Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology (MPT), thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.

Synchronizable Series Expressions. Part 2. Overview of the Theory and Implementation.

DTIC Science & Technology

1987-11-01

more running time than shown in the table. because time is eventually required in order to collect the garbage it creates. Program Running ’rime Garbage...possible to simply put an enumerator where it is used.) (loop for x integer from I to 4 collect x) - (lotS* ((x (Eup I :to 4))) (declare (type integer x...below. (loop for x from 1 to 4 and for y = 0 then (1- x) collect (list x y)) - (lotS* ((x (Eup 1 :to 4)) (y (Tprevious (1- x) 0))) (Rlist (list x y

Papers on Program Testing,

DTIC Science & Technology

1979-01-01

tractability for scientific analysis. Although much remains to be learned about mutation as a testing tool, there is a considerable body of written material...explicitly address classifications (2) may not have been affected at all! In general, the and (3) in this article , except to point out that even relative...34 ARTICLE B=B’B C IN CACM 1971). C=C*02 INTEGER AiN),N.F D=B+C INTEGER M.NS.R.I.J.W IF (A.NE.D) GOTO 200 MI PRINT 150 NS=N 150 FORMATIIH .RIGHT ANGLED

Alternation of regular and chaotic dynamics in a simple two-degree-of-freedom system with nonlinear inertial coupling.

PubMed

Sigalov, G; Gendelman, O V; AL-Shudeifat, M A; Manevitch, L I; Vakakis, A F; Bergman, L A

2012-03-01

We show that nonlinear inertial coupling between a linear oscillator and an eccentric rotator can lead to very interesting interchanges between regular and chaotic dynamical behavior. Indeed, we show that this model demonstrates rather unusual behavior from the viewpoint of nonlinear dynamics. Specifically, at a discrete set of values of the total energy, the Hamiltonian system exhibits non-conventional nonlinear normal modes, whose shape is determined by phase locking of rotatory and oscillatory motions of the rotator at integer ratios of characteristic frequencies. Considering the weakly damped system, resonance capture of the dynamics into the vicinity of these modes brings about regular motion of the system. For energy levels far from these discrete values, the motion of the system is chaotic. Thus, the succession of resonance captures and escapes by a discrete set of the normal modes causes a sequence of transitions between regular and chaotic behavior, provided that the damping is sufficiently small. We begin from the Hamiltonian system and present a series of Poincaré sections manifesting the complex structure of the phase space of the considered system with inertial nonlinear coupling. Then an approximate analytical description is presented for the non-conventional nonlinear normal modes. We confirm the analytical results by numerical simulation and demonstrate the alternate transitions between regular and chaotic dynamics mentioned above. The origin of the chaotic behavior is also discussed.

ALPS - A LINEAR PROGRAM SOLVER

NASA Technical Reports Server (NTRS)

Viterna, L. A.

1994-01-01

Linear programming is a widely-used engineering and management tool. Scheduling, resource allocation, and production planning are all well-known applications of linear programs (LP's). Most LP's are too large to be solved by hand, so over the decades many computer codes for solving LP's have been developed. ALPS, A Linear Program Solver, is a full-featured LP analysis program. ALPS can solve plain linear programs as well as more complicated mixed integer and pure integer programs. ALPS also contains an efficient solution technique for pure binary (0-1 integer) programs. One of the many weaknesses of LP solvers is the lack of interaction with the user. ALPS is a menu-driven program with no special commands or keywords to learn. In addition, ALPS contains a full-screen editor to enter and maintain the LP formulation. These formulations can be written to and read from plain ASCII files for portability. For those less experienced in LP formulation, ALPS contains a problem "parser" which checks the formulation for errors. ALPS creates fully formatted, readable reports that can be sent to a printer or output file. ALPS is written entirely in IBM's APL2/PC product, Version 1.01. The APL2 workspace containing all the ALPS code can be run on any APL2/PC system (AT or 386). On a 32-bit system, this configuration can take advantage of all extended memory. The user can also examine and modify the ALPS code. The APL2 workspace has also been "packed" to be run on any DOS system (without APL2) as a stand-alone "EXE" file, but has limited memory capacity on a 640K system. A numeric coprocessor (80X87) is optional but recommended. The standard distribution medium for ALPS is a 5.25 inch 360K MS-DOS format diskette. IBM, IBM PC and IBM APL2 are registered trademarks of International Business Machines Corporation. MS-DOS is a registered trademark of Microsoft Corporation.

Birkhoff Normal Form for Some Nonlinear PDEs

NASA Astrophysics Data System (ADS)

Bambusi, Dario

We consider the problem of extending to PDEs Birkhoff normal form theorem on Hamiltonian systems close to nonresonant elliptic equilibria. As a model problem we take the nonlinear wave equation with Dirichlet boundary conditions on [0,π] g is an analytic skewsymmetric function which vanishes for u=0 and is periodic with period 2π in the x variable. We prove, under a nonresonance condition which is fulfilled for most g's, that for any integer M there exists a canonical transformation that puts the Hamiltonian in Birkhoff normal form up to a reminder of order M. The canonical transformation is well defined in a neighbourhood of the origin of a Sobolev type phase space of sufficiently high order. Some dynamical consequences are obtained. The technique of proof is applicable to quite general semilinear equations in one space dimension.

APPLICATION OF NEURAL NETWORK ALGORITHMS FOR BPM LINEARIZATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Musson, John C.; Seaton, Chad; Spata, Mike F.

2012-11-01

Stripline BPM sensors contain inherent non-linearities, as a result of field distortions from the pickup elements. Many methods have been devised to facilitate corrections, often employing polynomial fitting. The cost of computation makes real-time correction difficult, particulalry when integer math is utilized. The application of neural-network technology, particularly the multi-layer perceptron algorithm, is proposed as an efficient alternative for electrode linearization. A process of supervised learning is initially used to determine the weighting coefficients, which are subsequently applied to the incoming electrode data. A non-linear layer, known as an activation layer, is responsible for the removal of saturation effects. Implementationmore » of a perceptron in an FPGA-based software-defined radio (SDR) is presented, along with performance comparisons. In addition, efficient calculation of the sigmoidal activation function via the CORDIC algorithm is presented.« less

Symmetry classification of time-fractional diffusion equation

NASA Astrophysics Data System (ADS)

Naeem, I.; Khan, M. D.

2017-01-01

In this article, a new approach is proposed to construct the symmetry groups for a class of fractional differential equations which are expressed in the modified Riemann-Liouville fractional derivative. We perform a complete group classification of a nonlinear fractional diffusion equation which arises in fractals, acoustics, control theory, signal processing and many other applications. Introducing the suitable transformations, the fractional derivatives are converted to integer order derivatives and in consequence the nonlinear fractional diffusion equation transforms to a partial differential equation (PDE). Then the Lie symmetries are computed for resulting PDE and using inverse transformations, we derive the symmetries for fractional diffusion equation. All cases are discussed in detail and results for symmetry properties are compared for different values of α. This study provides a new way of computing symmetries for a class of fractional differential equations.

The Capability Portfolio Analysis Tool (CPAT): A Mixed Integer Linear Programming Formulation for Fleet Modernization Analysis (Version 2.0.2).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waddell, Lucas; Muldoon, Frank; Henry, Stephen Michael

In order to effectively plan the management and modernization of their large and diverse fleets of vehicles, Program Executive Office Ground Combat Systems (PEO GCS) and Program Executive Office Combat Support and Combat Service Support (PEO CS&CSS) commis- sioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This paper contains a thor-more » ough documentation of the terminology, parameters, variables, and constraints that comprise the fleet management mixed integer linear programming (MILP) mathematical formulation. This paper, which is an update to the original CPAT formulation document published in 2015 (SAND2015-3487), covers the formulation of important new CPAT features.« less

An improved exploratory search technique for pure integer linear programming problems

NASA Technical Reports Server (NTRS)

Fogle, F. R.

1990-01-01

The development is documented of a heuristic method for the solution of pure integer linear programming problems. The procedure draws its methodology from the ideas of Hooke and Jeeves type 1 and 2 exploratory searches, greedy procedures, and neighborhood searches. It uses an efficient rounding method to obtain its first feasible integer point from the optimal continuous solution obtained via the simplex method. Since this method is based entirely on simple addition or subtraction of one to each variable of a point in n-space and the subsequent comparison of candidate solutions to a given set of constraints, it facilitates significant complexity improvements over existing techniques. It also obtains the same optimal solution found by the branch-and-bound technique in 44 of 45 small to moderate size test problems. Two example problems are worked in detail to show the inner workings of the method. Furthermore, using an established weighted scheme for comparing computational effort involved in an algorithm, a comparison of this algorithm is made to the more established and rigorous branch-and-bound method. A computer implementation of the procedure, in PC compatible Pascal, is also presented and discussed.

Generation Expansion Planning With Large Amounts of Wind Power via Decision-Dependent Stochastic Programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhan, Yiduo; Zheng, Qipeng P.; Wang, Jianhui

Power generation expansion planning needs to deal with future uncertainties carefully, given that the invested generation assets will be in operation for a long time. Many stochastic programming models have been proposed to tackle this challenge. However, most previous works assume predetermined future uncertainties (i.e., fixed random outcomes with given probabilities). In several recent studies of generation assets' planning (e.g., thermal versus renewable), new findings show that the investment decisions could affect the future uncertainties as well. To this end, this paper proposes a multistage decision-dependent stochastic optimization model for long-term large-scale generation expansion planning, where large amounts of windmore » power are involved. In the decision-dependent model, the future uncertainties are not only affecting but also affected by the current decisions. In particular, the probability distribution function is determined by not only input parameters but also decision variables. To deal with the nonlinear constraints in our model, a quasi-exact solution approach is then introduced to reformulate the multistage stochastic investment model to a mixed-integer linear programming model. The wind penetration, investment decisions, and the optimality of the decision-dependent model are evaluated in a series of multistage case studies. The results show that the proposed decision-dependent model provides effective optimization solutions for long-term generation expansion planning.« less

Determining on-fault earthquake magnitude distributions from integer programming

USGS Publications Warehouse

Geist, Eric L.; Parsons, Thomas E.

2018-01-01

Earthquake magnitude distributions among faults within a fault system are determined from regional seismicity and fault slip rates using binary integer programming. A synthetic earthquake catalog (i.e., list of randomly sampled magnitudes) that spans millennia is first formed, assuming that regional seismicity follows a Gutenberg-Richter relation. Each earthquake in the synthetic catalog can occur on any fault and at any location. The objective is to minimize misfits in the target slip rate for each fault, where slip for each earthquake is scaled from its magnitude. The decision vector consists of binary variables indicating which locations are optimal among all possibilities. Uncertainty estimates in fault slip rates provide explicit upper and lower bounding constraints to the problem. An implicit constraint is that an earthquake can only be located on a fault if it is long enough to contain that earthquake. A general mixed-integer programming solver, consisting of a number of different algorithms, is used to determine the optimal decision vector. A case study is presented for the State of California, where a 4 kyr synthetic earthquake catalog is created and faults with slip ≥3 mm/yr are considered, resulting in >106  variables. The optimal magnitude distributions for each of the faults in the system span a rich diversity of shapes, ranging from characteristic to power-law distributions. 

Nonlinear theory for axisymmetric self-similar two-dimensional oscillations of electrons in cold plasma with constant proton background

NASA Astrophysics Data System (ADS)

Osherovich, V. A.; Fainberg, J.

2018-01-01

We consider simultaneous oscillations of electrons moving both along the axis of symmetry and also in the direction perpendicular to the axis. We derive a system of three nonlinear ordinary differential equations which describe self-similar oscillations of cold electrons in a constant proton density background (np = n0 = constant). These three equations represent an exact class of solutions. For weak nonlinear conditions, the frequency spectra of electric field oscillations exhibit split frequency behavior at the Langmuir frequency ωp0 and its harmonics, as well as presence of difference frequencies at low spectral values. For strong nonlinear conditions, the spectra contain peaks at frequencies with values ωp0(n +m √{2 }) , where n and m are integer numbers (positive and negative). We predict that both spectral types (weak and strong) should be observed in plasmas where axial symmetry may exist. To illustrate possible applications of our theory, we present a spectrum of electric field oscillations observed in situ in the solar wind by the WAVES experiment on the Wind spacecraft during the passage of a type III solar radio burst.

A wavelet-based ECG delineation algorithm for 32-bit integer online processing

PubMed Central

2011-01-01

Background Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. Methods This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. Results The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. Conclusions The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra. PMID:21457580

A wavelet-based ECG delineation algorithm for 32-bit integer online processing.

PubMed

Di Marco, Luigi Y; Chiari, Lorenzo

2011-04-03

Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra.

Selection of actuator locations for static shape control of large space structures by heuristic integer programing

NASA Technical Reports Server (NTRS)

Haftka, R. T.; Adelman, H. M.

1984-01-01

Orbiting spacecraft such as large space antennas have to maintain a highly accurate space to operate satisfactorily. Such structures require active and passive controls to mantain an accurate shape under a variety of disturbances. Methods for the optimum placement of control actuators for correcting static deformations are described. In particular, attention is focused on the case were control locations have to be selected from a large set of available sites, so that integer programing methods are called for. The effectiveness of three heuristic techniques for obtaining a near-optimal site selection is compared. In addition, efficient reanalysis techniques for the rapid assessment of control effectiveness are presented. Two examples are used to demonstrate the methods: a simple beam structure and a 55m space-truss-parabolic antenna.

Developing optimal nurses work schedule using integer programming

NASA Astrophysics Data System (ADS)

Shahidin, Ainon Mardhiyah; Said, Mohd Syazwan Md; Said, Noor Hizwan Mohamad; Sazali, Noor Izatie Amaliena

2017-08-01

Time management is the art of arranging, organizing and scheduling one's time for the purpose of generating more effective work and productivity. Scheduling is the process of deciding how to commit resources between varieties of possible tasks. Thus, it is crucial for every organization to have a good work schedule for their staffs. The job of Ward nurses at hospitals runs for 24 hours every day. Therefore, nurses will be working using shift scheduling. This study is aimed to solve the nurse scheduling problem at an emergency ward of a private hospital. A 7-day work schedule for 7 consecutive weeks satisfying all the constraints set by the hospital will be developed using Integer Programming. The work schedule for the nurses obtained gives an optimal solution where all the constraints are being satisfied successfully.

An Integer Programming Model For Solving Heterogeneous Vehicle Routing Problem With Hard Time Window considering Service Choice

NASA Astrophysics Data System (ADS)

Susilawati, Enny; Mawengkang, Herman; Efendi, Syahril

2018-01-01

Generally a Vehicle Routing Problem with time windows (VRPTW) can be defined as a problem to determine the optimal set of routes used by a fleet of vehicles to serve a given set of customers with service time restrictions; the objective is to minimize the total travel cost (related to the travel times or distances) and operational cost (related to the number of vehicles used). In this paper we address a variant of the VRPTW in which the fleet of vehicle is heterogenic due to the different size of demand from customers. The problem, called Heterogeneous VRP (HVRP) also includes service levels. We use integer programming model to describe the problem. A feasible neighbourhood approach is proposed to solve the model.

Advances in mixed-integer programming methods for chemical production scheduling.

PubMed

Velez, Sara; Maravelias, Christos T

2014-01-01

The goal of this paper is to critically review advances in the area of chemical production scheduling over the past three decades and then present two recently proposed solution methods that have led to dramatic computational enhancements. First, we present a general framework and problem classification and discuss modeling and solution methods with an emphasis on mixed-integer programming (MIP) techniques. Second, we present two solution methods: (a) a constraint propagation algorithm that allows us to compute parameters that are then used to tighten MIP scheduling models and (b) a reformulation that introduces new variables, thus leading to effective branching. We also present computational results and an example illustrating how these methods are implemented, as well as the resulting enhancements. We close with a discussion of open research challenges and future research directions.

Optimal sensor placement for leak location in water distribution networks using genetic algorithms.

PubMed

Casillas, Myrna V; Puig, Vicenç; Garza-Castañón, Luis E; Rosich, Albert

2013-11-04

This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs) are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach.

Optimal Sensor Placement for Leak Location in Water Distribution Networks Using Genetic Algorithms

PubMed Central

Casillas, Myrna V.; Puig, Vicenç; Garza-Castañón, Luis E.; Rosich, Albert

2013-01-01

This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs) are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach. PMID:24193099

A divide-and-conquer approach to determine the Pareto frontier for optimization of protein engineering experiments.

PubMed

He, Lu; Friedman, Alan M; Bailey-Kellogg, Chris

2012-03-01

In developing improved protein variants by site-directed mutagenesis or recombination, there are often competing objectives that must be considered in designing an experiment (selecting mutations or breakpoints): stability versus novelty, affinity versus specificity, activity versus immunogenicity, and so forth. Pareto optimal experimental designs make the best trade-offs between competing objectives. Such designs are not "dominated"; that is, no other design is better than a Pareto optimal design for one objective without being worse for another objective. Our goal is to produce all the Pareto optimal designs (the Pareto frontier), to characterize the trade-offs and suggest designs most worth considering, but to avoid explicitly considering the large number of dominated designs. To do so, we develop a divide-and-conquer algorithm, Protein Engineering Pareto FRontier (PEPFR), that hierarchically subdivides the objective space, using appropriate dynamic programming or integer programming methods to optimize designs in different regions. This divide-and-conquer approach is efficient in that the number of divisions (and thus calls to the optimizer) is directly proportional to the number of Pareto optimal designs. We demonstrate PEPFR with three protein engineering case studies: site-directed recombination for stability and diversity via dynamic programming, site-directed mutagenesis of interacting proteins for affinity and specificity via integer programming, and site-directed mutagenesis of a therapeutic protein for activity and immunogenicity via integer programming. We show that PEPFR is able to effectively produce all the Pareto optimal designs, discovering many more designs than previous methods. The characterization of the Pareto frontier provides additional insights into the local stability of design choices as well as global trends leading to trade-offs between competing criteria. Copyright © 2011 Wiley Periodicals, Inc.

Variable neighborhood search to solve the vehicle routing problem for hazardous materials transportation.

PubMed

Bula, Gustavo Alfredo; Prodhon, Caroline; Gonzalez, Fabio Augusto; Afsar, H Murat; Velasco, Nubia

2017-02-15

This work focuses on the Heterogeneous Fleet Vehicle Routing problem (HFVRP) in the context of hazardous materials (HazMat) transportation. The objective is to determine a set of routes that minimizes the total expected routing risk. This is a nonlinear function, and it depends on the vehicle load and the population exposed when an incident occurs. Thus, a piecewise linear approximation is used to estimate it. For solving the problem, a variant of the Variable Neighborhood Search (VNS) algorithm is employed. To improve its performance, a post-optimization procedure is implemented via a Set Partitioning (SP) problem. The SP is solved on a pool of routes obtained from executions of the local search procedure embedded on the VNS. The algorithm is tested on two sets of HFVRP instances based on literature with up to 100 nodes, these instances are modified to include vehicle and arc risk parameters. The results are competitive in terms of computational efficiency and quality attested by a comparison with Mixed Integer Linear Programming (MILP) previously proposed. Copyright © 2016 Elsevier B.V. All rights reserved.

A reliable facility location design model with site-dependent disruption in the imperfect information context

PubMed Central

Yun, Lifen; Wang, Xifu; Fan, Hongqiang; Li, Xiaopeng

2017-01-01

This paper proposes a reliable facility location design model under imperfect information with site-dependent disruptions; i.e., each facility is subject to a unique disruption probability that varies across the space. In the imperfect information contexts, customers adopt a realistic “trial-and-error” strategy to visit facilities; i.e., they visit a number of pre-assigned facilities sequentially until they arrive at the first operational facility or give up looking for the service. This proposed model aims to balance initial facility investment and expected long-term operational cost by finding the optimal facility locations. A nonlinear integer programming model is proposed to describe this problem. We apply a linearization technique to reduce the difficulty of solving the proposed model. A number of problem instances are studied to illustrate the performance of the proposed model. The results indicate that our proposed model can reveal a number of interesting insights into the facility location design with site-dependent disruptions, including the benefit of backup facilities and system robustness against variation of the loss-of-service penalty. PMID:28486564

Optimal Operation System of the Integrated District Heating System with Multiple Regional Branches

NASA Astrophysics Data System (ADS)

Kim, Ui Sik; Park, Tae Chang; Kim, Lae-Hyun; Yeo, Yeong Koo

This paper presents an optimal production and distribution management for structural and operational optimization of the integrated district heating system (DHS) with multiple regional branches. A DHS consists of energy suppliers and consumers, district heating pipelines network and heat storage facilities in the covered region. In the optimal management system, production of heat and electric power, regional heat demand, electric power bidding and sales, transport and storage of heat at each regional DHS are taken into account. The optimal management system is formulated as a mixed integer linear programming (MILP) where the objectives is to minimize the overall cost of the integrated DHS while satisfying the operation constraints of heat units and networks as well as fulfilling heating demands from consumers. Piecewise linear formulation of the production cost function and stairwise formulation of the start-up cost function are used to compute nonlinear cost function approximately. Evaluation of the total overall cost is based on weekly operations at each district heat branches. Numerical simulations show the increase of energy efficiency due to the introduction of the present optimal management system.

Using heuristic algorithms for capacity leasing and task allocation issues in telecommunication networks under fuzzy quality of service constraints

NASA Astrophysics Data System (ADS)

Huseyin Turan, Hasan; Kasap, Nihat; Savran, Huseyin

2014-03-01

Nowadays, every firm uses telecommunication networks in different amounts and ways in order to complete their daily operations. In this article, we investigate an optimisation problem that a firm faces when acquiring network capacity from a market in which there exist several network providers offering different pricing and quality of service (QoS) schemes. The QoS level guaranteed by network providers and the minimum quality level of service, which is needed for accomplishing the operations are denoted as fuzzy numbers in order to handle the non-deterministic nature of the telecommunication network environment. Interestingly, the mathematical formulation of the aforementioned problem leads to the special case of a well-known two-dimensional bin packing problem, which is famous for its computational complexity. We propose two different heuristic solution procedures that have the capability of solving the resulting nonlinear mixed integer programming model with fuzzy constraints. In conclusion, the efficiency of each algorithm is tested in several test instances to demonstrate the applicability of the methodology.

Integer Optimization Model for a Logistic System based on Location-Routing Considering Distance and Chosen Route

NASA Astrophysics Data System (ADS)

Mulyasari, Joni; Mawengkang, Herman; Efendi, Syahril

2018-02-01

In a distribution network it is important to decide the locations of facilities that impacts not only the profitability of an organization but the ability to serve customers.Generally the location-routing problem is to minimize the overall cost by simultaneously selecting a subset of candidate facilities and constructing a set of delivery routes that satisfy some restrictions. In this paper we impose restriction on the route that should be passed for delivery. We use integer programming model to describe the problem. A feasible neighbourhood search is proposed to solve the result model.

A new Fortran 90 program to compute regular and irregular associated Legendre functions (new version announcement)

NASA Astrophysics Data System (ADS)

Schneider, Barry I.; Segura, Javier; Gil, Amparo; Guan, Xiaoxu; Bartschat, Klaus

2018-04-01

This is a revised and updated version of a modern Fortran 90 code to compute the regular Plm (x) and irregular Qlm (x) associated Legendre functions for all x ∈(- 1 , + 1) (on the cut) and | x | > 1 and integer degree (l) and order (m). The necessity to revise the code comes as a consequence of some comments of Prof. James Bremer of the UC//Davis Mathematics Department, who discovered that there were errors in the code for large integer degree and order for the normalized regular Legendre functions on the cut.

Modeling an integrated hospital management planning problem using integer optimization approach

NASA Astrophysics Data System (ADS)

Sitepu, Suryati; Mawengkang, Herman; Irvan

2017-09-01

Hospital is a very important institution to provide health care for people. It is not surprising that nowadays the people’s demands for hospital is increasing. However, due to the rising cost of healthcare services, hospitals need to consider efficiencies in order to overcome these two problems. This paper deals with an integrated strategy of staff capacity management and bed allocation planning to tackle these problems. Mathematically, the strategy can be modeled as an integer linear programming problem. We solve the model using a direct neighborhood search approach, based on the notion of superbasic variables.

Numerical study of the medium thickness in the Z-scan technique

NASA Astrophysics Data System (ADS)

Severiano Carrillo, I.; Méndez Otero, M. M.; Arroyo Carrasco, M. L.; Iturbe Castillo, M. D.

2011-09-01

The optical characterization of nonlinear media through the Z-scan technique considers initially a thin medium (with a thickness much less than the beam depth of focus). It has been observed that increasing the thickness of the medium the transmittance increases, this means that n2 increases, for this reason we will present a numerical model to determinate the minimum thin and the maximum thick medium limit. A thin medium is considered as a thin lens with focal length F1 and a thick medium can be regarded as a set of such thin lenses set with focal lengths F2, these lenses are contained in a medium whit a refraction index different than air. This analysis is made through Matlab using the theory of Gaussian beams, ABCD matrices and the q parameter, elementary theory in the development of this work, where the main feature of this model is that the nonlinearity type of the medium is considered as an integer constant in its focal length3. We present the graphs obtained from Z-scan for thick medium with both thermal and Kerr nonlinearities.

Recent research in network problems with applications

NASA Technical Reports Server (NTRS)

Thompson, G. L.

1980-01-01

The capabilities of network codes and their extensions are surveyed in regard to specially structured integer programming problems which are solved by using the solutions of a series of ordinary network problems.

Internal resonance of an elastic body levitated above high-Tc superconducting bulks

NASA Astrophysics Data System (ADS)

Kokuzawa, T.; Toshihiko, S.; Yoshizawa, M.

2010-06-01

In high-Tc superconducting magnetic levitation systems, levitated bodies can keep stable levitation with no contact and no control and thus their damping is very small. Thanks to these features, their applications to various apparatus are expected. However, on account of their small damping, the nonlinearity of electromagnetic levitation force can give notable effects upon motion of the levitated bodies. Therefore this nonlinearity must be taken into account to accurately analyze the dynamical behavior of the levitated bodies. Structures of such a levitated body can show elastic deformation if the large electromagnetic force acts on it. Therefore, we need to deal with the model as an elastic body. As mentioned above, nonlinear characteristics easily appear in this elastic vibration on account of the small damping. Especially when the ratio of the natural frequencies of the eigenmodes is integer, internal resonance can occur. This nonlinear resonance is derived from nonlinear interactions among the eigenmodes of the elastic levitated body. This kind of internal resonance of an elastic body appearing in high-Tc superconducting levitation systems has not been studied so far. This research especially deals with internal resonance of a beam supported at both its ends by electromagnetic forces acting on permanent magnets. The governing equation with the nonlinear boundary conditions for the dynamics of a levitated beam has been derived. Numerical results show internal resonance of the 1st mode and the 3rd mode. Experimental results are qualitatively in good agreement with numerical ones.

Integer programming model for optimizing bus timetable using genetic algorithm

NASA Astrophysics Data System (ADS)

Wihartiko, F. D.; Buono, A.; Silalahi, B. P.

2017-01-01

Bus timetable gave an information for passengers to ensure the availability of bus services. Timetable optimal condition happened when bus trips frequency could adapt and suit with passenger demand. In the peak time, the number of bus trips would be larger than the off-peak time. If the number of bus trips were more frequent than the optimal condition, it would make a high operating cost for bus operator. Conversely, if the number of trip was less than optimal condition, it would make a bad quality service for passengers. In this paper, the bus timetabling problem would be solved by integer programming model with modified genetic algorithm. Modification was placed in the chromosomes design, initial population recovery technique, chromosomes reconstruction and chromosomes extermination on specific generation. The result of this model gave the optimal solution with accuracy 99.1%.

Reconstructing cerebrovascular networks under local physiological constraints by integer programming

DOE PAGES

Rempfler, Markus; Schneider, Matthias; Ielacqua, Giovanna D.; ...

2015-04-23

We introduce a probabilistic approach to vessel network extraction that enforces physiological constraints on the vessel structure. The method accounts for both image evidence and geometric relationships between vessels by solving an integer program, which is shown to yield the maximum a posteriori (MAP) estimate to the probabilistic model. Starting from an over-connected network, it is pruning vessel stumps and spurious connections by evaluating the local geometry and the global connectivity of the graph. We utilize a high-resolution micro computed tomography (µCT) dataset of a cerebrovascular corrosion cast to obtain a reference network and learn the prior distributions of ourmore » probabilistic model. As a result, we perform experiments on micro magnetic resonance angiography (µMRA) images of mouse brains and discuss properties of the networks obtained under different tracking and pruning approaches.« less

FPGA Implementation of Optimal 3D-Integer DCT Structure for Video Compression

PubMed Central

2015-01-01

A novel optimal structure for implementing 3D-integer discrete cosine transform (DCT) is presented by analyzing various integer approximation methods. The integer set with reduced mean squared error (MSE) and high coding efficiency are considered for implementation in FPGA. The proposed method proves that the least resources are utilized for the integer set that has shorter bit values. Optimal 3D-integer DCT structure is determined by analyzing the MSE, power dissipation, coding efficiency, and hardware complexity of different integer sets. The experimental results reveal that direct method of computing the 3D-integer DCT using the integer set [10, 9, 6, 2, 3, 1, 1] performs better when compared to other integer sets in terms of resource utilization and power dissipation. PMID:26601120

Topological charge algebra of optical vortices in nonlinear interactions.

PubMed

Zhdanova, Alexandra A; Shutova, Mariia; Bahari, Aysan; Zhi, Miaochan; Sokolov, Alexei V

2015-12-28

We investigate the transfer of orbital angular momentum among multiple beams involved in a coherent Raman interaction. We use a liquid crystal light modulator to shape pump and Stokes beams into optical vortices with various integer values of topological charge, and cross them in a Raman-active crystal to produce multiple Stokes and anti-Stokes sidebands. We measure the resultant vortex charges using a tilted-lens technique. We verify that in every case the generated beams' topological charges obey a simple relationship, resulting from angular momentum conservation for created and annihilated photons, or equivalently, from phase-matching considerations for multiple interacting beams.

Existence of entire solutions of some non-linear differential-difference equations.

PubMed

Chen, Minfeng; Gao, Zongsheng; Du, Yunfei

2017-01-01

In this paper, we investigate the admissible entire solutions of finite order of the differential-difference equations [Formula: see text] and [Formula: see text], where [Formula: see text], [Formula: see text] are two non-zero polynomials, [Formula: see text] is a polynomial and [Formula: see text]. In addition, we investigate the non-existence of entire solutions of finite order of the differential-difference equation [Formula: see text], where [Formula: see text], [Formula: see text] are two non-constant polynomials, [Formula: see text], m , n are positive integers and satisfy [Formula: see text] except for [Formula: see text], [Formula: see text].

Automated Simultaneous Assembly of Multistage Testlets for a High-Stakes Licensing Examination

ERIC Educational Resources Information Center

Breithaupt, Krista; Hare, Donovan R.

2007-01-01

Many challenges exist for high-stakes testing programs offering continuous computerized administration. The automated assembly of test questions to exactly meet content and other requirements, provide uniformity, and control item exposure can be modeled and solved by mixed-integer programming (MIP) methods. A case study of the computerized…

THREE-PEE SAMPLING THEORY and program 'THRP' for computer generation of selection criteria

Treesearch

L. R. Grosenbaugh

1965-01-01

Theory necessary for sampling with probability proportional to prediction ('three-pee,' or '3P,' sampling) is first developed and then exemplified by numerical comparisons of several estimators. Program 'T RP' for computer generation of appropriate 3P-sample-selection criteria is described, and convenient random integer dispensers are...

The checkpoint ordering problem

PubMed Central

Hungerländer, P.

2017-01-01

Abstract We suggest a new variant of a row layout problem: Find an ordering of n departments with given lengths such that the total weighted sum of their distances to a given checkpoint is minimized. The Checkpoint Ordering Problem (COP) is both of theoretical and practical interest. It has several applications and is conceptually related to some well-studied combinatorial optimization problems, namely the Single-Row Facility Layout Problem, the Linear Ordering Problem and a variant of parallel machine scheduling. In this paper we study the complexity of the (COP) and its special cases. The general version of the (COP) with an arbitrary but fixed number of checkpoints is NP-hard in the weak sense. We propose both a dynamic programming algorithm and an integer linear programming approach for the (COP) . Our computational experiments indicate that the (COP) is hard to solve in practice. While the run time of the dynamic programming algorithm strongly depends on the length of the departments, the integer linear programming approach is able to solve instances with up to 25 departments to optimality. PMID:29170574

The spike trains of inhibited pacemaker neurons seen through the magnifying glass of nonlinear analyses.

PubMed

Segundo, J P; Sugihara, G; Dixon, P; Stiber, M; Bersier, L F

1998-12-01

This communication describes the new information that may be obtained by applying nonlinear analytical techniques to neurobiological time-series. Specifically, we consider the sequence of interspike intervals Ti (the "timing") of trains recorded from synaptically inhibited crayfish pacemaker neurons. As reported earlier, different postsynaptic spike train forms (sets of timings with shared properties) are generated by varying the average rate and/or pattern (implying interval dispersions and sequences) of presynaptic spike trains. When the presynaptic train is Poisson (independent exponentially distributed intervals), the form is "Poisson-driven" (unperturbed and lengthened intervals succeed each other irregularly). When presynaptic trains are pacemaker (intervals practically equal), forms are either "p:q locked" (intervals repeat periodically), "intermittent" (mostly almost locked but disrupted irregularly), "phase walk throughs" (intermittencies with briefer regular portions), or "messy" (difficult to predict or describe succinctly). Messy trains are either "erratic" (some intervals natural and others lengthened irregularly) or "stammerings" (intervals are integral multiples of presynaptic intervals). The individual spike train forms were analysed using attractor reconstruction methods based on the lagged coordinates provided by successive intervals from the time-series Ti. Numerous models were evaluated in terms of their predictive performance by a trial-and-error procedure: the most successful model was taken as best reflecting the true nature of the system's attractor. Each form was characterized in terms of its dimensionality, nonlinearity and predictability. (1) The dimensionality of the underlying dynamical attractor was estimated by the minimum number of variables (coordinates Ti) required to model acceptably the system's dynamics, i.e. by the system's degrees of freedom. Each model tested was based on a different number of Ti; the smallest number whose predictions were judged successful provided the best integer approximation of the attractor's true dimension (not necessarily an integer). Dimensionalities from three to five provided acceptable fits. (2) The degree of nonlinearity was estimated by: (i) comparing the correlations between experimental results and data from linear and nonlinear models, and (ii) tuning model nonlinearity via a distance-weighting function and identifying the either local or global neighborhood size. Lockings were compatible with linear models and stammerings were marginal; nonlinear models were best for Poisson-driven, intermittent and erratic forms. (3) Finally, prediction accuracy was plotted against increasingly long sequences of intervals forecast: the accuracies for Poisson-driven, locked and stammering forms were invariant, revealing irregularities due to uncorrelated noise, but those of intermittent and messy erratic forms decayed rapidly, indicating an underlying deterministic process. The excellent reconstructions possible for messy erratic and for some intermittent forms are especially significant because of their relatively low dimensionality (around 4), high degree of nonlinearity and prediction decay with time. This is characteristic of chaotic systems, and provides evidence that nonlinear couplings between relatively few variables are the major source of the apparent complexity seen in these cases. This demonstration of different dimensions, degrees of nonlinearity and predictabilities provides rigorous support for the categorization of different synaptically driven discharge forms proposed earlier on the basis of more heuristic criteria. This has significant implications. (1) It demonstrates that heterogeneous postsynaptic forms can indeed be induced by manipulating a few presynaptic variables. (2) Each presynaptic timing induces a form with characteristic dimensionality, thus breaking up the preparation into subsystems such that the physical variables in each operate as one

Periodic solutions for one dimensional wave equation with bounded nonlinearity

NASA Astrophysics Data System (ADS)

Ji, Shuguan

2018-05-01

This paper is concerned with the periodic solutions for the one dimensional nonlinear wave equation with either constant or variable coefficients. The constant coefficient model corresponds to the classical wave equation, while the variable coefficient model arises from the forced vibrations of a nonhomogeneous string and the propagation of seismic waves in nonisotropic media. For finding the periodic solutions of variable coefficient wave equation, it is usually required that the coefficient u (x) satisfies ess infηu (x) > 0 with ηu (x) = 1/2 u″/u - 1/4 (u‧/u)2, which actually excludes the classical constant coefficient model. For the case ηu (x) = 0, it is indicated to remain an open problem by Barbu and Pavel (1997) [6]. In this work, for the periods having the form T = 2p-1/q (p , q are positive integers) and some types of boundary value conditions, we find some fundamental properties for the wave operator with either constant or variable coefficients. Based on these properties, we obtain the existence of periodic solutions when the nonlinearity is monotone and bounded. Such nonlinearity may cross multiple eigenvalues of the corresponding wave operator. In particular, we do not require the condition ess infηu (x) > 0.

Multi-task feature selection in microarray data by binary integer programming.

PubMed

Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

A mathematical programming approach for sequential clustering of dynamic networks

NASA Astrophysics Data System (ADS)

Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia

2016-02-01

A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

Finite pure integer programming algorithms employing only hyperspherically deduced cuts

NASA Technical Reports Server (NTRS)

Young, R. D.

1971-01-01

Three algorithms are developed that may be based exclusively on hyperspherically deduced cuts. The algorithms only apply, therefore, to problems structured so that these cuts are valid. The algorithms are shown to be finite.

Speedy Alchemy.

ERIC Educational Resources Information Center

Deininger, Rolf A.; Berger, Carl F., Jr.

1983-01-01

Provides instructions for interfacing a pH meter directly to an Apple II microcomputer without an analog-to-digital converter. Includes program listing (with enough remark statements to make it self-documenting) in Integer Basic to display the pH readings. (Author/JN)

Solving large-scale fixed cost integer linear programming models for grid-based location problems with heuristic techniques

NASA Astrophysics Data System (ADS)

Noor-E-Alam, Md.; Doucette, John

2015-08-01

Grid-based location problems (GBLPs) can be used to solve location problems in business, engineering, resource exploitation, and even in the field of medical sciences. To solve these decision problems, an integer linear programming (ILP) model is designed and developed to provide the optimal solution for GBLPs considering fixed cost criteria. Preliminary results show that the ILP model is efficient in solving small to moderate-sized problems. However, this ILP model becomes intractable in solving large-scale instances. Therefore, a decomposition heuristic is proposed to solve these large-scale GBLPs, which demonstrates significant reduction of solution runtimes. To benchmark the proposed heuristic, results are compared with the exact solution via ILP. The experimental results show that the proposed method significantly outperforms the exact method in runtime with minimal (and in most cases, no) loss of optimality.

Personnel scheduling using an integer programming model- an application at Avanti Blue-Nile Hotels.

PubMed

Kassa, Biniyam Asmare; Tizazu, Anteneh Eshetu

2013-01-01

In this paper, we report perhaps a first of its kind application of management science in the Ethiopian hotel industry. Avanti Blue Nile Hotels, a newly established five star hotel in Bahir Dar, is the company for which we developed an integer programming model that determines an optimal weekly shift schedule for the Hotel's engineering department personnel while satisfying several constraints including weekly rest requirements per employee, rest requirements between working shifts per employee, required number of personnel per shift, and other constraints. The model is implemented on an excel solver routine. The model enables the company's personnel department management to develop a fair personnel schedule as needed and to effectively utilize personnel resources while satisfying several technical, legal and economic requirements. These encouraging achievements make us optimistic about the gains other Ethiopian organizations can amass by introducing management science approaches in their management planning and decision making systems.

Combinatorial optimization games

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deng, X.; Ibaraki, Toshihide; Nagamochi, Hiroshi

1997-06-01

We introduce a general integer programming formulation for a class of combinatorial optimization games, which immediately allows us to improve the algorithmic result for finding amputations in the core (an important solution concept in cooperative game theory) of the network flow game on simple networks by Kalai and Zemel. An interesting result is a general theorem that the core for this class of games is nonempty if and only if a related linear program has an integer optimal solution. We study the properties for this mathematical condition to hold for several interesting problems, and apply them to resolve algorithmic andmore » complexity issues for their cores along the line as put forward in: decide whether the core is empty; if the core is empty, find an imputation in the core; given an imputation x, test whether x is in the core. We also explore the properties of totally balanced games in this succinct formulation of cooperative games.« less

JPLEX: Java Simplex Implementation with Branch-and-Bound Search for Automated Test Assembly

ERIC Educational Resources Information Center

Park, Ryoungsun; Kim, Jiseon; Dodd, Barbara G.; Chung, Hyewon

2011-01-01

JPLEX, short for Java simPLEX, is an automated test assembly (ATA) program. It is a mixed integer linear programming (MILP) solver written in Java. It reads in a configuration file, solves the minimization problem, and produces an output file for postprocessing. It implements the simplex algorithm to create a fully relaxed solution and…

Radar Resource Management in a Dense Target Environment

DTIC Science & Technology

2014-03-01

problem faced by networked MFRs . While relaxing our assumptions concerning information gain presents numerous challenges worth exploring, future research...linear programming MFR multifunction phased array radar MILP mixed integer linear programming NATO North Atlantic Treaty Organization PDF probability...1: INTRODUCTION Multifunction phased array radars ( MFRs ) are capable of performing various tasks in rapid succession. The performance of target search

A statistical mechanical approach to restricted integer partition functions

NASA Astrophysics Data System (ADS)

Zhou, Chi-Chun; Dai, Wu-Sheng

2018-05-01

The main aim of this paper is twofold: (1) suggesting a statistical mechanical approach to the calculation of the generating function of restricted integer partition functions which count the number of partitions—a way of writing an integer as a sum of other integers under certain restrictions. In this approach, the generating function of restricted integer partition functions is constructed from the canonical partition functions of various quantum gases. (2) Introducing a new type of restricted integer partition functions corresponding to general statistics which is a generalization of Gentile statistics in statistical mechanics; many kinds of restricted integer partition functions are special cases of this restricted integer partition function. Moreover, with statistical mechanics as a bridge, we reveal a mathematical fact: the generating function of restricted integer partition function is just the symmetric function which is a class of functions being invariant under the action of permutation groups. Using this approach, we provide some expressions of restricted integer partition functions as examples.

Canonical quantization of constrained systems and coadjoint orbits of Diff(S sup 1 )

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scherer, W.M.

It is shown that Dirac's treatment of constrained Hamiltonian systems and Schwinger's action principle quantization lead to identical commutations relations. An explicit relation between the Lagrange multipliers in the action principle approach and the additional terms in the Dirac bracket is derived. The equivalence of the two methods is demonstrated in the case of the non-linear sigma model. Dirac's method is extended to superspace and this extension is applied to the chiral superfield. The Dirac brackets of the massive interacting chiral superfluid are derived and shown to give the correct commutation relations for the component fields. The Hamiltonian of themore » theory is given and the Hamiltonian equations of motion are computed. They agree with the component field results. An infinite sequence of differential operators which are covariant under the coadjoint action of Diff(S{sup 1}) and analogues to Hill's operator is constructed. They map conformal fields of negative integer and half-integer weight to their dual space. Some properties of these operators are derived and possible applications are discussed. The Korteweg-de Vries equation is formulated as a coadjoint orbit of Diff(S{sup 1}).« less

Performance analysis of two-degree of freedom fractional order PID controllers for robotic manipulator with payload.

PubMed

Sharma, Richa; Gaur, Prerna; Mittal, A P

2015-09-01

The robotic manipulators are multi-input multi-output (MIMO), coupled and highly nonlinear systems. The presence of external disturbances and time-varying parameters adversely affects the performance of these systems. Therefore, the controller designed for these systems should effectively deal with such complexities, and it is an intriguing task for control engineers. This paper presents two-degree of freedom fractional order proportional-integral-derivative (2-DOF FOPID) controller scheme for a two-link planar rigid robotic manipulator with payload for trajectory tracking task. The tuning of all controller parameters is done using cuckoo search algorithm (CSA). The performance of proposed 2-DOF FOPID controllers is compared with those of their integer order designs, i.e., 2-DOF PID controllers, and with the traditional PID controllers. In order to show effectiveness of proposed scheme, the robustness testing is carried out for model uncertainties, payload variations with time, external disturbance and random noise. Numerical simulation results indicate that the 2-DOF FOPID controllers are superior to their integer order counterparts and the traditional PID controllers. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Minimal excitation states for heat transport in driven quantum Hall systems

NASA Astrophysics Data System (ADS)

Vannucci, Luca; Ronetti, Flavio; Rech, Jérôme; Ferraro, Dario; Jonckheere, Thibaut; Martin, Thierry; Sassetti, Maura

2017-06-01

We investigate minimal excitation states for heat transport into a fractional quantum Hall system driven out of equilibrium by means of time-periodic voltage pulses. A quantum point contact allows for tunneling of fractional quasiparticles between opposite edge states, thus acting as a beam splitter in the framework of the electron quantum optics. Excitations are then studied through heat and mixed noise generated by the random partitioning at the barrier. It is shown that levitons, the single-particle excitations of a filled Fermi sea recently observed in experiments, represent the cleanest states for heat transport since excess heat and mixed shot noise both vanish only when Lorentzian voltage pulses carrying integer electric charge are applied to the conductor. This happens in the integer quantum Hall regime and for Laughlin fractional states as well, with no influence of fractional physics on the conditions for clean energy pulses. In addition, we demonstrate the robustness of such excitations to the overlap of Lorentzian wave packets. Even though mixed and heat noise have nonlinear dependence on the voltage bias, and despite the noninteger power-law behavior arising from the fractional quantum Hall physics, an arbitrary superposition of levitons always generates minimal excitation states.

Stochastic Dynamic Mixed-Integer Programming (SD-MIP)

DTIC Science & Technology

2015-05-05

stochastic linear programming ( SLP ) problems. By using a combination of ideas from cutting plane theory of deterministic MIP (especially disjunctive...developed to date. b) As part of this project, we have also developed tools for very large scale Stochastic Linear Programming ( SLP ). There are...several reasons for this. First, SLP models continue to challenge many of the fastest computers to date, and many applications within the DoD (e.g

Mixed-Integer Nonconvex Quadratic Optimization Relaxations and Performance Analysis

DTIC Science & Technology

2016-10-11

Analysis of Interior Point Algorithms for Non-Lipschitz and Nonconvex Minimization,” (W. Bian, X. Chen, and Ye), Math Programming, 149 (2015) 301-327...Chen, Ge, Wang, Ye), Math Programming, 143 (1-2) (2014) 371-383. This paper resolved an important open question in cardinality constrained...Statistical Performance, and Algorithmic Theory for Local Solutions,” (H. Liu, T. Yao, R. Li, Y. Ye) manuscript, 2nd revision in Math Programming

Materiel Acquisition Management of U.S. Army Attack Helicopters

DTIC Science & Technology

1989-06-02

used to evaluate the existing helicopter program periodically in order to determine utility in reference to all evaluation criteria. Defintion of... mixed integer linear programming model, the Phoenix model has demonstrated the potential to assist in the analysis of strategic and operational issues in...Fleet Max i of Aircraft per Fleet Programmed Buys .. -- Technology Unit Production mix Retirement Start-up ROTIE Flying Hour Aviation Overheadl I Aviation

Integer programming methods for reserve selection and design

Treesearch

Robert G. Haight; Stephanie A. Snyder

2009-01-01

How many nature reserves should there be? Where should they be located? Which places have highest priority for protection? Conservation biologists, economists, and operations researchers have been developing quantitative methods to address these questions since the 1980s.

Optimal traffic resource allocation and management.

DOT National Transportation Integrated Search

2010-05-01

"In this paper, we address the problem of determining the patrol routes of state troopers for maximum coverage of : highway spots with high frequencies of crashes (hot spots). We develop a mixed integer linear programming model : for this problem und...

Efficient Remainder Rule

ERIC Educational Resources Information Center

Firozzaman, Firoz; Firoz, Fahim

2017-01-01

Understanding the solution of a problem may require the reader to have background knowledge on the subject. For instance, finding an integer which, when divided by a nonzero integer leaves a remainder; but when divided by another nonzero integer may leave a different remainder. To find a smallest positive integer or a set of integers following the…

Point-Wise Phase Matching for Nonlinear Frequency Generation in Dielectric Resonators

NASA Technical Reports Server (NTRS)

Yu, Nan (Inventor); Strekalov, Dmitry V. (Inventor); Lin, Guoping (Inventor)

2016-01-01

An optical resonator fabricated from a uniaxial birefringent crystal, such as beta barium borate. The crystal is cut with the optical axis not perpendicular to a face of the cut crystal. In some cases the optical axis lies in the plane of the cut crystal face. An incident (input) electromagnetic signal (which can range from the infrared through the visible to the ultraviolet) is applied to the resonator. An output signal is recovered which has a frequency that is an integer multiple of the frequency of the input signal. In some cases a prism is used to evanescently couple the input and the output signals to the resonator.

Classification of the nonlinear dynamics and bifurcation structure of ultrasound contrast agents excited at higher multiples of their resonance frequency

NASA Astrophysics Data System (ADS)

Sojahrood, Amin Jafari; Kolios, Michael C.

2012-07-01

Through numerical simulation of the Hoff model we show that when ultrasound contrast agents (UCAs) are excited at frequencies which are close to integer (m>2) multiples of their natural resonance frequency, the bifurcation structure of the UCA oscillations as a function of pressure may be characterized by 3 general distinct regions. The UCA behavior starts with initial period one oscillations which undergoes a saddle node bifurcation to m coexisting attractors for an acoustic pressure above a threshold, P. Further increasing the pressure above a second threshold P, is followed by a sudden transition to period 1 oscillations.

Nonlinear Diophantine equation 11 x +13 y = z 2

NASA Astrophysics Data System (ADS)

Sugandha, A.; Tripena, A.; Prabowo, A.; Sukono, F.

2018-03-01

This research aims to obtaining the solutions (if any) from the Non Linear Diophantine equation of 11 x + 13 y = z 2. There are 3 possibilities to obtain the solutions (if any) from the Non Linear Diophantine equation, namely single, multiple, and no solution. This research is conducted in two stages: (1) by utilizing simulation to obtain the solutions (if any) from the Non Linear Diophantine equation of 11 x + 13 y = z 2 and (2) by utilizing congruency theory with its characteristics proven that the Non Linear Diophantine equation has no solution for non negative whole numbers (integers) of x, y, z.

Hybrid Nested Partitions and Math Programming Framework for Large-scale Combinatorial Optimization

DTIC Science & Technology

2010-03-31

optimization problems: 1) exact algorithms and 2) metaheuristic algorithms . This project will integrate concepts from these two technologies to develop...optimal solutions within an acceptable amount of computation time, and 2) metaheuristic algorithms such as genetic algorithms , tabu search, and the...integer programming decomposition approaches, such as Dantzig Wolfe decomposition and Lagrangian relaxation, and metaheuristics such as the Nested

Automated Test Assembly Using lp_Solve Version 5.5 in R

ERIC Educational Resources Information Center

Diao, Qi; van der Linden, Wim J.

2011-01-01

This article reviews the use of the software program lp_solve version 5.5 for solving mixed-integer automated test assembly (ATA) problems. The program is freely available under Lesser General Public License 2 (LGPL2). It can be called from the statistical language R using the lpSolveAPI interface. Three empirical problems are presented to…

47 CFR 1.2202 - Competitive bidding design options.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Section 1.2202 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Grants...) Procedures that utilize mathematical computer optimization software, such as integer programming, to evaluate... evaluating bids using a ranking based on specified factors. (B) Procedures that combine computer optimization...

SPECIES RICHNESS AND BIODIVERSITY CONSERVATION PRIORITIES IN BRITISH COLUMBIA

EPA Science Inventory

Patterns in the geographic distribution of seven species groups were used to identify important areas for conservation in British Columbia, Canada. Potential priority sites for conservation were determined using an integer programming algorithm that maximized the number of speci...

Selective Optimization

DTIC Science & Technology

2015-07-06

NUMBER 5b. GRANT NUMBER AFOSR FA9550-12-1-0154 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Shabbir Ahmed and Santanu S. Dey 5d. PROJECT NUMBER 5e. TASK...standard mixed-integer programming (MIP) formulations of selective optimization problems. While such formulations can be attacked by commercial...F33615-86-C-5169. 5b. GRANT NUMBER. Enter all grant numbers as they appear in the report, e.g. AFOSR-82-1234. 5c. PROGRAM ELEMENT NUMBER. Enter

Cost-aware request routing in multi-geography cloud data centres using software-defined networking

NASA Astrophysics Data System (ADS)

Yuan, Haitao; Bi, Jing; Li, Bo Hu; Tan, Wei

2017-03-01

Current geographically distributed cloud data centres (CDCs) require gigantic energy and bandwidth costs to provide multiple cloud applications to users around the world. Previous studies only focus on energy cost minimisation in distributed CDCs. However, a CDC provider needs to deliver gigantic data between users and distributed CDCs through internet service providers (ISPs). Geographical diversity of bandwidth and energy costs brings a highly challenging problem of how to minimise the total cost of a CDC provider. With the recently emerging software-defined networking, we study the total cost minimisation problem for a CDC provider by exploiting geographical diversity of energy and bandwidth costs. We formulate the total cost minimisation problem as a mixed integer non-linear programming (MINLP). Then, we develop heuristic algorithms to solve the problem and to provide a cost-aware request routing for joint optimisation of the selection of ISPs and the number of servers in distributed CDCs. Besides, to tackle the dynamic workload in distributed CDCs, this article proposes a regression-based workload prediction method to obtain future incoming workload. Finally, this work evaluates the cost-aware request routing by trace-driven simulation and compares it with the existing approaches to demonstrate its effectiveness.

Optimal synthesis and design of the number of cycles in the leaching process for surimi production.

PubMed

Reinheimer, M Agustina; Scenna, Nicolás J; Mussati, Sergio F

2016-12-01

Water consumption required during the leaching stage in the surimi manufacturing process strongly depends on the design and the number and size of stages connected in series for the soluble protein extraction target, and it is considered as the main contributor to the operating costs. Therefore, the optimal synthesis and design of the leaching stage is essential to minimize the total annual cost. In this study, a mathematical optimization model for the optimal design of the leaching operation is presented. Precisely, a detailed Mixed Integer Nonlinear Programming (MINLP) model including operating and geometric constraints was developed based on our previous optimization model (NLP model). Aspects about quality, water consumption and main operating parameters were considered. The minimization of total annual costs, which considered a trade-off between investment and operating costs, led to an optimal solution with lesser number of stages (2 instead of 3 stages) and higher volumes of the leaching tanks comparing with previous results. An analysis was performed in order to investigate how the optimal solution was influenced by the variations of the unitary cost of fresh water, waste treatment and capital investment.

Two models of inventory control with supplier selection in case of multiple sourcing: a case of Isfahan Steel Company

NASA Astrophysics Data System (ADS)

Rabieh, Masood; Soukhakian, Mohammad Ali; Mosleh Shirazi, Ali Naghi

2016-06-01

Selecting the best suppliers is crucial for a company's success. Since competition is a determining factor nowadays, reducing cost and increasing quality of products are two key criteria for appropriate supplier selection. In the study, first the inventories of agglomeration plant of Isfahan Steel Company were categorized through VED and ABC methods. Then the models to supply two important kinds of raw materials (inventories) were developed, considering the following items: (1) the optimal consumption composite of the materials, (2) the total cost of logistics, (3) each supplier's terms and conditions, (4) the buyer's limitations and (5) the consumption behavior of the buyers. Among diverse developed and tested models—using the company's actual data within three pervious years—the two new innovative models of mixed-integer non-linear programming type were found to be most suitable. The results of solving two models by lingo software (based on company's data in this particular case) were equaled. Comparing the results of the new models to the actual performance of the company revealed 10.9 and 7.1 % reduction in total procurement costs of the company in two consecutive years.

Design for life-cycle profit with simultaneous consideration of initial manufacturing and end-of-life remanufacturing

NASA Astrophysics Data System (ADS)

Kwak, Minjung; Kim, Harrison

2015-01-01

Remanufacturing is emerging as a promising solution for achieving green, profitable businesses. This article considers a manufacturer that produces new products and also remanufactured versions of the new products that become available at the end of their life cycle. For such a manufacturer, design decisions at the initial design stage determine both the current profit from manufacturing and future profit from remanufacturing. To maximize the total profit, design decisions must carefully consider both ends of product life cycle, i.e. manufacturing and end-of-life stages. This article proposes a decision-support model for the life-cycle design using mixed-integer nonlinear programming. With an aim to maximize the total life-cycle profit, the proposed model searches for an (at least locally) optimal product design (i.e. design specifications and the selling price) for the new and remanufactured products. It optimizes both the initial design and design upgrades at the end-of-life stage and also provides corresponding production strategies, including production quantities and take-back rate. The model is extended to a multi-objective model that maximizes both economic profit and environmental-impact saving. To illustrate, the developed model is demonstrated with an example of a desktop computer.

Cumulative Poisson Distribution Program

NASA Technical Reports Server (NTRS)

Bowerman, Paul N.; Scheuer, Ernest M.; Nolty, Robert

1990-01-01

Overflow and underflow in sums prevented. Cumulative Poisson Distribution Program, CUMPOIS, one of two computer programs that make calculations involving cumulative Poisson distributions. Both programs, CUMPOIS (NPO-17714) and NEWTPOIS (NPO-17715), used independently of one another. CUMPOIS determines cumulative Poisson distribution, used to evaluate cumulative distribution function (cdf) for gamma distributions with integer shape parameters and cdf for X (sup2) distributions with even degrees of freedom. Used by statisticians and others concerned with probabilities of independent events occurring over specific units of time, area, or volume. Written in C.

Optimal design of a gas transmission network: A case study of the Turkish natural gas pipeline network system

NASA Astrophysics Data System (ADS)

Gunes, Ersin Fatih

Turkey is located between Europe, which has increasing demand for natural gas and the geographies of Middle East, Asia and Russia, which have rich and strong natural gas supply. Because of the geographical location, Turkey has strategic importance according to energy sources. To supply this demand, a pipeline network configuration with the optimal and efficient lengths, pressures, diameters and number of compressor stations is extremely needed. Because, Turkey has a currently working and constructed network topology, obtaining an optimal configuration of the pipelines, including an optimal number of compressor stations with optimal locations, is the focus of this study. Identifying a network design with lowest costs is important because of the high maintenance and set-up costs. The quantity of compressor stations, the pipeline segments' lengths, the diameter sizes and pressures at compressor stations, are considered to be decision variables in this study. Two existing optimization models were selected and applied to the case study of Turkey. Because of the fixed cost of investment, both models are formulated as mixed integer nonlinear programs, which require branch and bound combined with the nonlinear programming solution methods. The differences between these two models are related to some factors that can affect the network system of natural gas such as wall thickness, material balance compressor isentropic head and amount of gas to be delivered. The results obtained by these two techniques are compared with each other and with the current system. Major differences between results are costs, pressures and flow rates. These solution techniques are able to find a solution with minimum cost for each model both of which are less than the current cost of the system while satisfying all the constraints on diameter, length, flow rate and pressure. These results give the big picture of an ideal configuration for the future state network for the country of Turkey.

Calibration of a stochastic health evolution model using NHIS data

NASA Astrophysics Data System (ADS)

Gupta, Aparna; Li, Zhisheng

2011-10-01

This paper presents and calibrates an individual's stochastic health evolution model. In this health evolution model, the uncertainty of health incidents is described by a stochastic process with a finite number of possible outcomes. We construct a comprehensive health status index (HSI) to describe an individual's health status, as well as a health risk factor system (RFS) to classify individuals into different risk groups. Based on the maximum likelihood estimation (MLE) method and the method of nonlinear least squares fitting, model calibration is formulated in terms of two mixed-integer nonlinear optimization problems. Using the National Health Interview Survey (NHIS) data, the model is calibrated for specific risk groups. Longitudinal data from the Health and Retirement Study (HRS) is used to validate the calibrated model, which displays good validation properties. The end goal of this paper is to provide a model and methodology, whose output can serve as a crucial component of decision support for strategic planning of health related financing and risk management.

Moving multiple sinks through wireless sensor networks for lifetime maximization.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrioli, Chiara; Carosi, Alessio; Basagni, Stefano

2008-01-01

Unattended sensor networks typically watch for some phenomena such as volcanic events, forest fires, pollution, or movements in animal populations. Sensors report to a collection point periodically or when they observe reportable events. When sensors are too far from the collection point to communicate directly, other sensors relay messages for them. If the collection point location is static, sensor nodes that are closer to the collection point relay far more messages than those on the periphery. Assuming all sensor nodes have roughly the same capabilities, those with high relay burden experience battery failure much faster than the rest of themore » network. However, since their death disconnects the live nodes from the collection point, the whole network is then dead. We consider the problem of moving a set of collectors (sinks) through a wireless sensor network to balance the energy used for relaying messages, maximizing the lifetime of the network. We show how to compute an upper bound on the lifetime for any instance using linear and integer programming. We present a centralized heuristic that produces sink movement schedules that produce network lifetimes within 1.4% of the upper bound for realistic settings. We also present a distributed heuristic that produces lifetimes at most 25:3% below the upper bound. More specifically, we formulate a linear program (LP) that is a relaxation of the scheduling problem. The variables are naturally continuous, but the LP relaxes some constraints. The LP has an exponential number of constraints, but we can satisfy them all by enforcing only a polynomial number using a separation algorithm. This separation algorithm is a p-median facility location problem, which we can solve efficiently in practice for huge instances using integer programming technology. This LP selects a set of good sensor configurations. Given the solution to the LP, we can find a feasible schedule by selecting a subset of these configurations, ordering them via a traveling salesman heuristic, and computing feasible transitions using matching algorithms. This algorithm assumes sinks can get a schedule from a central server or a leader sink. If the network owner prefers the sinks make independent decisions, they can use our distributed heuristic. In this heuristic, sinks maintain estimates of the energy distribution in the network and move greedily (with some coordination) based on local search. This application uses the new SUCASA (Solver Utility for Customization with Automatic Symbol Access) facility within the PICO (Parallel Integer and Combinatorial Optimizer) integer programming solver system. SUCASA allows rapid development of customized math programming (search-based) solvers using a problem's natural multidimensional representation. In this case, SUCASA also significantly improves runtime compared to implementations in the ampl math programming language or in perl.« less

Exact calculation of distributions on integers, with application to sequence alignment.

PubMed

Newberg, Lee A; Lawrence, Charles E

2009-01-01

Computational biology is replete with high-dimensional discrete prediction and inference problems. Dynamic programming recursions can be applied to several of the most important of these, including sequence alignment, RNA secondary-structure prediction, phylogenetic inference, and motif finding. In these problems, attention is frequently focused on some scalar quantity of interest, a score, such as an alignment score or the free energy of an RNA secondary structure. In many cases, score is naturally defined on integers, such as a count of the number of pairing differences between two sequence alignments, or else an integer score has been adopted for computational reasons, such as in the test of significance of motif scores. The probability distribution of the score under an appropriate probabilistic model is of interest, such as in tests of significance of motif scores, or in calculation of Bayesian confidence limits around an alignment. Here we present three algorithms for calculating the exact distribution of a score of this type; then, in the context of pairwise local sequence alignments, we apply the approach so as to find the alignment score distribution and Bayesian confidence limits.

Center for Parallel Optimization

DTIC Science & Technology

1993-09-30

BOLLING AFB DC 20332-0001 _ii _ 11. SUPPLEMENTARY NOTES 12a. DISTRIBUTION/ AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE APPROVED FOR PUBLIC RELEASE...Machines Corporation, March 16-19, 1993 , A Branch- and-Bound Method for Mixed Integer Programming on the CM-.5 "* Dr. Roberto Musmanno, University of

Topics

ERIC Educational Resources Information Center

Mathematics Teaching, 1973

1973-01-01

This column includes the description of a game involving addition and subtraction of integers represented by colored bricks, a general formula for an enlargement in the Cartesian plane, an analysis of the possibilities for certain games of board Solitaire, and a BASIC program for a recreational mathematics problem. (DT)

Distributing Earthquakes Among California's Faults: A Binary Integer Programming Approach

NASA Astrophysics Data System (ADS)

Geist, E. L.; Parsons, T.

2016-12-01

Statement of the problem is simple: given regional seismicity specified by a Gutenber-Richter (G-R) relation, how are earthquakes distributed to match observed fault-slip rates? The objective is to determine the magnitude-frequency relation on individual faults. The California statewide G-R b-value and a-value are estimated from historical seismicity, with the a-value accounting for off-fault seismicity. UCERF3 consensus slip rates are used, based on geologic and geodetic data and include estimates of coupling coefficients. The binary integer programming (BIP) problem is set up such that each earthquake from a synthetic catalog spanning millennia can occur at any location along any fault. The decision vector, therefore, consists of binary variables, with values equal to one indicating the location of each earthquake that results in an optimal match of slip rates, in an L1-norm sense. Rupture area and slip associated with each earthquake are determined from a magnitude-area scaling relation. Uncertainty bounds on the UCERF3 slip rates provide explicit minimum and maximum constraints to the BIP model, with the former more important to feasibility of the problem. There is a maximum magnitude limit associated with each fault, based on fault length, providing an implicit constraint. Solution of integer programming problems with a large number of variables (>105 in this study) has been possible only since the late 1990s. In addition to the classic branch-and-bound technique used for these problems, several other algorithms have been recently developed, including pre-solving, sifting, cutting planes, heuristics, and parallelization. An optimal solution is obtained using a state-of-the-art BIP solver for M≥6 earthquakes and California's faults with slip-rates > 1 mm/yr. Preliminary results indicate a surprising diversity of on-fault magnitude-frequency relations throughout the state.

Newton/Poisson-Distribution Program

NASA Technical Reports Server (NTRS)

Bowerman, Paul N.; Scheuer, Ernest M.

1990-01-01

NEWTPOIS, one of two computer programs making calculations involving cumulative Poisson distributions. NEWTPOIS (NPO-17715) and CUMPOIS (NPO-17714) used independently of one another. NEWTPOIS determines Poisson parameter for given cumulative probability, from which one obtains percentiles for gamma distributions with integer shape parameters and percentiles for X(sup2) distributions with even degrees of freedom. Used by statisticians and others concerned with probabilities of independent events occurring over specific units of time, area, or volume. Program written in C.

Integers as Transformations.

ERIC Educational Resources Information Center

Thompson, Patrick W.; Dreyfus, Tommy

1988-01-01

Investigates whether elementary school students can construct operations of thought for integers and integer addition crucial for understanding elementary algebra. Two sixth graders were taught using a computer. Results included both students being able to construct mental operations for negating arbitrary integers and determining sign and…

Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study

PubMed Central

Catanzaro, Daniele; Schäffer, Alejandro A.; Schwartz, Russell

2016-01-01

Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with Synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints. PMID:26353381

A mathematical model for municipal solid waste management - A case study in Hong Kong.

PubMed

Lee, C K M; Yeung, C L; Xiong, Z R; Chung, S H

2016-12-01

With the booming economy and increasing population, the accumulation of waste has become an increasingly arduous issue and has aroused the attention from all sectors of society. Hong Kong which has a relative high daily per capita domestic waste generation rate in Asia has not yet established a comprehensive waste management system. This paper conducts a review of waste management approaches and models. Researchers highlight that mathematical models provide useful information for decision-makers to select appropriate choices and save cost. It is suggested to consider municipal solid waste management in a holistic view and improve the utilization of waste management infrastructures. A mathematical model which adopts integer linear programming and mixed integer programming has been developed for Hong Kong municipal solid waste management. A sensitivity analysis was carried out to simulate different scenarios which provide decision-makers important information for establishing Hong Kong waste management system. Copyright © 2016 Elsevier Ltd. All rights reserved.

A new mathematical modeling for pure parsimony haplotyping problem.

PubMed

Feizabadi, R; Bagherian, M; Vaziri, H R; Salahi, M

2016-11-01

Pure parsimony haplotyping (PPH) problem is important in bioinformatics because rational haplotyping inference plays important roles in analysis of genetic data, mapping complex genetic diseases such as Alzheimer's disease, heart disorders and etc. Haplotypes and genotypes are m-length sequences. Although several integer programing models have already been presented for PPH problem, its NP-hardness characteristic resulted in ineffectiveness of those models facing the real instances especially instances with many heterozygous sites. In this paper, we assign a corresponding number to each haplotype and genotype and based on those numbers, we set a mixed integer programing model. Using numbers, instead of sequences, would lead to less complexity of the new model in comparison with previous models in a way that there are neither constraints nor variables corresponding to heterozygous nucleotide sites in it. Experimental results approve the efficiency of the new model in producing better solution in comparison to two state-of-the art haplotyping approaches. Copyright © 2016 Elsevier Inc. All rights reserved.

Discovering Link Communities in Complex Networks by an Integer Programming Model and a Genetic Algorithm

PubMed Central

Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua

2013-01-01

Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks. PMID:24386268

Integer Linear Programming for Constrained Multi-Aspect Committee Review Assignment

PubMed Central

Karimzadehgan, Maryam; Zhai, ChengXiang

2011-01-01

Automatic review assignment can significantly improve the productivity of many people such as conference organizers, journal editors and grant administrators. A general setup of the review assignment problem involves assigning a set of reviewers on a committee to a set of documents to be reviewed under the constraint of review quota so that the reviewers assigned to a document can collectively cover multiple topic aspects of the document. No previous work has addressed such a setup of committee review assignments while also considering matching multiple aspects of topics and expertise. In this paper, we tackle the problem of committee review assignment with multi-aspect expertise matching by casting it as an integer linear programming problem. The proposed algorithm can naturally accommodate any probabilistic or deterministic method for modeling multiple aspects to automate committee review assignments. Evaluation using a multi-aspect review assignment test set constructed using ACM SIGIR publications shows that the proposed algorithm is effective and efficient for committee review assignments based on multi-aspect expertise matching. PMID:22711970

A robust multi-objective global supplier selection model under currency fluctuation and price discount

NASA Astrophysics Data System (ADS)

Zarindast, Atousa; Seyed Hosseini, Seyed Mohamad; Pishvaee, Mir Saman

2017-06-01

Robust supplier selection problem, in a scenario-based approach has been proposed, when the demand and exchange rates are subject to uncertainties. First, a deterministic multi-objective mixed integer linear programming is developed; then, the robust counterpart of the proposed mixed integer linear programming is presented using the recent extension in robust optimization theory. We discuss decision variables, respectively, by a two-stage stochastic planning model, a robust stochastic optimization planning model which integrates worst case scenario in modeling approach and finally by equivalent deterministic planning model. The experimental study is carried out to compare the performances of the three models. Robust model resulted in remarkable cost saving and it illustrated that to cope with such uncertainties, we should consider them in advance in our planning. In our case study different supplier were selected due to this uncertainties and since supplier selection is a strategic decision, it is crucial to consider these uncertainties in planning approach.

Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study.

PubMed

Catanzaro, Daniele; Shackney, Stanley E; Schaffer, Alejandro A; Schwartz, Russell

2016-01-01

Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints.

A supplier selection and order allocation problem with stochastic demands

NASA Astrophysics Data System (ADS)

Zhou, Yun; Zhao, Lei; Zhao, Xiaobo; Jiang, Jianhua

2011-08-01

We consider a system comprising a retailer and a set of candidate suppliers that operates within a finite planning horizon of multiple periods. The retailer replenishes its inventory from the suppliers and satisfies stochastic customer demands. At the beginning of each period, the retailer makes decisions on the replenishment quantity, supplier selection and order allocation among the selected suppliers. An optimisation problem is formulated to minimise the total expected system cost, which includes an outer level stochastic dynamic program for the optimal replenishment quantity and an inner level integer program for supplier selection and order allocation with a given replenishment quantity. For the inner level subproblem, we develop a polynomial algorithm to obtain optimal decisions. For the outer level subproblem, we propose an efficient heuristic for the system with integer-valued inventory, based on the structural properties of the system with real-valued inventory. We investigate the efficiency of the proposed solution approach, as well as the impact of parameters on the optimal replenishment decision with numerical experiments.

Galaxy Redshifts from Discrete Optimization of Correlation Functions

NASA Astrophysics Data System (ADS)

Lee, Benjamin C. G.; Budavári, Tamás; Basu, Amitabh; Rahman, Mubdi

2016-12-01

We propose a new method of constraining the redshifts of individual extragalactic sources based on celestial coordinates and their ensemble statistics. Techniques from integer linear programming (ILP) are utilized to optimize simultaneously for the angular two-point cross- and autocorrelation functions. Our novel formalism introduced here not only transforms the otherwise hopelessly expensive, brute-force combinatorial search into a linear system with integer constraints but also is readily implementable in off-the-shelf solvers. We adopt Gurobi, a commercial optimization solver, and use Python to build the cost function dynamically. The preliminary results on simulated data show potential for future applications to sky surveys by complementing and enhancing photometric redshift estimators. Our approach is the first application of ILP to astronomical analysis.

Non-integer viscoelastic constitutive law to model soft biological tissues to in-vivo indentation.

PubMed

Demirci, Nagehan; Tönük, Ergin

2014-01-01

During the last decades, derivatives and integrals of non-integer orders are being more commonly used for the description of constitutive behavior of various viscoelastic materials including soft biological tissues. Compared to integer order constitutive relations, non-integer order viscoelastic material models of soft biological tissues are capable of capturing a wider range of viscoelastic behavior obtained from experiments. Although integer order models may yield comparably accurate results, non-integer order material models have less number of parameters to be identified in addition to description of an intermediate material that can monotonically and continuously be adjusted in between an ideal elastic solid and an ideal viscous fluid. In this work, starting with some preliminaries on non-integer (fractional) calculus, the "spring-pot", (intermediate mechanical element between a solid and a fluid), non-integer order three element (Zener) solid model, finally a user-defined large strain non-integer order viscoelastic constitutive model was constructed to be used in finite element simulations. Using the constitutive equation developed, by utilizing inverse finite element method and in vivo indentation experiments, soft tissue material identification was performed. The results indicate that material coefficients obtained from relaxation experiments, when optimized with creep experimental data could simulate relaxation, creep and cyclic loading and unloading experiments accurately. Non-integer calculus viscoelastic constitutive models, having physical interpretation and modeling experimental data accurately is a good alternative to classical phenomenological viscoelastic constitutive equations.

Fast Integer Ambiguity Resolution for GPS Attitude Determination

NASA Technical Reports Server (NTRS)

Lightsey, E. Glenn; Crassidis, John L.; Markley, F. Landis

1999-01-01

In this paper, a new algorithm for GPS (Global Positioning System) integer ambiguity resolution is shown. The algorithm first incorporates an instantaneous (static) integer search to significantly reduce the search space using a geometric inequality. Then a batch-type loss function is used to check the remaining integers in order to determine the optimal integer. This batch function represents the GPS sightline vectors in the body frame as the sum of two vectors, one depending on the phase measurements and the other on the unknown integers. The new algorithm has several advantages: it does not require an a-priori estimate of the vehicle's attitude; it provides an inherent integrity check using a covariance-type expression; and it can resolve the integers even when coplanar baselines exist. The performance of the new algorithm is tested on a dynamic hardware simulator.

Charge of a quasiparticle in a superconductor

PubMed Central

Ronen, Yuval; Cohen, Yonatan; Kang, Jung-Hyun; Haim, Arbel; Rieder, Maria-Theresa; Heiblum, Moty; Mahalu, Diana; Shtrikman, Hadas

2016-01-01

Nonlinear charge transport in superconductor–insulator–superconductor (SIS) Josephson junctions has a unique signature in the shuttled charge quantum between the two superconductors. In the zero-bias limit Cooper pairs, each with twice the electron charge, carry the Josephson current. An applied bias VSD leads to multiple Andreev reflections (MAR), which in the limit of weak tunneling probability should lead to integer multiples of the electron charge ne traversing the junction, with n integer larger than 2Δ/eVSD and Δ the superconducting order parameter. Exceptionally, just above the gap eVSD ≥ 2Δ, with Andreev reflections suppressed, one would expect the current to be carried by partitioned quasiparticles, each with energy-dependent charge, being a superposition of an electron and a hole. Using shot-noise measurements in an SIS junction induced in an InAs nanowire (with noise proportional to the partitioned charge), we first observed quantization of the partitioned charge q = e*/e=n, with n = 1–4, thus reaffirming the validity of our charge interpretation. Concentrating next on the bias region eVSD∼2Δ, we found a reproducible and clear dip in the extracted charge to q ∼0.6, which, after excluding other possibilities, we attribute to the partitioned quasiparticle charge. Such dip is supported by numerical simulations of our SIS structure. PMID:26831071

Charge of a quasiparticle in a superconductor.

PubMed

Ronen, Yuval; Cohen, Yonatan; Kang, Jung-Hyun; Haim, Arbel; Rieder, Maria-Theresa; Heiblum, Moty; Mahalu, Diana; Shtrikman, Hadas

2016-02-16

Nonlinear charge transport in superconductor-insulator-superconductor (SIS) Josephson junctions has a unique signature in the shuttled charge quantum between the two superconductors. In the zero-bias limit Cooper pairs, each with twice the electron charge, carry the Josephson current. An applied bias VSD leads to multiple Andreev reflections (MAR), which in the limit of weak tunneling probability should lead to integer multiples of the electron charge ne traversing the junction, with n integer larger than 2Δ/eVSD and Δ the superconducting order parameter. Exceptionally, just above the gap eVSD ≥ 2Δ, with Andreev reflections suppressed, one would expect the current to be carried by partitioned quasiparticles, each with energy-dependent charge, being a superposition of an electron and a hole. Using shot-noise measurements in an SIS junction induced in an InAs nanowire (with noise proportional to the partitioned charge), we first observed quantization of the partitioned charge q = e*/e = n, with n = 1-4, thus reaffirming the validity of our charge interpretation. Concentrating next on the bias region eVSD ~ 2Δ, we found a reproducible and clear dip in the extracted charge to q ~ 0.6, which, after excluding other possibilities, we attribute to the partitioned quasiparticle charge. Such dip is supported by numerical simulations of our SIS structure.

Observation of electromagnetically induced Talbot effect in an atomic system

NASA Astrophysics Data System (ADS)

Zhang, Zhaoyang; Liu, Xing; Zhang, Dan; Sheng, Jiteng; Zhang, Yiqi; Zhang, Yanpeng; Xiao, Min

2018-01-01

The electromagnetically induced Talbot effect (EITE) resulting from the repeated self-reconstruction of a spatially intensity-modulated probe field is experimentally demonstrated in a three-level atomic configuration. The probe beam is launched into an optically induced lattice (established by the interference of two coupling fields) inside a rubidium vapor cell and is diffracted by the electromagnetically induced grating that was formed. The diffraction pattern repeats itself at the planes of integer multiple Talbot lengths. In addition, a fractional EITE is also investigated. The experimental observations agree well with the theoretical predictions. This investigation may potentially pave the way for studying the nonlinear and quantum dynamical features that have been predicted for established periodic optical systems.

Elliptic net and its cryptographic application

NASA Astrophysics Data System (ADS)

Muslim, Norliana; Said, Mohamad Rushdan Md

2017-11-01

Elliptic net is a generalization of elliptic divisibility sequence and in cryptography field, most cryptographic pairings that are based on elliptic curve such as Tate pairing can be improved by applying elliptic nets algorithm. The elliptic net is constructed by using n dimensional array of values in rational number satisfying nonlinear recurrence relations that arise from elliptic divisibility sequences. The two main properties hold in the recurrence relations are for all positive integers m>n, hm +nhm -n=hm +1hm -1hn2-hn +1hn -1hm2 and hn divides hm whenever n divides m. In this research, we discuss elliptic divisibility sequence associated with elliptic nets based on cryptographic perspective and its possible research direction.

On Distributed PV Hosting Capacity Estimation, Sensitivity Study, and Improvement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Fei; Mather, Barry

This paper first studies the estimated distributed PV hosting capacities of seventeen utility distribution feeders using the Monte Carlo simulation based stochastic analysis, and then analyzes the sensitivity of PV hosting capacity to both feeder and photovoltaic system characteristics. Furthermore, an active distribution network management approach is proposed to maximize PV hosting capacity by optimally switching capacitors, adjusting voltage regulator taps, managing controllable branch switches and controlling smart PV inverters. The approach is formulated as a mixed-integer nonlinear optimization problem and a genetic algorithm is developed to obtain the solution. Multiple simulation cases are studied and the effectiveness of themore » proposed approach on increasing PV hosting capacity is demonstrated.« less

A class of traveling wave solutions for space-time fractional biological population model in mathematical physics

NASA Astrophysics Data System (ADS)

Akram, Ghazala; Batool, Fiza

2017-10-01

The (G'/G)-expansion method is utilized for a reliable treatment of space-time fractional biological population model. The method has been applied in the sense of the Jumarie's modified Riemann-Liouville derivative. Three classes of exact traveling wave solutions, hyperbolic, trigonometric and rational solutions of the associated equation are characterized with some free parameters. A generalized fractional complex transform is applied to convert the fractional equations to ordinary differential equations which subsequently resulted in number of exact solutions. It should be mentioned that the (G'/G)-expansion method is very effective and convenient for solving nonlinear partial differential equations of fractional order whose balancing number is a negative integer.

Joint image encryption and compression scheme based on IWT and SPIHT

NASA Astrophysics Data System (ADS)

Zhang, Miao; Tong, Xiaojun

2017-03-01

A joint lossless image encryption and compression scheme based on integer wavelet transform (IWT) and set partitioning in hierarchical trees (SPIHT) is proposed to achieve lossless image encryption and compression simultaneously. Making use of the properties of IWT and SPIHT, encryption and compression are combined. Moreover, the proposed secure set partitioning in hierarchical trees (SSPIHT) via the addition of encryption in the SPIHT coding process has no effect on compression performance. A hyper-chaotic system, nonlinear inverse operation, Secure Hash Algorithm-256(SHA-256), and plaintext-based keystream are all used to enhance the security. The test results indicate that the proposed methods have high security and good lossless compression performance.

Optimal Design and Operation of Permanent Irrigation Systems

NASA Astrophysics Data System (ADS)

Oron, Gideon; Walker, Wynn R.

1981-01-01

Solid-set pressurized irrigation system design and operation are studied with optimization techniques to determine the minimum cost distribution system. The principle of the analysis is to divide the irrigation system into subunits in such a manner that the trade-offs among energy, piping, and equipment costs are selected at the minimum cost point. The optimization procedure involves a nonlinear, mixed integer approach capable of achieving a variety of optimal solutions leading to significant conclusions with regard to the design and operation of the system. Factors investigated include field geometry, the effect of the pressure head, consumptive use rates, a smaller flow rate in the pipe system, and outlet (sprinkler or emitter) discharge.

Learning Integer Addition: Is Later Better?

ERIC Educational Resources Information Center

Aqazade, Mahtob; Bofferding, Laura; Farmer, Sherri

2017-01-01

We investigate thirty-three second and fifth-grade students' solution strategies on integer addition problems before and after analyzing contrasting cases with integer addition and participating in a lesson on integers. The students took a pretest, participated in two small group sessions and a short lesson, and took a posttest. Even though the…

Online with Integers

ERIC Educational Resources Information Center

Siegel, Jonathan W.; Siegel, P. B.

2011-01-01

Integers are sometimes used in physics problems to simplify the mathematics so the arithmetic does not distract students from the physics concepts. This is particularly important in exams where students should not have to spend a lot of time using their calculators. Common uses of integers in physics problems include integer solutions to…

Integers Made Easy: Just Walk It Off

ERIC Educational Resources Information Center

Nurnberger-Haag, Julie

2007-01-01

This article describes a multisensory method for teaching students how to multiply and divide as well as add and subtract integers. The author uses sidewalk chalk and the underlying concept of integers to physically and mentally engage students in understanding the concepts of integers, making connections, and developing computational fluency.…

Optimally Scheduling Basic Courses at the Defense Language Institute using Integer Programming

DTIC Science & Technology

2005-09-01

DLI’s manual schedules at best can train 8%, 7% and 64%. 15. NUMBER OF PAGES 59 14. SUBJECT TERMS Operations Research, Linear Programming...class in 2006, 2007, and 2008, whereas DLI’s manual schedules at best can train 8%, 7% and 64%. vi THIS PAGE...ARABIC INSTRUTOR LEVELS .....................................25 FIGURE 2. OCS1 AND OCS2 CHINESE-MANDARIN INSTRUTOR LEVELS ............26 FIGURE 3

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

NASA Astrophysics Data System (ADS)

Ozoe, Shunsuke; Tanaka, Yoichi; Fukushima, Masao

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.

Making Sense of Integer Arithmetic: The Effect of Using Virtual Manipulatives on Students' Representational Fluency

ERIC Educational Resources Information Center

Bolyard, Johnna; Moyer-Packenham, Patricia

2012-01-01

This study investigated how the use of virtual manipulatives in integer instruction impacts student achievement for integer addition and subtraction. Of particular interest was the influence of using virtual manipulatives on students' ability to create and translate among representations for integer computation. The research employed a…

Teachers' Construction of Meanings of Signed Quantities and Integer Operation

ERIC Educational Resources Information Center

Kumar, Ruchi S.; Subramaniam, K.; Naik, Shweta Shripad

2017-01-01

Understanding signed quantities and its arithmetic is one of the challenging topics of middle school mathematics. The "specialized content knowledge" (SCK) for teaching integers includes understanding of a variety of representations that may be used while teaching. In this study, we argue that meanings of integers and integer operations…

Anisotropic fractal media by vector calculus in non-integer dimensional space

NASA Astrophysics Data System (ADS)

Tarasov, Vasily E.

2014-08-01

A review of different approaches to describe anisotropic fractal media is proposed. In this paper, differentiation and integration non-integer dimensional and multi-fractional spaces are considered as tools to describe anisotropic fractal materials and media. We suggest a generalization of vector calculus for non-integer dimensional space by using a product measure method. The product of fractional and non-integer dimensional spaces allows us to take into account the anisotropy of the fractal media in the framework of continuum models. The integration over non-integer-dimensional spaces is considered. In this paper differential operators of first and second orders for fractional space and non-integer dimensional space are suggested. The differential operators are defined as inverse operations to integration in spaces with non-integer dimensions. Non-integer dimensional space that is product of spaces with different dimensions allows us to give continuum models for anisotropic type of the media. The Poisson's equation for fractal medium, the Euler-Bernoulli fractal beam, and the Timoshenko beam equations for fractal material are considered as examples of application of suggested generalization of vector calculus for anisotropic fractal materials and media.

Bi-Objective Modelling for Hazardous Materials Road–Rail Multimodal Routing Problem with Railway Schedule-Based Space–Time Constraints

PubMed Central

Sun, Yan; Lang, Maoxiang; Wang, Danzhu

2016-01-01

The transportation of hazardous materials is always accompanied by considerable risk that will impact public and environment security. As an efficient and reliable transportation organization, a multimodal service should participate in the transportation of hazardous materials. In this study, we focus on transporting hazardous materials through the multimodal service network and explore the hazardous materials multimodal routing problem from the operational level of network planning. To formulate this problem more practicably, minimizing the total generalized costs of transporting the hazardous materials and the social risk along the planned routes are set as the optimization objectives. Meanwhile, the following formulation characteristics will be comprehensively modelled: (1) specific customer demands; (2) multiple hazardous material flows; (3) capacitated schedule-based rail service and uncapacitated time-flexible road service; and (4) environmental risk constraint. A bi-objective mixed integer nonlinear programming model is first built to formulate the routing problem that combines the formulation characteristics above. Then linear reformations are developed to linearize and improve the initial model so that it can be effectively solved by exact solution algorithms on standard mathematical programming software. By utilizing the normalized weighted sum method, we can generate the Pareto solutions to the bi-objective optimization problem for a specific case. Finally, a large-scale empirical case study from the Beijing–Tianjin–Hebei Region in China is presented to demonstrate the feasibility of the proposed methods in dealing with the practical problem. Various scenarios are also discussed in the case study. PMID:27483294

Dynamic Allocation of SPM Based on Time-Slotted Cache Conflict Graph for System Optimization

NASA Astrophysics Data System (ADS)

Wu, Jianping; Ling, Ming; Zhang, Yang; Mei, Chen; Wang, Huan

This paper proposes a novel dynamic Scratch-pad Memory allocation strategy to optimize the energy consumption of the memory sub-system. Firstly, the whole program execution process is sliced into several time slots according to the temporal dimension; thereafter, a Time-Slotted Cache Conflict Graph (TSCCG) is introduced to model the behavior of Data Cache (D-Cache) conflicts within each time slot. Then, Integer Nonlinear Programming (INP) is implemented, which can avoid time-consuming linearization process, to select the most profitable data pages. Virtual Memory System (VMS) is adopted to remap those data pages, which will cause severe Cache conflicts within a time slot, to SPM. In order to minimize the swapping overhead of dynamic SPM allocation, a novel SPM controller with a tightly coupled DMA is introduced to issue the swapping operations without CPU's intervention. Last but not the least, this paper discusses the fluctuation of system energy profit based on different MMU page size as well as the Time Slot duration quantitatively. According to our design space exploration, the proposed method can optimize all of the data segments, including global data, heap and stack data in general, and reduce the total energy consumption by 27.28% on average, up to 55.22% with a marginal performance promotion. And comparing to the conventional static CCG (Cache Conflicts Graph), our approach can obtain 24.7% energy profit on average, up to 30.5% with a sight boost in performance.

Multi-vehicle mobility allowance shuttle transit (MAST) system : an analytical model to select the fleet size and a scheduling heuristic.

DOT National Transportation Integrated Search

2012-06-01

The mobility allowance shuttle transit (MAST) system is a hybrid transit system in which vehicles are : allowed to deviate from a fixed route to serve flexible demand. A mixed integer programming (MIP) : formulation for the static scheduling problem ...

A Graphical Teaching Tool for Understanding Two's Complement.

ERIC Educational Resources Information Center

Luck, Carlos L.

As part of the Electrical Engineering program at the Univesity of Southern Maine, students are typically introduced to Two's Complement algebra and representation, a method to include negative numbers in the binary representation of integers that is widely used in microprocessors and related digital systems. The traditional, procedural method to…

Space tug economic analysis study. Volume 2: Tug concepts analysis. Part 2: Economic analysis

NASA Technical Reports Server (NTRS)

1972-01-01

An economic analysis of space tug operations is presented. The subjects discussed are: (1) cost uncertainties, (2) scenario analysis, (3) economic sensitivities, (4) mixed integer programming formulation of the space tug problem, and (5) critical parameters in the evaluation of a public expenditure.

Optimizing efficiency of height modeling for extensive forest inventories.

Treesearch

T.M. Barrett

2006-01-01

Although critical to monitoring forest ecosystems, inventories are expensive. This paper presents a generalizable method for using an integer programming model to examine tradeoffs between cost and estimation error for alternative measurement strategies in forest inventories. The method is applied to an example problem of choosing alternative height-modeling strategies...

Selecting Personal Computers.

ERIC Educational Resources Information Center

Djang, Philipp A.

1993-01-01

Describes a Multiple Criteria Decision Analysis Approach for the selection of personal computers that combines the capabilities of Analytic Hierarchy Process and Integer Goal Programing. An example of how decision makers can use this approach to determine what kind of personal computers and how many of each type to purchase is given. (nine…

Integrated Sensing and Processing (ISP) Phase II: Demonstration and Evaluation for Distributed Sensor Netowrks and Missile Seeker Systems

DTIC Science & Technology

2007-02-28

Shah, D. Waagen, H. Schmitt, S. Bellofiore, A. Spanias, and D. Cochran, 32nd International Conference on Acoustics, Speech , and Signal Processing...Information Exploitation Office kNN k-Nearest Neighbor LEAN Laplacian Eigenmap Adaptive Neighbor LIP Linear Integer Programming ISP

INFORM: An interactive data collection and display program with debugging capability

NASA Technical Reports Server (NTRS)

Cwynar, D. S.

1980-01-01

A computer program was developed to aid ASSEMBLY language programmers of mini and micro computers in solving the man machine communications problems that exist when scaled integers are involved. In addition to producing displays of quasi-steady state values, INFORM provides an interactive mode for debugging programs, making program patches, and modifying the displays. Auxiliary routines SAMPLE and DATAO add dynamic data acquisition and high speed dynamic display capability to the program. Programming information and flow charts to aid in implementing INFORM on various machines together with descriptions of all supportive software are provided. Program modifications to satisfy the individual user's needs are considered.

Classification and disease prediction via mathematical programming

NASA Astrophysics Data System (ADS)

Lee, Eva K.; Wu, Tsung-Lin

2007-11-01

In this chapter, we present classification models based on mathematical programming approaches. We first provide an overview on various mathematical programming approaches, including linear programming, mixed integer programming, nonlinear programming and support vector machines. Next, we present our effort of novel optimization-based classification models that are general purpose and suitable for developing predictive rules for large heterogeneous biological and medical data sets. Our predictive model simultaneously incorporates (1) the ability to classify any number of distinct groups; (2) the ability to incorporate heterogeneous types of attributes as input; (3) a high-dimensional data transformation that eliminates noise and errors in biological data; (4) the ability to incorporate constraints to limit the rate of misclassification, and a reserved-judgment region that provides a safeguard against over-training (which tends to lead to high misclassification rates from the resulting predictive rule) and (5) successive multi-stage classification capability to handle data points placed in the reserved judgment region. To illustrate the power and flexibility of the classification model and solution engine, and its multigroup prediction capability, application of the predictive model to a broad class of biological and medical problems is described. Applications include: the differential diagnosis of the type of erythemato-squamous diseases; predicting presence/absence of heart disease; genomic analysis and prediction of aberrant CpG island meythlation in human cancer; discriminant analysis of motility and morphology data in human lung carcinoma; prediction of ultrasonic cell disruption for drug delivery; identification of tumor shape and volume in treatment of sarcoma; multistage discriminant analysis of biomarkers for prediction of early atherosclerois; fingerprinting of native and angiogenic microvascular networks for early diagnosis of diabetes, aging, macular degeneracy and tumor metastasis; prediction of protein localization sites; and pattern recognition of satellite images in classification of soil types. In all these applications, the predictive model yields correct classification rates ranging from 80% to 100%. This provides motivation for pursuing its use as a medical diagnostic, monitoring and decision-making tool.

Handling Nonlinearities in ELF/VLF Generation Using Modulated Heating at HAARP

NASA Astrophysics Data System (ADS)

Jin, G.; Spasojevic, M.; Cohen, M.; Inan, U. S.

2011-12-01

George Jin Maria Spasojevic Morris Cohen Umran Inan Stanford University Modulated HF heating of the D-region ionosphere near the auroral electrojet can generate extremely low frequency (ELF) waves in the kilohertz range. This process is nonlinear and generates harmonics at integer multiples of the ELF modulation frequency. The nonlinear distortion has implications for any communications applications since the harmonics contain a substantial fraction of the signal power and use up bandwidth. We examine two techniques for handling the nonlinearity. First we modulate the HF heating with a non-sinusoidal envelope designed to create a sinusoidal change in the Hall conductivity at a particular altitude in the ionosphere to minimize any generated harmonics. The modulation waveform is generated by inverting a numerical HF heating model, starting from the desired conductivity time series, and obtaining the HF power envelope that will result in that conductivity. The second technique attempts to use the energy in the harmonics to improve bit error rates when digital modulation is applied to the ELF carrier. In conventional quadrature phase-shift keying (QPSK), where a ELF carrier is phase-shifted by 0°, 90°, 180°, and 270° in order to transmit a pair of bits, the even harmonics cannot distinguish between the four possible shifts. By using different phase values, all the energy in the harmonics can contribute to determining the phase of the carrier and thus improve the bit error rate.

Software Technology for Adaptable, Reliable Systems (STARS) (User Manual). Ada Command Environment (ACE) Version 8.0 Sun OS Implementation

DTIC Science & Technology

1990-10-29

the equivalent type names in the basic X libary . 37. Intrinsics Contains the type declarations common to all Xt toolkit routines. 38. Widget-Package...Memory-Size constant Integer 1; MinInt constant I-reger Integer’First; MaxInt const-i’ integer Integer’Last; -- Max- Digits constant Integer 1; -- MaxMan...connection between some type names used by Xt routines and the equivalent type names in the basic X libary . .package RenamedXlibTypes is P;’ge 65 29

CUMBIN - CUMULATIVE BINOMIAL PROGRAMS

NASA Technical Reports Server (NTRS)

Bowerman, P. N.

1994-01-01

The cumulative binomial program, CUMBIN, is one of a set of three programs which calculate cumulative binomial probability distributions for arbitrary inputs. The three programs, CUMBIN, NEWTONP (NPO-17556), and CROSSER (NPO-17557), can be used independently of one another. CUMBIN can be used by statisticians and users of statistical procedures, test planners, designers, and numerical analysts. The program has been used for reliability/availability calculations. CUMBIN calculates the probability that a system of n components has at least k operating if the probability that any one operating is p and the components are independent. Equivalently, this is the reliability of a k-out-of-n system having independent components with common reliability p. CUMBIN can evaluate the incomplete beta distribution for two positive integer arguments. CUMBIN can also evaluate the cumulative F distribution and the negative binomial distribution, and can determine the sample size in a test design. CUMBIN is designed to work well with all integer values 0 < k <= n. To run the program, the user simply runs the executable version and inputs the information requested by the program. The program is not designed to weed out incorrect inputs, so the user must take care to make sure the inputs are correct. Once all input has been entered, the program calculates and lists the result. The CUMBIN program is written in C. It was developed on an IBM AT with a numeric co-processor using Microsoft C 5.0. Because the source code is written using standard C structures and functions, it should compile correctly with most C compilers. The program format is interactive. It has been implemented under DOS 3.2 and has a memory requirement of 26K. CUMBIN was developed in 1988.

Operational Planning for Multiple Heterogeneous Unmanned Aerial Vehicles in Three Dimensions

DTIC Science & Technology

2009-06-01

human input in the planning process. Two solution methods are presented: (1) a mixed-integer program, and (2) an algorithm that utilizes a metaheuristic ...and (2) an algorithm that utilizes a metaheuristic to generate composite variables for a linear program, called the Composite Operations Planning...that represent a path and an associated type of UAV. The reformulation is incorporated into an algorithm that uses a metaheuristic to generate the

Forest management and economics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buongiorno, J.; Gilless, J.K.

1987-01-01

This volume provides a survey of quantitative methods, guiding the reader through formulation and analysis of models that address forest management problems. The authors use simple mathematics, graphics, and short computer programs to explain each method. Emphasizing applications, they discuss linear, integer, dynamic, and goal programming; simulation; network modeling; and econometrics, as these relate to problems of determining economic harvest schedules in even-aged and uneven-aged forests, the evaluation of forest policies, multiple-objective decision making, and more.

Modeling Road Vulnerability to Snow Using Mixed Integer Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodriguez, Tony K; Omitaomu, Olufemi A; Ostrowski, James A

As the number and severity of snowfall events continue to grow, the need to intelligently direct road maintenance during these snowfall events will also grow. In several locations, local governments lack the resources to completely treat all roadways during snow events. Furthermore, some governments utilize only traffic data to determine which roads should be treated. As a result, many schools, businesses, and government offices must be unnecessarily closed, which directly impacts the social, educational, and economic well-being of citizens and institutions. In this work, we propose a mixed integer programming formulation to optimally allocate resources to manage snowfall on roadsmore » using meteorological, geographical, and environmental parameters. Additionally, we evaluate the impacts of an increase in budget for winter road maintenance on snow control resources.« less

DORMAN computer program (study 2.5). Volume 2: User's guide and programmer's guide. [development of data bank for computerized information storage of NASA programs

NASA Technical Reports Server (NTRS)

Wray, S. T., Jr.

1973-01-01

The DORMAN program was developed to create and modify a data bank containing data decks which serve as input to the DORCA Computer Program. Via a remote terminal a user can access the bank, extract any data deck, modify that deck, output the modified deck to be input to the DORCA program, and save the modified deck in the data bank. This computer program is an assist in the utilization of the DORCA program. The program is dimensionless and operates almost entirely in integer mode. The program was developed on the CDC 6400/7600 complex for implementation on a UNIVAC 1108 computer.

Counting Triangles to Sum Squares

ERIC Educational Resources Information Center

DeMaio, Joe

2012-01-01

Counting complete subgraphs of three vertices in complete graphs, yields combinatorial arguments for identities for sums of squares of integers, odd integers, even integers and sums of the triangular numbers.

Slip and Slide Method of Factoring Trinomials with Integer Coefficients over the Integers

ERIC Educational Resources Information Center

Donnell, William A.

2012-01-01

In intermediate and college algebra courses there are a number of methods for factoring quadratic trinomials with integer coefficients over the integers. Some of these methods have been given names, such as trial and error, reversing FOIL, AC method, middle term splitting method and slip and slide method. The purpose of this article is to discuss…

Obstacles and Affordances for Integer Reasoning: An Analysis of Children's Thinking and the History of Mathematics

ERIC Educational Resources Information Center

Bishop, Jessica Pierson; Lamb, Lisa L.; Philipp, Randolph A.; Whitacre, Ian; Schappelle, Bonnie P.; Lewis, Melinda L.

2014-01-01

We identify and document 3 cognitive obstacles, 3 cognitive affordances, and 1 type of integer understanding that can function as either an obstacle or affordance for learners while they extend their numeric domains from whole numbers to include negative integers. In particular, we highlight 2 key subsets of integer reasoning: understanding or…

Anisotropic fractal media by vector calculus in non-integer dimensional space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tarasov, Vasily E., E-mail: tarasov@theory.sinp.msu.ru

2014-08-15

A review of different approaches to describe anisotropic fractal media is proposed. In this paper, differentiation and integration non-integer dimensional and multi-fractional spaces are considered as tools to describe anisotropic fractal materials and media. We suggest a generalization of vector calculus for non-integer dimensional space by using a product measure method. The product of fractional and non-integer dimensional spaces allows us to take into account the anisotropy of the fractal media in the framework of continuum models. The integration over non-integer-dimensional spaces is considered. In this paper differential operators of first and second orders for fractional space and non-integer dimensionalmore » space are suggested. The differential operators are defined as inverse operations to integration in spaces with non-integer dimensions. Non-integer dimensional space that is product of spaces with different dimensions allows us to give continuum models for anisotropic type of the media. The Poisson's equation for fractal medium, the Euler-Bernoulli fractal beam, and the Timoshenko beam equations for fractal material are considered as examples of application of suggested generalization of vector calculus for anisotropic fractal materials and media.« less

Techniques for computing the discrete Fourier transform using the quadratic residue Fermat number systems

NASA Technical Reports Server (NTRS)

Truong, T. K.; Chang, J. J.; Hsu, I. S.; Pei, D. Y.; Reed, I. S.

1986-01-01

The complex integer multiplier and adder over the direct sum of two copies of finite field developed by Cozzens and Finkelstein (1985) is specialized to the direct sum of the rings of integers modulo Fermat numbers. Such multiplication over the rings of integers modulo Fermat numbers can be performed by means of two integer multiplications, whereas the complex integer multiplication requires three integer multiplications. Such multiplications and additions can be used in the implementation of a discrete Fourier transform (DFT) of a sequence of complex numbers. The advantage of the present approach is that the number of multiplications needed to compute a systolic array of the DFT can be reduced substantially. The architectural designs using this approach are regular, simple, expandable and, therefore, naturally suitable for VLSI implementation.

Fractional order fuzzy control of hybrid power system with renewable generation using chaotic PSO.

PubMed

Pan, Indranil; Das, Saptarshi

2016-05-01

This paper investigates the operation of a hybrid power system through a novel fuzzy control scheme. The hybrid power system employs various autonomous generation systems like wind turbine, solar photovoltaic, diesel engine, fuel-cell, aqua electrolyzer etc. Other energy storage devices like the battery, flywheel and ultra-capacitor are also present in the network. A novel fractional order (FO) fuzzy control scheme is employed and its parameters are tuned with a particle swarm optimization (PSO) algorithm augmented with two chaotic maps for achieving an improved performance. This FO fuzzy controller shows better performance over the classical PID, and the integer order fuzzy PID controller in both linear and nonlinear operating regimes. The FO fuzzy controller also shows stronger robustness properties against system parameter variation and rate constraint nonlinearity, than that with the other controller structures. The robustness is a highly desirable property in such a scenario since many components of the hybrid power system may be switched on/off or may run at lower/higher power output, at different time instants. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Highly intense monocycle terahertz vortex generation by utilizing a Tsurupica spiral phase plate

PubMed Central

Miyamoto, Katsuhiko; Kang, Bong Joo; Kim, Won Tae; Sasaki, Yuta; Niinomi, Hiromasa; Suizu, Koji; Rotermund, Fabian; Omatsu, Takashige

2016-01-01

Optical vortex, possessing an annular intensity profile and an orbital angular momentum (characterized by an integer termed a topological charge) associated with a helical wavefront, has attracted great attention for diverse applications due to its unique properties. In particular for terahertz (THz) frequency range, several approaches for THz vortex generation, including molded phase plates consisting of metal slit antennas, achromatic polarization elements and binary-diffractive optical elements, have been recently proposed, however, they are typically designed for a specific frequency. Here, we demonstrate highly intense broadband monocycle vortex generation near 0.6 THz by utilizing a polymeric Tsurupica spiral phase plate in combination with tilted-pulse-front optical rectification in a prism-cut LiNbO3 crystal. A maximum peak power of 2.3 MW was obtained for THz vortex output with an expected topological charge of 1.15. Furthermore, we applied the highly intense THz vortex beam for studying unique nonlinear behaviors in bilayer graphene towards the development of nonlinear super-resolution THz microscopy and imaging system. PMID:27966595

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

DOE Office of Scientific and Technical Information (OSTI.GOV)

Powell, Kody M.; Kim, Jong Suk; Cole, Wesley J.

2016-10-01

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens ofmore » thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.« less

Integrated locating of helicopter stations and helipads for wounded transfer under demand location uncertainty.

PubMed

Bozorgi-Amiri, Ali; Tavakoli, Shayan; Mirzaeipour, Hossein; Rabbani, Masoud

2017-03-01

Health emergency medical service (HEMS) plays an important role in reducing injuries by providing advanced medical care in the shortest time and reducing the transfer time to advanced treatment centers. In the regions without ground relief coverage, it would be faster to transfer emergency patients to the hospital by a helicopter. In this paper, an integer nonlinear programming model is presented for the integrated locating of helicopter stations and helipads by considering uncertainty in demand points. We assume three transfer modes: (1) direct transfer by an ambulance, (2) transfer by an ambulance to a helicopter station and then to the hospital by a helicopter, (3) transfer by an ambulance to a predetermined point and then to the hospital by a helicopter. We also assume that demands occur in a square-shaped area, in which each side follows a uniform distribution. It is also assumed that demands in an area decrease errors in the distances between each two cities. The purpose of this model is to minimize the transfer time from demand points to the hospital by considering different modes. The proposed model is examined in terms of validity and applicability in Lorestan Province and a sensitivity analysis is also conducted on the total allocated budget. Copyright © 2016 Elsevier Inc. All rights reserved.

Incorporating location, routing, and inventory decisions in a bi-objective supply chain design problem with risk-pooling

NASA Astrophysics Data System (ADS)

Tavakkoli-Moghaddam, Reza; Forouzanfar, Fateme; Ebrahimnejad, Sadoullah

2013-07-01

This paper considers a single-sourcing network design problem for a three-level supply chain. For the first time, a novel mathematical model is presented considering risk-pooling, the inventory existence at distribution centers (DCs) under demand uncertainty, the existence of several alternatives to transport the product between facilities, and routing of vehicles from distribution centers to customer in a stochastic supply chain system, simultaneously. This problem is formulated as a bi-objective stochastic mixed-integer nonlinear programming model. The aim of this model is to determine the number of located distribution centers, their locations, and capacity levels, and allocating customers to distribution centers and distribution centers to suppliers. It also determines the inventory control decisions on the amount of ordered products and the amount of safety stocks at each opened DC, selecting a type of vehicle for transportation. Moreover, it determines routing decisions, such as determination of vehicles' routes starting from an opened distribution center to serve its allocated customers and returning to that distribution center. All are done in a way that the total system cost and the total transportation time are minimized. The Lingo software is used to solve the presented model. The computational results are illustrated in this paper.

Scheduling algorithms for rapid imaging using agile Cubesat constellations

NASA Astrophysics Data System (ADS)

Nag, Sreeja; Li, Alan S.; Merrick, James H.

2018-02-01

Distributed Space Missions such as formation flight and constellations, are being recognized as important Earth Observation solutions to increase measurement samples over space and time. Cubesats are increasing in size (27U, ∼40 kg in development) with increasing capabilities to host imager payloads. Given the precise attitude control systems emerging in the commercial market, Cubesats now have the ability to slew and capture images within short notice. We propose a modular framework that combines orbital mechanics, attitude control and scheduling optimization to plan the time-varying, full-body orientation of agile Cubesats in a constellation such that they maximize the number of observed images and observation time, within the constraints of Cubesat hardware specifications. The attitude control strategy combines bang-bang and PD control, with constraints such as power consumption, response time, and stability factored into the optimality computations and a possible extension to PID control to account for disturbances. Schedule optimization is performed using dynamic programming with two levels of heuristics, verified and improved upon using mixed integer linear programming. The automated scheduler is expected to run on ground station resources and the resultant schedules uplinked to the satellites for execution, however it can be adapted for onboard scheduling, contingent on Cubesat hardware and software upgrades. The framework is generalizable over small steerable spacecraft, sensor specifications, imaging objectives and regions of interest, and is demonstrated using multiple 20 kg satellites in Low Earth Orbit for two case studies - rapid imaging of Landsat's land and coastal images and extended imaging of global, warm water coral reefs. The proposed algorithm captures up to 161% more Landsat images than nadir-pointing sensors with the same field of view, on a 2-satellite constellation over a 12-h simulation. Integer programming was able to verify that optimality of the dynamic programming solution for single satellites was within 10%, and find up to 5% more optimal solutions. The optimality gap for constellations was found to be 22% at worst, but the dynamic programming schedules were found at nearly four orders of magnitude better computational speed than integer programming. The algorithm can include cloud cover predictions, ground downlink windows or any other spatial, temporal or angular constraints into the orbital module and be integrated into planning tools for agile constellations.

Case study and lessons learned for the Great Lakes ITS Program, Airport ITS Integration and the Road Infrastructure Management System projects, final report, Wayne County, Michigan

DOT National Transportation Integrated Search

2007-03-02

This report presents the case study and lessons learned for the national evaluation of the Great Lakes Intelligent Transportation Systems (GLITS) Airport ITS Integration and Road Infrastructure Management System (RIMS) projects. The Airport ITS Integ...

A Procedure Using Calculators to Express Answers in Fractional Form.

ERIC Educational Resources Information Center

Carlisle, Earnest

A procedure is described that enables students to perform operations on fractions with a calculator, expressing the answer as a fraction. Patterns using paper-and-pencil procedures for each operation with fractions are presented. A microcomputer software program illustrates how the answer can be found using integer values of the numerators and…

Automated Test-Form Generation

ERIC Educational Resources Information Center

van der Linden, Wim J.; Diao, Qi

2011-01-01

In automated test assembly (ATA), the methodology of mixed-integer programming is used to select test items from an item bank to meet the specifications for a desired test form and optimize its measurement accuracy. The same methodology can be used to automate the formatting of the set of selected items into the actual test form. Three different…

A strategic assessment of biofuels development in the Western States

Treesearch

Kenneth E. Skog; Robert Rummer; Bryan Jenkins; Nathan Parker; Peter Tittman; Quinn Hart; Richard Nelson; Ed Gray; Anneliese Schmidt; Marcia Patton-Mallory; Gordon Gayle

2009-01-01

The Western Governors' Association assessment of biofuels potential in western states estimated the location and capacity of biofuels plants that could potentially be built for selected gasoline prices in 2015 using a mixed integer programming model. The model included information on forest biomass supply curves by county (developed using Forest Service FIA data...

An Integer Programming-Based Generalized Vehicle Routing Approach for Printed Circuit Board Assembly Optimization

ERIC Educational Resources Information Center

Seth, Anupam

2009-01-01

Production planning and scheduling for printed circuit, board assembly has so far defied standard operations research approaches due to the size and complexity of the underlying problems, resulting in unexploited automation flexibility. In this thesis, the increasingly popular collect-and-place machine configuration is studied and the assembly…

Elements of Mathematics, Book O: Intuitive Background. Chapter 2, The Integers.

ERIC Educational Resources Information Center

Exner, Robert; And Others

The sixteen chapters of this book provide the core materials for the Elements of Mathematics Program, a secondary sequence developed for highly motivated students with strong verbal abilities. The sequence is based on a functional-relational approach to mathematics teaching, and emphasizes teaching by analysis of real-life situations. This text is…

Algorithms for Scheduling and Network Problems

DTIC Science & Technology

1991-09-01

time. We already know, by Lemma 2.2.1, that WOPT = O(log( mpU )), so if we could solve this integer program optimally we would be done. However, the...Folydirat, 15:177-191, 1982. [6] I.S. Belov and Ya. N. Stolin. An algorithm in a single path operations scheduling problem. In Mathematical Economics and

Enhancing Autonomy of Aerial Systems Via Integration of Visual Sensors into Their Avionics Suite

DTIC Science & Technology

2016-09-01

aerial platform for subsequent visual sensor integration. 14. SUBJECT TERMS autonomous system, quadrotors, direct method, inverse ...CONTROLLER ARCHITECTURE .....................................................43 B. INVERSE DYNAMICS IN THE VIRTUAL DOMAIN ......................45 1...control station GPS Global-Positioning System IDVD inverse dynamics in the virtual domain ILP integer linear program INS inertial-navigation system

A farm-level precision land management framework based on integer programming

PubMed Central

Li, Qi; Hu, Guiping; Jubery, Talukder Zaki; Ganapathysubramanian, Baskar

2017-01-01

Farmland management involves several planning and decision making tasks including seed selection and irrigation management. A farm-level precision farmland management model based on mixed integer linear programming is proposed in this study. Optimal decisions are designed for pre-season planning of crops and irrigation water allocation. The model captures the effect of size and shape of decision scale as well as special irrigation patterns. The authors illustrate the model with a case study on a farm in the state of California in the U.S. and show the model can capture the impact of precision farm management on profitability. The results show that threefold increase of annual net profit for farmers could be achieved by carefully choosing irrigation and seed selection. Although farmers could increase profits by applying precision management to seed or irrigation alone, profit increase is more significant if farmers apply precision management on seed and irrigation simultaneously. The proposed model can also serve as a risk analysis tool for farmers facing seasonal irrigation water limits as well as a quantitative tool to explore the impact of precision agriculture. PMID:28346499

Microgrid Optimal Scheduling With Chance-Constrained Islanding Capability

DOE PAGES

Liu, Guodong; Starke, Michael R.; Xiao, B.; ...

2017-01-13

To facilitate the integration of variable renewable generation and improve the resilience of electricity sup-ply in a microgrid, this paper proposes an optimal scheduling strategy for microgrid operation considering constraints of islanding capability. A new concept, probability of successful islanding (PSI), indicating the probability that a microgrid maintains enough spinning reserve (both up and down) to meet local demand and accommodate local renewable generation after instantaneously islanding from the main grid, is developed. The PSI is formulated as mixed-integer linear program using multi-interval approximation taking into account the probability distributions of forecast errors of wind, PV and load. With themore » goal of minimizing the total operating cost while preserving user specified PSI, a chance-constrained optimization problem is formulated for the optimal scheduling of mirogrids and solved by mixed integer linear programming (MILP). Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator and a battery demonstrate the effectiveness of the proposed scheduling strategy. Lastly, we verify the relationship between PSI and various factors.« less

A hybrid inventory management system respondingto regular demand and surge demand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mohammad S. Roni; Mingzhou Jin; Sandra D. Eksioglu

2014-06-01

This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a givenmore » policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.« less

Chemotherapy appointment scheduling under uncertainty using mean-risk stochastic integer programming.

PubMed

Alvarado, Michelle; Ntaimo, Lewis

2018-03-01

Oncology clinics are often burdened with scheduling large volumes of cancer patients for chemotherapy treatments under limited resources such as the number of nurses and chairs. These cancer patients require a series of appointments over several weeks or months and the timing of these appointments is critical to the treatment's effectiveness. Additionally, the appointment duration, the acuity levels of each appointment, and the availability of clinic nurses are uncertain. The timing constraints, stochastic parameters, rising treatment costs, and increased demand of outpatient oncology clinic services motivate the need for efficient appointment schedules and clinic operations. In this paper, we develop three mean-risk stochastic integer programming (SIP) models, referred to as SIP-CHEMO, for the problem of scheduling individual chemotherapy patient appointments and resources. These mean-risk models are presented and an algorithm is devised to improve computational speed. Computational results were conducted using a simulation model and results indicate that the risk-averse SIP-CHEMO model with the expected excess mean-risk measure can decrease patient waiting times and nurse overtime when compared to deterministic scheduling algorithms by 42 % and 27 %, respectively.

Supporting Dynamic Spectrum Access in Heterogeneous LTE+ Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luiz A. DaSilva; Ryan E. Irwin; Mike Benonis

As early as 2014, mobile network operators’ spectral capac- ity is expected to be overwhelmed by the demand brought on by new devices and applications. With Long Term Evo- lution Advanced (LTE+) networks likely as the future one world 4G standard, network operators may need to deploy a Dynamic Spectrum Access (DSA) overlay in Heterogeneous Networks (HetNets) to extend coverage, increase spectrum efficiency, and increase the capacity of these networks. In this paper, we propose three new management frameworks for DSA in an LTE+ HetNet: Spectrum Accountability Client, Cell Spectrum Management, and Domain Spectrum Man- agement. For these spectrum managementmore » frameworks, we define protocol interfaces and operational signaling scenar- ios to support cooperative sensing, spectrum lease manage- ment, and alarm scenarios for rule adjustment. We also quan- tify, through integer programs, the benefits of using DSA in an LTE+ HetNet, that can opportunistically reuse vacant TV and GSM spectrum. Using integer programs, we consider a topology using Geographic Information System data from the Blacksburg, VA metro area to assess the realistic benefits of DSA in an LTE+ HetNet.« less

Two Methods for Efficient Solution of the Hitting-Set Problem

NASA Technical Reports Server (NTRS)

Vatan, Farrokh; Fijany, Amir

2005-01-01

A paper addresses much of the same subject matter as that of Fast Algorithms for Model-Based Diagnosis (NPO-30582), which appears elsewhere in this issue of NASA Tech Briefs. However, in the paper, the emphasis is more on the hitting-set problem (also known as the transversal problem), which is well known among experts in combinatorics. The authors primary interest in the hitting-set problem lies in its connection to the diagnosis problem: it is a theorem of model-based diagnosis that in the set-theory representation of the components of a system, the minimal diagnoses of a system are the minimal hitting sets of the system. In the paper, the hitting-set problem (and, hence, the diagnosis problem) is translated from a combinatorial to a computational problem by mapping it onto the Boolean satisfiability and integer- programming problems. The paper goes on to describe developments nearly identical to those summarized in the cited companion NASA Tech Briefs article, including the utilization of Boolean-satisfiability and integer- programming techniques to reduce the computation time and/or memory needed to solve the hitting-set problem.

Integer-Linear-Programing Optimization in Scalable Video Multicast with Adaptive Modulation and Coding in Wireless Networks

PubMed Central

Lee, Chaewoo

2014-01-01

The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm. PMID:25276862

Checking Equivalence of SPMD Programs Using Non-Interference

DTIC Science & Technology

2010-01-29

with it hopes to go beyond the limits of Moore’s law, but also worries that programming will become harder [5]. One of the reasons why parallel...array name in G or L, and e is an arithmetic expression of integer type. In the CUDA code shown in Section 3, b and t are represented by coreId and...b+ t. A second, optimized version of the program (using function “reverse2”, see Section 3) can be modeled as a tuple P2 = ( G ,L2, F 2), with G same

Parallel scheduling of recursively defined arrays

NASA Technical Reports Server (NTRS)

Myers, T. J.; Gokhale, M. B.

1986-01-01

A new method of automatic generation of concurrent programs which constructs arrays defined by sets of recursive equations is described. It is assumed that the time of computation of an array element is a linear combination of its indices, and integer programming is used to seek a succession of hyperplanes along which array elements can be computed concurrently. The method can be used to schedule equations involving variable length dependency vectors and mutually recursive arrays. Portions of the work reported here have been implemented in the PS automatic program generation system.

Sums of Consecutive Integers

ERIC Educational Resources Information Center

Pong, Wai Yan

2007-01-01

We begin by answering the question, "Which natural numbers are sums of consecutive integers?" We then go on to explore the set of lengths (numbers of summands) in the decompositions of an integer as such sums.

lsjk—a C++ library for arbitrary-precision numeric evaluation of the generalized log-sine functions

NASA Astrophysics Data System (ADS)

Kalmykov, M. Yu.; Sheplyakov, A.

2005-10-01

Generalized log-sine functions Lsj(k)(θ) appear in higher order ɛ-expansion of different Feynman diagrams. We present an algorithm for the numerical evaluation of these functions for real arguments. This algorithm is implemented as a C++ library with arbitrary-precision arithmetics for integer 0⩽k⩽9 and j⩾2. Some new relations and representations of the generalized log-sine functions are given. Program summaryTitle of program:lsjk Catalogue number:ADVS Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADVS Program obtained from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing terms: GNU General Public License Computers:all Operating systems:POSIX Programming language:C++ Memory required to execute:Depending on the complexity of the problem, at least 32 MB RAM recommended No. of lines in distributed program, including testing data, etc.:41 975 No. of bytes in distributed program, including testing data, etc.:309 156 Distribution format:tar.gz Other programs called:The CLN library for arbitrary-precision arithmetics is required at version 1.1.5 or greater External files needed:none Nature of the physical problem:Numerical evaluation of the generalized log-sine functions for real argument in the region 0<θ<π. These functions appear in Feynman integrals Method of solution:Series representation for the real argument in the region 0<θ<π Restriction on the complexity of the problem:Limited up to Lsj(9)(θ), and j is an arbitrary integer number. Thus, all function up to the weight 12 in the region 0<θ<π can be evaluated. The algorithm can be extended up to higher values of k(k>9) without modification Typical running time:Depending on the complexity of problem. See text below.

DB90: A Fortran Callable Relational Database Routine for Scientific and Engineering Computer Programs

NASA Technical Reports Server (NTRS)

Wrenn, Gregory A.

2005-01-01

This report describes a database routine called DB90 which is intended for use with scientific and engineering computer programs. The software is written in the Fortran 90/95 programming language standard with file input and output routines written in the C programming language. These routines should be completely portable to any computing platform and operating system that has Fortran 90/95 and C compilers. DB90 allows a program to supply relation names and up to 5 integer key values to uniquely identify each record of each relation. This permits the user to select records or retrieve data in any desired order.

Synchronic interval Gaussian mixed-integer programming for air quality management.

PubMed

Cheng, Guanhui; Huang, Guohe Gordon; Dong, Cong

2015-12-15

To reveal the synchronism of interval uncertainties, the tradeoff between system optimality and security, the discreteness of facility-expansion options, the uncertainty of pollutant dispersion processes, and the seasonality of wind features in air quality management (AQM) systems, a synchronic interval Gaussian mixed-integer programming (SIGMIP) approach is proposed in this study. A robust interval Gaussian dispersion model is developed for approaching the pollutant dispersion process under interval uncertainties and seasonal variations. The reflection of synchronic effects of interval uncertainties in the programming objective is enabled through introducing interval functions. The proposition of constraint violation degrees helps quantify the tradeoff between system optimality and constraint violation under interval uncertainties. The overall optimality of system profits of an SIGMIP model is achieved based on the definition of an integrally optimal solution. Integer variables in the SIGMIP model are resolved by the existing cutting-plane method. Combining these efforts leads to an effective algorithm for the SIGMIP model. An application to an AQM problem in a region in Shandong Province, China, reveals that the proposed SIGMIP model can facilitate identifying the desired scheme for AQM. The enhancement of the robustness of optimization exercises may be helpful for increasing the reliability of suggested schemes for AQM under these complexities. The interrelated tradeoffs among control measures, emission sources, flow processes, receptors, influencing factors, and economic and environmental goals are effectively balanced. Interests of many stakeholders are reasonably coordinated. The harmony between economic development and air quality control is enabled. Results also indicate that the constraint violation degree is effective at reflecting the compromise relationship between constraint-violation risks and system optimality under interval uncertainties. This can help decision makers mitigate potential risks, e.g. insufficiency of pollutant treatment capabilities, exceedance of air quality standards, deficiency of pollution control fund, or imbalance of economic or environmental stress, in the process of guiding AQM. Copyright © 2015 Elsevier B.V. All rights reserved.

TH-EF-BRB-04: 4π Dynamic Conformal Arc Therapy Dynamic Conformal Arc Therapy (DCAT) for SBRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiu, T; Long, T; Tian, Z.

2016-06-15

Purpose: To develop an efficient and effective trajectory optimization methodology for 4π dynamic conformal arc treatment (4π DCAT) with synchronized gantry and couch motion; and to investigate potential clinical benefits for stereotactic body radiation therapy (SBRT) to breast, lung, liver and spine tumors. Methods: The entire optimization framework for 4π DCAT inverse planning consists of two parts: 1) integer programming algorithm and 2) particle swarm optimization (PSO) algorithm. The integer programming is designed to find an optimal solution for arc delivery trajectory with both couch and gantry rotation, while PSO minimize a non-convex objective function based on the selected trajectorymore » and dose-volume constraints. In this study, control point interaction is explicitly taken into account. Beam trajectory was modeled as a series of control points connected together to form a deliverable path. With linear treatment planning objectives, a mixed-integer program (MIP) was formulated. Under mild assumptions, the MIP is tractable. Assigning monitor units to control points along the path can be integrated into the model and done by PSO. The developed 4π DCAT inverse planning strategy is evaluated on SBRT cases and compared to clinically treated plans. Results: The resultant dose distribution of this technique was evaluated between 3D conformal treatment plan generated by Pinnacle treatment planning system and 4π DCAT on a lung SBRT patient case. Both plans share the same scale of MU, 3038 and 2822 correspondingly to 3D conformal plan and 4π DCAT. The mean doses for most of OARs were greatly reduced at 32% (cord), 70% (esophagus), 2.8% (lung) and 42.4% (stomach). Conclusion: Initial results in this study show the proposed 4π DCAT treatment technique can achieve better OAR sparing and lower MUs, which indicates that the developed technique is promising for high dose SBRT to reduce the risk of secondary cancer.« less

Bi-objective integer programming for RNA secondary structure prediction with pseudoknots.

PubMed

Legendre, Audrey; Angel, Eric; Tahi, Fariza

2018-01-15

RNA structure prediction is an important field in bioinformatics, and numerous methods and tools have been proposed. Pseudoknots are specific motifs of RNA secondary structures that are difficult to predict. Almost all existing methods are based on a single model and return one solution, often missing the real structure. An alternative approach would be to combine different models and return a (small) set of solutions, maximizing its quality and diversity in order to increase the probability that it contains the real structure. We propose here an original method for predicting RNA secondary structures with pseudoknots, based on integer programming. We developed a generic bi-objective integer programming algorithm allowing to return optimal and sub-optimal solutions optimizing simultaneously two models. This algorithm was then applied to the combination of two known models of RNA secondary structure prediction, namely MEA and MFE. The resulting tool, called BiokoP, is compared with the other methods in the literature. The results show that the best solution (structure with the highest F 1 -score) is, in most cases, given by BiokoP. Moreover, the results of BiokoP are homogeneous, regardless of the pseudoknot type or the presence or not of pseudoknots. Indeed, the F 1 -scores are always higher than 70% for any number of solutions returned. The results obtained by BiokoP show that combining the MEA and the MFE models, as well as returning several optimal and several sub-optimal solutions, allow to improve the prediction of secondary structures. One perspective of our work is to combine better mono-criterion models, in particular to combine a model based on the comparative approach with the MEA and the MFE models. This leads to develop in the future a new multi-objective algorithm to combine more than two models. BiokoP is available on the EvryRNA platform: https://EvryRNA.ibisc.univ-evry.fr .

AKLSQF - LEAST SQUARES CURVE FITTING

NASA Technical Reports Server (NTRS)

Kantak, A. V.

1994-01-01

The Least Squares Curve Fitting program, AKLSQF, computes the polynomial which will least square fit uniformly spaced data easily and efficiently. The program allows the user to specify the tolerable least squares error in the fitting or allows the user to specify the polynomial degree. In both cases AKLSQF returns the polynomial and the actual least squares fit error incurred in the operation. The data may be supplied to the routine either by direct keyboard entry or via a file. AKLSQF produces the least squares polynomial in two steps. First, the data points are least squares fitted using the orthogonal factorial polynomials. The result is then reduced to a regular polynomial using Sterling numbers of the first kind. If an error tolerance is specified, the program starts with a polynomial of degree 1 and computes the least squares fit error. The degree of the polynomial used for fitting is then increased successively until the error criterion specified by the user is met. At every step the polynomial as well as the least squares fitting error is printed to the screen. In general, the program can produce a curve fitting up to a 100 degree polynomial. All computations in the program are carried out under Double Precision format for real numbers and under long integer format for integers to provide the maximum accuracy possible. AKLSQF was written for an IBM PC X/AT or compatible using Microsoft's Quick Basic compiler. It has been implemented under DOS 3.2.1 using 23K of RAM. AKLSQF was developed in 1989.

Analysis misconception of integers in microteaching activities

NASA Astrophysics Data System (ADS)

Setyawati, R. D.; Indiati, I.

2018-05-01

This study view to analyse student misconceptions on integers in microteaching activities. This research used qualitative research design. An integers test contained questions from eight main areas of integers. The Integers material test includes (a) converting the image into fractions, (b) examples of positive numbers including rational numbers, (c) operations in fractions, (d) sorting fractions from the largest to the smallest, and vice versa; e) equate denominator, (f) concept of ratio mark, (g) definition of fraction, and (h) difference between fractions and parts. The results indicated an integers concepts: (1) the students have not been able to define concepts well based on the classification of facts in organized part; (2) The correlational concept: students have not been able to combine interrelated events in the form of general principles; and (3) theoretical concepts: students have not been able to use concepts that facilitate in learning the facts or events in an organized system.

Dynamic Flow Management Problems in Air Transportation

NASA Technical Reports Server (NTRS)

Patterson, Sarah Stock

1997-01-01

In 1995, over six hundred thousand licensed pilots flew nearly thirty-five million flights into over eighteen thousand U.S. airports, logging more than 519 billion passenger miles. Since demand for air travel has increased by more than 50% in the last decade while capacity has stagnated, congestion is a problem of undeniable practical significance. In this thesis, we will develop optimization techniques that reduce the impact of congestion on the national airspace. We start by determining the optimal release times for flights into the airspace and the optimal speed adjustment while airborne taking into account the capacitated airspace. This is called the Air Traffic Flow Management Problem (TFMP). We address the complexity, showing that it is NP-hard. We build an integer programming formulation that is quite strong as some of the proposed inequalities are facet defining for the convex hull of solutions. For practical problems, the solutions of the LP relaxation of the TFMP are very often integral. In essence, we reduce the problem to efficiently solving large scale linear programming problems. Thus, the computation times are reasonably small for large scale, practical problems involving thousands of flights. Next, we address the problem of determining how to reroute aircraft in the airspace system when faced with dynamically changing weather conditions. This is called the Air Traffic Flow Management Rerouting Problem (TFMRP) We present an integrated mathematical programming approach for the TFMRP, which utilizes several methodologies, in order to minimize delay costs. In order to address the high dimensionality, we present an aggregate model, in which we formulate the TFMRP as a multicommodity, integer, dynamic network flow problem with certain side constraints. Using Lagrangian relaxation, we generate aggregate flows that are decomposed into a collection of flight paths using a randomized rounding heuristic. This collection of paths is used in a packing integer programming formulation, the solution of which generates feasible and near-optimal routes for individual flights. The algorithm, termed the Lagrangian Generation Algorithm, is used to solve practical problems in the southwestern portion of United States in which the solutions are within 1% of the corresponding lower bounds.

Fractal electrodynamics via non-integer dimensional space approach

NASA Astrophysics Data System (ADS)

Tarasov, Vasily E.

2015-09-01

Using the recently suggested vector calculus for non-integer dimensional space, we consider electrodynamics problems in isotropic case. This calculus allows us to describe fractal media in the framework of continuum models with non-integer dimensional space. We consider electric and magnetic fields of fractal media with charges and currents in the framework of continuum models with non-integer dimensional spaces. An application of the fractal Gauss's law, the fractal Ampere's circuital law, the fractal Poisson equation for electric potential, and equation for fractal stream of charges are suggested. Lorentz invariance and speed of light in fractal electrodynamics are discussed. An expression for effective refractive index of non-integer dimensional space is suggested.

A combinatorial approach to the design of vaccines.

PubMed

Martínez, Luis; Milanič, Martin; Legarreta, Leire; Medvedev, Paul; Malaina, Iker; de la Fuente, Ildefonso M

2015-05-01

We present two new problems of combinatorial optimization and discuss their applications to the computational design of vaccines. In the shortest λ-superstring problem, given a family S1,...,S(k) of strings over a finite alphabet, a set Τ of "target" strings over that alphabet, and an integer λ, the task is to find a string of minimum length containing, for each i, at least λ target strings as substrings of S(i). In the shortest λ-cover superstring problem, given a collection X1,...,X(n) of finite sets of strings over a finite alphabet and an integer λ, the task is to find a string of minimum length containing, for each i, at least λ elements of X(i) as substrings. The two problems are polynomially equivalent, and the shortest λ-cover superstring problem is a common generalization of two well known combinatorial optimization problems, the shortest common superstring problem and the set cover problem. We present two approaches to obtain exact or approximate solutions to the shortest λ-superstring and λ-cover superstring problems: one based on integer programming, and a hill-climbing algorithm. An application is given to the computational design of vaccines and the algorithms are applied to experimental data taken from patients infected by H5N1 and HIV-1.

Density of Primitive Pythagorean Triples

ERIC Educational Resources Information Center

Killen, Duncan A.

2004-01-01

Based on the properties of a Primitive Pythagorean Triple (PPT), a computer program was written to generate, print, and count all PPTs greater than or equal to I[subscript x], where I[subscript x] is an arbitrarily chosen integer. The Density of Primitive Pythagorean Triples may be defined as the ratio of the number of PPTs whose hypotenuse is…

Applying ant colony optimization metaheuristic to solve forest transportation planning problems with side constraints

Treesearch

Marco A. Contreras; Woodam Chung; Greg Jones

2008-01-01

Forest transportation planning problems (FTPP) have evolved from considering only the financial aspects of timber management to more holistic problems that also consider the environmental impacts of roads. These additional requirements have introduced side constraints, making FTPP larger and more complex. Mixed-integer programming (MIP) has been used to solve FTPP, but...

Going Around On Circles: Mathematics and Computer Art. Part 2.

ERIC Educational Resources Information Center

Gordon, Sheldon P.; Gordon, Florence S.

1984-01-01

Discusses properties of epicycloids. (The easiest way to picture them is to think of a piece of radioactive bubble gum attached to a wheel which is rolling around the outside of a larger wheel.) Includes a computer program (TRS-80 color computer) that will graph any epicycloid with integer values for the radii. (JN)

Dynamic reserve selection: Optimal land retention with land-price feedbacks

Treesearch

Sandor F. Toth; Robert G. Haight; Luke W. Rogers

2011-01-01

Urban growth compromises open space and ecosystem functions. To mitigate the negative effects, some agencies use reserve selection models to identify conservation sites for purchase or retention. Existing models assume that conservation has no impact on nearby land prices. We propose a new integer program that relaxes this assumption via adaptive cost coefficients. Our...

Integrating Test-Form Formatting into Automated Test Assembly

ERIC Educational Resources Information Center

Diao, Qi; van der Linden, Wim J.

2013-01-01

Automated test assembly uses the methodology of mixed integer programming to select an optimal set of items from an item bank. Automated test-form generation uses the same methodology to optimally order the items and format the test form. From an optimization point of view, production of fully formatted test forms directly from the item pool using…

Large-Scale Multiobjective Static Test Generation for Web-Based Testing with Integer Programming

ERIC Educational Resources Information Center

Nguyen, M. L.; Hui, Siu Cheung; Fong, A. C. M.

2013-01-01

Web-based testing has become a ubiquitous self-assessment method for online learning. One useful feature that is missing from today's web-based testing systems is the reliable capability to fulfill different assessment requirements of students based on a large-scale question data set. A promising approach for supporting large-scale web-based…

A Unified Approach to Optimization

DTIC Science & Technology

2014-10-02

employee scheduling, ad placement, latin squares, disjunctions of linear systems, temporal modeling with interval variables, and traveling salesman problems ...integrating technologies. A key to integrated modeling is to formulate a problem with high-levelmetaconstraints, which are inspired by the “global... problem substructure to the solver. This contrasts with the atomistic modeling style of mixed integer programming (MIP) and satisfiability (SAT) solvers

Equitably Distributing Quality of Marine Security Guards Using Integer Programming

DTIC Science & Technology

2013-03-01

Model for Fix-It Shop-Assignment (From Balakrishnan et al ., 2007...LP; Balakrishnan et al ., 2007). The Soviet mathematician A. N. Kolmogorov is recognized as the first person to conceptually develop the idea of LP...commercial sector today. Balakrishnan et al . (2007) captured the three major steps in LP, which are formulation, solution, and interpretation and

Parameterizing by the Number of Numbers

NASA Astrophysics Data System (ADS)

Fellows, Michael R.; Gaspers, Serge; Rosamond, Frances A.

The usefulness of parameterized algorithmics has often depended on what Niedermeier has called "the art of problem parameterization". In this paper we introduce and explore a novel but general form of parameterization: the number of numbers. Several classic numerical problems, such as Subset Sum, Partition, 3-Partition, Numerical 3-Dimensional Matching, and Numerical Matching with Target Sums, have multisets of integers as input. We initiate the study of parameterizing these problems by the number of distinct integers in the input. We rely on an FPT result for Integer Linear Programming Feasibility to show that all the above-mentioned problems are fixed-parameter tractable when parameterized in this way. In various applied settings, problem inputs often consist in part of multisets of integers or multisets of weighted objects (such as edges in a graph, or jobs to be scheduled). Such number-of-numbers parameterized problems often reduce to subproblems about transition systems of various kinds, parameterized by the size of the system description. We consider several core problems of this kind relevant to number-of-numbers parameterization. Our main hardness result considers the problem: given a non-deterministic Mealy machine M (a finite state automaton outputting a letter on each transition), an input word x, and a census requirement c for the output word specifying how many times each letter of the output alphabet should be written, decide whether there exists a computation of M reading x that outputs a word y that meets the requirement c. We show that this problem is hard for W[1]. If the question is whether there exists an input word x such that a computation of M on x outputs a word that meets c, the problem becomes fixed-parameter tractable.

Engineering calculations for solving the orbital allotment problem

NASA Technical Reports Server (NTRS)

Reilly, C.; Walton, E. K.; Mount-Campbell, C.; Caldecott, R.; Aebker, E.; Mata, F.

1988-01-01

Four approaches for calculating downlink interferences for shaped-beam antennas are described. An investigation of alternative mixed-integer programming models for satellite synthesis is summarized. Plans for coordinating the various programs developed under this grant are outlined. Two procedures for ordering satellites to initialize the k-permutation algorithm are proposed. Results are presented for the k-permutation algorithms. Feasible solutions are found for 5 of the 6 problems considered. Finally, it is demonstrated that the k-permutation algorithm can be used to solve arc allotment problems.

Analysis of Modeling Assumptions used in Production Cost Models for Renewable Integration Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stoll, Brady; Brinkman, Gregory; Townsend, Aaron

2016-01-01

Renewable energy integration studies have been published for many different regions exploring the question of how higher penetration of renewable energy will impact the electric grid. These studies each make assumptions about the systems they are analyzing; however the effect of many of these assumptions has not been yet been examined and published. In this paper we analyze the impact of modeling assumptions in renewable integration studies, including the optimization method used (linear or mixed-integer programming) and the temporal resolution of the dispatch stage (hourly or sub-hourly). We analyze each of these assumptions on a large and a small systemmore » and determine the impact of each assumption on key metrics including the total production cost, curtailment of renewables, CO2 emissions, and generator starts and ramps. Additionally, we identified the impact on these metrics if a four-hour ahead commitment step is included before the dispatch step and the impact of retiring generators to reduce the degree to which the system is overbuilt. We find that the largest effect of these assumptions is at the unit level on starts and ramps, particularly for the temporal resolution, and saw a smaller impact at the aggregate level on system costs and emissions. For each fossil fuel generator type we measured the average capacity started, average run-time per start, and average number of ramps. Linear programming results saw up to a 20% difference in number of starts and average run time of traditional generators, and up to a 4% difference in the number of ramps, when compared to mixed-integer programming. Utilizing hourly dispatch instead of sub-hourly dispatch saw no difference in coal or gas CC units for either start metric, while gas CT units had a 5% increase in the number of starts and 2% increase in the average on-time per start. The number of ramps decreased up to 44%. The smallest effect seen was on the CO2 emissions and total production cost, with a 0.8% and 0.9% reduction respectively when using linear programming compared to mixed-integer programming and 0.07% and 0.6% reduction, respectively, in the hourly dispatch compared to sub-hourly dispatch.« less

Hybrid-optimization algorithm for the management of a conjunctive-use project and well field design

USGS Publications Warehouse

Chiu, Yung-Chia; Nishikawa, Tracy; Martin, Peter

2012-01-01

Hi‐Desert Water District (HDWD), the primary water‐management agency in the Warren Groundwater Basin, California, plans to construct a waste water treatment plant to reduce future septic‐tank effluent from reaching the groundwater system. The treated waste water will be reclaimed by recharging the groundwater basin via recharge ponds as part of a larger conjunctive‐use strategy. HDWD wishes to identify the least‐cost conjunctive‐use strategies for managing imported surface water, reclaimed water, and local groundwater. As formulated, the mixed‐integer nonlinear programming (MINLP) groundwater‐management problem seeks to minimize water‐delivery costs subject to constraints including potential locations of the new pumping wells, California State regulations, groundwater‐level constraints, water‐supply demand, available imported water, and pump/recharge capacities. In this study, a hybrid‐optimization algorithm, which couples a genetic algorithm and successive‐linear programming, is developed to solve the MINLP problem. The algorithm was tested by comparing results to the enumerative solution for a simplified version of the HDWD groundwater‐management problem. The results indicate that the hybrid‐optimization algorithm can identify the global optimum. The hybrid‐optimization algorithm is then applied to solve a complex groundwater‐management problem. Sensitivity analyses were also performed to assess the impact of varying the new recharge pond orientation, varying the mixing ratio of reclaimed water and pumped water, and varying the amount of imported water available. The developed conjunctive management model can provide HDWD water managers with information that will improve their ability to manage their surface water, reclaimed water, and groundwater resources.

Hybrid-optimization algorithm for the management of a conjunctive-use project and well field design

USGS Publications Warehouse

Chiu, Yung-Chia; Nishikawa, Tracy; Martin, Peter

2012-01-01

Hi-Desert Water District (HDWD), the primary water-management agency in the Warren Groundwater Basin, California, plans to construct a waste water treatment plant to reduce future septic-tank effluent from reaching the groundwater system. The treated waste water will be reclaimed by recharging the groundwater basin via recharge ponds as part of a larger conjunctive-use strategy. HDWD wishes to identify the least-cost conjunctiveuse strategies for managing imported surface water, reclaimed water, and local groundwater. As formulated, the mixed-integer nonlinear programming (MINLP) groundwater-management problem seeks to minimize water delivery costs subject to constraints including potential locations of the new pumping wells, California State regulations, groundwater-level constraints, water-supply demand, available imported water, and pump/recharge capacities. In this study, a hybrid-optimization algorithm, which couples a genetic algorithm and successive-linear programming, is developed to solve the MINLP problem. The algorithm was tested by comparing results to the enumerative solution for a simplified version of the HDWD groundwater-management problem. The results indicate that the hybrid-optimization algorithm can identify the global optimum. The hybrid-optimization algorithm is then applied to solve a complex groundwater-management problem. Sensitivity analyses were also performed to assess the impact of varying the new recharge pond orientation, varying the mixing ratio of reclaimed water and pumped water, and varying the amount of imported water available. The developed conjunctive management model can provide HDWD water managers with information that will improve their ability to manage their surface water, reclaimed water, and groundwater resources.

Oilfield flooding polymer

DOEpatents

Martin, Fred D.; Hatch, Melvin J.; Shepitka, Joel S.; Donaruma, Lorraine G.

1986-01-01

A monomer, polymers containing the monomer, and the use of the polymer in oilfield flooding is disclosed. The subject monomer is represented by the general formula: ##STR1## wherein: n is an integer from 0 to about 4; m is an integer from 0 to about 6; a is an integer equal to at least 1 except where m is equal to 0, a must equal 0 and where m is equal to 1, a must equal 0 or 1; p is an integer from 2 to about 10; b is an integer equal to at least 1 and is of sufficient magnitude that the ratio b/p is at least 0.2; and q is an integer from 0 to 2. The number of hydroxy groups in the monomer is believed to be critical, and therefore the sum of (a+b) divided by the sum (m+p) should be at least 0.2. The moieties linked to the acrylic nitrogen can be joined to provide a ringed structure.

An Ada Linear-Algebra Software Package Modeled After HAL/S

NASA Technical Reports Server (NTRS)

Klumpp, Allan R.; Lawson, Charles L.

1990-01-01

New avionics software written more easily. Software package extends Ada programming language to include linear-algebra capabilities similar to those of HAL/S programming language. Designed for such avionics applications as Space Station flight software. In addition to built-in functions of HAL/S, package incorporates quaternion functions used in Space Shuttle and Galileo projects and routines from LINPAK solving systems of equations involving general square matrices. Contains two generic programs: one for floating-point computations and one for integer computations. Written on IBM/AT personal computer running under PC DOS, v.3.1.

A Paper-and-Pencil gcd Algorithm for Gaussian Integers

ERIC Educational Resources Information Center

Szabo, Sandor

2005-01-01

As with natural numbers, a greatest common divisor of two Gaussian (complex) integers "a" and "b" is a Gaussian integer "d" that is a common divisor of both "a" and "b". This article explores an algorithm for such gcds that is easy to do by hand.

NOLIN: A nonlinear laminate analysis program

NASA Technical Reports Server (NTRS)

Kibler, J. J.

1975-01-01

A nonlinear, plane-stress, laminate analysis program, NOLIN, was developed which accounts for laminae nonlinearity under inplane shear and transverse extensional stress. The program determines the nonlinear stress-strain behavior of symmetric laminates subjected to any combination of inplane shear and biaxial extensional loadings. The program has the ability to treat different stress-strain behavior in tension and compression, and predicts laminate failure using any or all of maximum stress, maximum strain, and quadratic interaction failure criteria. A brief description of the program is presented including discussion of the flow of information and details of the input required. Sample problems and a complete listing of the program is also provided.

Robust design of (s, S) inventory policy parameters in supply chains with demand and lead time uncertainties

NASA Astrophysics Data System (ADS)

Karimi Movahed, Kamran; Zhang, Zhi-Hai

2015-09-01

Demand and lead time uncertainties have significant effects on supply chain behaviour. In this paper, we present a single-product three-level multi-period supply chain with uncertain demands and lead times by using robust techniques to study the managerial insights of the supply chain inventory system under uncertainty. We formulate this problem as a robust mixed-integer linear program with minimised expected cost and total cost variation to determine the optimal (s, S) values of the inventory parameters. Several numerical studies are performed to investigate the supply chain behaviour. Useful guidelines for the design of a robust supply chain are also provided. Results show that the order variance and the expected cost in a supply chain significantly increase when the manufacturer's review period is an integer ratio of the distributor's and the retailer's review periods.

PLANS; a finite element program for nonlinear analysis of structures. Volume 2: User's manual

NASA Technical Reports Server (NTRS)

Pifko, A.; Armen, H., Jr.; Levy, A.; Levine, H.

1977-01-01

The PLANS system, rather than being one comprehensive computer program, is a collection of finite element programs used for the nonlinear analysis of structures. This collection of programs evolved and is based on the organizational philosophy in which classes of analyses are treated individually based on the physical problem class to be analyzed. Each of the independent finite element computer programs of PLANS, with an associated element library, can be individually loaded and used to solve the problem class of interest. A number of programs have been developed for material nonlinear behavior alone and for combined geometric and material nonlinear behavior. The usage, capabilities, and element libraries of the current programs include: (1) plastic analysis of built-up structures where bending and membrane effects are significant, (2) three dimensional elastic-plastic analysis, (3) plastic analysis of bodies of revolution, and (4) material and geometric nonlinear analysis of built-up structures.

Generalized Fractional Derivative Anisotropic Viscoelastic Characterization.

PubMed

Hilton, Harry H

2012-01-18

Isotropic linear and nonlinear fractional derivative constitutive relations are formulated and examined in terms of many parameter generalized Kelvin models and are analytically extended to cover general anisotropic homogeneous or non-homogeneous as well as functionally graded viscoelastic material behavior. Equivalent integral constitutive relations, which are computationally more powerful, are derived from fractional differential ones and the associated anisotropic temperature-moisture-degree-of-cure shift functions and reduced times are established. Approximate Fourier transform inversions for fractional derivative relations are formulated and their accuracy is evaluated. The efficacy of integer and fractional derivative constitutive relations is compared and the preferential use of either characterization in analyzing isotropic and anisotropic real materials must be examined on a case-by-case basis. Approximate protocols for curve fitting analytical fractional derivative results to experimental data are formulated and evaluated.

Exact traveling wave solutions of fractional order Boussinesq-like equations by applying Exp-function method

NASA Astrophysics Data System (ADS)

Rahmatullah; Ellahi, Rahmat; Mohyud-Din, Syed Tauseef; Khan, Umar

2018-03-01

We have computed new exact traveling wave solutions, including complex solutions of fractional order Boussinesq-Like equations, occurring in physical sciences and engineering, by applying Exp-function method. The method is blended with fractional complex transformation and modified Riemann-Liouville fractional order operator. Our obtained solutions are verified by substituting back into their corresponding equations. To the best of our knowledge, no other technique has been reported to cope with the said fractional order nonlinear problems combined with variety of exact solutions. Graphically, fractional order solution curves are shown to be strongly related to each other and most importantly, tend to fixate on their integer order solution curve. Our solutions comprise high frequencies and very small amplitude of the wave responses.

Investigation of the Nicole model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adam, C.; Sanchez-Guillen, J.; Vazquez, R.A.

2006-05-15

We study soliton solutions of the Nicole model - a non-linear four-dimensional field theory consisting of the CP{sup 1} Lagrangian density to the non-integer power (3/2) - using an ansatz within toroidal coordinates, which is indicated by the conformal symmetry of the static equations of motion. We calculate the soliton energies numerically and find that they grow linearly with the topological charge (Hopf index). Further we prove this behavior to hold exactly for the ansatz. On the other hand, for the full three-dimensional system without symmetry reduction we prove a sub-linear upper bound, analogously to the case of the Faddeev-Niemimore » model. It follows that symmetric solitons cannot be true minimizers of the energy for sufficiently large Hopf index, again in analogy to the Faddeev-Niemi model.« less

A new VLSI complex integer multiplier which uses a quadratic-polynomial residue system with Fermat numbers

NASA Technical Reports Server (NTRS)

Truong, T. K.; Hsu, I. S.; Chang, J. J.; Shyu, H. C.; Reed, I. S.

1986-01-01

A quadratic-polynomial Fermat residue number system (QFNS) has been used to compute complex integer multiplications. The advantage of such a QFNS is that a complex integer multiplication requires only two integer multiplications. In this article, a new type Fermat number multiplier is developed which eliminates the initialization condition of the previous method. It is shown that the new complex multiplier can be implemented on a single VLSI chip. Such a chip is designed and fabricated in CMOS-pw technology.

A new VLSI complex integer multiplier which uses a quadratic-polynomial residue system with Fermat numbers

NASA Technical Reports Server (NTRS)

Shyu, H. C.; Reed, I. S.; Truong, T. K.; Hsu, I. S.; Chang, J. J.

1987-01-01

A quadratic-polynomial Fermat residue number system (QFNS) has been used to compute complex integer multiplications. The advantage of such a QFNS is that a complex integer multiplication requires only two integer multiplications. In this article, a new type Fermat number multiplier is developed which eliminates the initialization condition of the previous method. It is shown that the new complex multiplier can be implemented on a single VLSI chip. Such a chip is designed and fabricated in CMOS-Pw technology.

Elasticity of fractal materials using the continuum model with non-integer dimensional space

NASA Astrophysics Data System (ADS)

Tarasov, Vasily E.

2015-01-01

Using a generalization of vector calculus for space with non-integer dimension, we consider elastic properties of fractal materials. Fractal materials are described by continuum models with non-integer dimensional space. A generalization of elasticity equations for non-integer dimensional space, and its solutions for the equilibrium case of fractal materials are suggested. Elasticity problems for fractal hollow ball and cylindrical fractal elastic pipe with inside and outside pressures, for rotating cylindrical fractal pipe, for gradient elasticity and thermoelasticity of fractal materials are solved.

Innovative Teaching Games: Climbing the Hills of Math Skills. California Demonstration Mathematics Program.

ERIC Educational Resources Information Center

Pittsburg Unified School District, CA.

The card games in this publication are an alternative activity to help students master computational skills. Games for operations with whole numbers, fractions, decimals, percents, integers, and square roots are included. They can be used to introduce math topics and for practice and review, with either the whole class or in small groups with 2 to…

Optimizing Marine Corps Personnel Assignments Using an Integer Programming Model

DTIC Science & Technology

2012-12-01

Corps. vi THIS PAGE INTENTIONALLY LEFT BLANK vii TABLE OF CONTENTS I. INTRODUCTION ...throughout our careers. xvi THIS PAGE INTENTIONALLY LEFT BLANK 1 I. INTRODUCTION The Marine Corps Manpower and Reserve Affairs (M&RA) office has the...2012 BAH Rates-with Dependents. Defense Travel Mangement Office. (2011, December). 2012 BAH Rates-without Dependents. M ileage C ost 1 Per D iem

Discrete Optimization of Electronic Hyperpolarizabilities in a Chemical Subspace

DTIC Science & Technology

2009-05-01

molecular design. Methods for optimization in discrete spaces have been studied extensively and recently reviewed ( 5). Optimization methods include...integer programming, as in branch-and-bound techniques (including dead-end elimination [ 6]), simulated annealing ( 7), and genetic algorithms ( 8...These algorithms have found renewed interest and application in molecular and materials design (9- 12) . Recently, new approaches have been

Development of a Prototype H-46 Helicopter Diagnostic Expert System.

DTIC Science & Technology

1987-09-01

SQUADRON MAINTEN\\NCE: CURRENT PROCESS AND CA D S INTEG R ,ATIO N ........................................ 14 A. MAINTENANCE DATA SYSTEM...increasce the effectiveness of the maintenance process should enhance the ability of achieving :hee objectives. Artificial intelligence techniques offer a...completeiy validated. G. ORGANIZATION OF STUDY Chapter II contains a description of the Naval Aviation Maintenance Program’s Maintenance Data System (MDS

Learning oncogenetic networks by reducing to mixed integer linear programming.

PubMed

Shahrabi Farahani, Hossein; Lagergren, Jens

2013-01-01

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

Should We Stop Developing Heuristics and Only Rely on Mixed Integer Programming Solvers in Automated Test Assembly? A Rejoinder to van der Linden and Li (2016).

PubMed

Chen, Pei-Hua

2017-05-01

This rejoinder responds to the commentary by van der Linden and Li entiled "Comment on Three-Element Item Selection Procedures for Multiple Forms Assembly: An Item Matching Approach" on the article "Three-Element Item Selection Procedures for Multiple Forms Assembly: An Item Matching Approach" by Chen. Van der Linden and Li made a strong statement calling for the cessation of test assembly heuristics development, and instead encouraged embracing mixed integer programming (MIP). This article points out the nondeterministic polynomial (NP)-hard nature of MIP problems and how solutions found using heuristics could be useful in an MIP context. Although van der Linden and Li provided several practical examples of test assembly supporting their view, the examples ignore the cases in which a slight change of constraints or item pool data might mean it would not be possible to obtain solutions as quickly as before. The article illustrates the use of heuristic solutions to improve both the performance of MIP solvers and the quality of solutions. Additional responses to the commentary by van der Linden and Li are included.

A bi-objective integer programming model for partly-restricted flight departure scheduling

PubMed Central

Guan, Wei; Zhang, Wenyi; Jiang, Shixiong; Fan, Lingling

2018-01-01

The normal studies on air traffic departure scheduling problem (DSP) mainly deal with an independent airport in which the departure traffic is not affected by surrounded airports, which, however, is not a consistent case. In reality, there still exist cases where several commercial airports are closely located and one of them possesses a higher priority. During the peak hours, the departure activities of the lower-priority airports are usually required to give way to those of higher-priority airport. These giving-way requirements can inflict a set of changes on the modeling of departure scheduling problem with respect to the lower-priority airports. To the best of our knowledge, studies on DSP under this condition are scarce. Accordingly, this paper develops a bi-objective integer programming model to address the flight departure scheduling of the partly-restricted (e.g., lower-priority) one among several adjacent airports. An adapted tabu search algorithm is designed to solve the current problem. It is demonstrated from the case study of Tianjin Binhai International Airport in China that the proposed method can obviously improve the operation efficiency, while still realizing superior equity and regularity among restricted flows. PMID:29715299

Accurate construction of consensus genetic maps via integer linear programming.

PubMed

Wu, Yonghui; Close, Timothy J; Lonardi, Stefano

2011-01-01

We study the problem of merging genetic maps, when the individual genetic maps are given as directed acyclic graphs. The computational problem is to build a consensus map, which is a directed graph that includes and is consistent with all (or, the vast majority of) the markers in the input maps. However, when markers in the individual maps have ordering conflicts, the resulting consensus map will contain cycles. Here, we formulate the problem of resolving cycles in the context of a parsimonious paradigm that takes into account two types of errors that may be present in the input maps, namely, local reshuffles and global displacements. The resulting combinatorial optimization problem is, in turn, expressed as an integer linear program. A fast approximation algorithm is proposed, and an additional speedup heuristic is developed. Our algorithms were implemented in a software tool named MERGEMAP which is freely available for academic use. An extensive set of experiments shows that MERGEMAP consistently outperforms JOINMAP, which is the most popular tool currently available for this task, both in terms of accuracy and running time. MERGEMAP is available for download at http://www.cs.ucr.edu/~yonghui/mgmap.html.

MIP models for connected facility location: A theoretical and computational study☆

PubMed Central

Gollowitzer, Stefan; Ljubić, Ivana

2011-01-01

This article comprises the first theoretical and computational study on mixed integer programming (MIP) models for the connected facility location problem (ConFL). ConFL combines facility location and Steiner trees: given a set of customers, a set of potential facility locations and some inter-connection nodes, ConFL searches for the minimum-cost way of assigning each customer to exactly one open facility, and connecting the open facilities via a Steiner tree. The costs needed for building the Steiner tree, facility opening costs and the assignment costs need to be minimized. We model ConFL using seven compact and three mixed integer programming formulations of exponential size. We also show how to transform ConFL into the Steiner arborescence problem. A full hierarchy between the models is provided. For two exponential size models we develop a branch-and-cut algorithm. An extensive computational study is based on two benchmark sets of randomly generated instances with up to 1300 nodes and 115,000 edges. We empirically compare the presented models with respect to the quality of obtained bounds and the corresponding running time. We report optimal values for all but 16 instances for which the obtained gaps are below 0.6%. PMID:25009366

Quantum-Inspired Maximizer

NASA Technical Reports Server (NTRS)

Zak, Michail

2008-01-01

A report discusses an algorithm for a new kind of dynamics based on a quantum- classical hybrid-quantum-inspired maximizer. The model is represented by a modified Madelung equation in which the quantum potential is replaced by different, specially chosen 'computational' potential. As a result, the dynamics attains both quantum and classical properties: it preserves superposition and entanglement of random solutions, while allowing one to measure its state variables, using classical methods. Such optimal combination of characteristics is a perfect match for quantum-inspired computing. As an application, an algorithm for global maximum of an arbitrary integrable function is proposed. The idea of the proposed algorithm is very simple: based upon the Quantum-inspired Maximizer (QIM), introduce a positive function to be maximized as the probability density to which the solution is attracted. Then the larger value of this function will have the higher probability to appear. Special attention is paid to simulation of integer programming and NP-complete problems. It is demonstrated that the problem of global maximum of an integrable function can be found in polynomial time by using the proposed quantum- classical hybrid. The result is extended to a constrained maximum with applications to integer programming and TSP (Traveling Salesman Problem).

A bi-objective integer programming model for partly-restricted flight departure scheduling.

PubMed

Zhong, Han; Guan, Wei; Zhang, Wenyi; Jiang, Shixiong; Fan, Lingling

2018-01-01

The normal studies on air traffic departure scheduling problem (DSP) mainly deal with an independent airport in which the departure traffic is not affected by surrounded airports, which, however, is not a consistent case. In reality, there still exist cases where several commercial airports are closely located and one of them possesses a higher priority. During the peak hours, the departure activities of the lower-priority airports are usually required to give way to those of higher-priority airport. These giving-way requirements can inflict a set of changes on the modeling of departure scheduling problem with respect to the lower-priority airports. To the best of our knowledge, studies on DSP under this condition are scarce. Accordingly, this paper develops a bi-objective integer programming model to address the flight departure scheduling of the partly-restricted (e.g., lower-priority) one among several adjacent airports. An adapted tabu search algorithm is designed to solve the current problem. It is demonstrated from the case study of Tianjin Binhai International Airport in China that the proposed method can obviously improve the operation efficiency, while still realizing superior equity and regularity among restricted flows.

Discovery of Boolean metabolic networks: integer linear programming based approach.

PubMed

Qiu, Yushan; Jiang, Hao; Ching, Wai-Ki; Cheng, Xiaoqing

2018-04-11

Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Efficient computational methods are required to identify the drug targets while incurring minimal side-effects. In this paper, we propose a graph-based computational damage model that summarizes the impact of enzymes on compounds in metabolic networks. An efficient method based on Integer Linear Programming formalism is then developed to identify the optimal enzyme-combination so as to minimize the side-effects. The identified target enzymes for known successful drugs are then verified by comparing the results with those in the existing literature. Side-effects reduction plays a crucial role in the study of drug development. A graph-based computational damage model is proposed and the theoretical analysis states the captured problem is NP-completeness. The proposed approaches can therefore contribute to the discovery of drug targets. Our developed software is available at " http://hkumath.hku.hk/~wkc/APBC2018-metabolic-network.zip ".

A combined MOIP-MCDA approach to building and screening atmospheric pollution control strategies in urban regions.

PubMed

Mavrotas, George; Ziomas, Ioannis C; Diakouaki, Danae

2006-07-01

This article presents a methodological approach for the formulation of control strategies capable of reducing atmospheric pollution at the standards set by European legislation. The approach was implemented in the greater area of Thessaloniki and was part of a project aiming at the compliance with air quality standards in five major cities in Greece. The methodological approach comprises two stages: in the first stage, the availability of several measures contributing to a certain extent to reducing atmospheric pollution indicates a combinatorial problem and favors the use of Integer Programming. More specifically, Multiple Objective Integer Programming is used in order to generate alternative efficient combinations of the available policy measures on the basis of two conflicting objectives: public expenditure minimization and social acceptance maximization. In the second stage, these combinations of control measures (i.e., the control strategies) are then comparatively evaluated with respect to a wider set of criteria, using tools from Multiple Criteria Decision Analysis, namely, the well-known PROMETHEE method. The whole procedure is based on the active involvement of local and central authorities in order to incorporate their concerns and preferences, as well as to secure the adoption and implementation of the resulting solution.

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

PubMed

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

2016-06-02

Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Optimising the selection of food items for FFQs using Mixed Integer Linear Programming.

PubMed

Gerdessen, Johanna C; Souverein, Olga W; van 't Veer, Pieter; de Vries, Jeanne Hm

2015-01-01

To support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible. Selection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear Programming (MILP) model. The methodology was demonstrated for an FFQ with interest in energy, total protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, total carbohydrates, mono- and disaccharides, dietary fibre and potassium. The food lists generated by the MILP model have good performance in terms of length, coverage and R 2 (explained variance) of all nutrients. MILP-generated food lists were 32-40 % shorter than a benchmark food list, whereas their quality in terms of R 2 was similar to that of the benchmark. The results suggest that the MILP model makes the selection process faster, more standardised and transparent, and is especially helpful in coping with multiple nutrients. The complexity of the method does not increase with increasing number of nutrients. The generated food lists appear either shorter or provide more information than a food list generated without the MILP model.

A Combined MOIP-MCDA Approach to Building and Screening Atmospheric Pollution Control Strategies in Urban Regions

NASA Astrophysics Data System (ADS)

Mavrotas, George; Ziomas, Ioannis C.; Diakouaki, Danae

2006-07-01

This article presents a methodological approach for the formulation of control strategies capable of reducing atmospheric pollution at the standards set by European legislation. The approach was implemented in the greater area of Thessaloniki and was part of a project aiming at the compliance with air quality standards in five major cities in Greece. The methodological approach comprises two stages: in the first stage, the availability of several measures contributing to a certain extent to reducing atmospheric pollution indicates a combinatorial problem and favors the use of Integer Programming. More specifically, Multiple Objective Integer Programming is used in order to generate alternative efficient combinations of the available policy measures on the basis of two conflicting objectives: public expenditure minimization and social acceptance maximization. In the second stage, these combinations of control measures (i.e., the control strategies) are then comparatively evaluated with respect to a wider set of criteria, using tools from Multiple Criteria Decision Analysis, namely, the well-known PROMETHEE method. The whole procedure is based on the active involvement of local and central authorities in order to incorporate their concerns and preferences, as well as to secure the adoption and implementation of the resulting solution.

Exact Dissipative Moment Closures for Simulation of Magnetospheric Plasmas

NASA Astrophysics Data System (ADS)

Newman, D. L.; Sen, N.; Goldman, M. V.

2004-11-01

Dissipative fluid closures produce a kinetic-like plasma response in simulations based on the evolution of moments of the Vlasov equation. Such methods were previously shown to approximate the kinetic susceptibility of a Maxwellian plasma.(G. W. Hammett and F. W. Perkins Phys. Rev. Lett.) 64, 3019 (1990). We show here that dissipative closures can yield the exact linear response for kappa velocity distributions (i.e., f(v)∝(v^2+w^2)^-κ in 1-D, where w∝ v_th), provided κ is an integer and κ+1 moments are retained in the closure. This finding is particularly relevant to the simulation of collisionless space plasmas, which frequently exhibit power-law tails characteristic of kappa distributions. Such dissipative algorithms can be made energy conserving by evolving the thermal parameter w. Dominant nonlinearities (e.g., ponderomotive effects) can also be incorporated into the algorithm. These methods have proven especially valuable in the context of reduced 2-D Vlasov simulations,(N. Sen, et al., Reduced 2-D Vlasov Simulationsldots), this meeting. where they have been used to model perpendicular ion dynamics in the evolution of nonlinear structures (e.g., double layers) in the auroral ionosphere.

McMillan Lens in a System with Space Charge

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lobach, I.; Nagaitsev, S.; Stern, E.

Space charge (SC) in a circulating beam in a ring produces both betatron tune shift and betatron tune spread. These effects make some particles move on to a machine resonance and become unstable. Linear elements of beam optics cannot reduce the tune spread induced by SC because of its intrinsic nonlinear nature. We investigate the possibility to mitigate it by a thin McMillan lens providing a nonlinear axially symmetric kick, which is qualitatively opposite to the accumulated kick by SC. Experimentally, the proposed concept can be tested in Fermilab's IOTA ring. A thin McMillan lens can be implemented by amore » short (70 cm) insertion of an electron beam with specifically chosen density distribution in transverse directions. In this article, to see if McMillan lenses reduce the tune spread induced by SC, we make several simulations with particle tracking code Synergia. We choose such beam and lattice parameters that tune spread is roughly 0.5 and a beam instability due to the half-integer resonance 0.5 is observed. Then, we try to reduce emittance growth by shifting betatron tunes by adjusting quadrupoles and reducing the tune spread by McMillan lenses.« less

Sum-Difference Numbers

ERIC Educational Resources Information Center

Shi, Yixun

2010-01-01

Starting with an interesting number game sometimes used by school teachers to demonstrate the factorization of integers, "sum-difference numbers" are defined. A positive integer n is a "sum-difference number" if there exist positive integers "x, y, w, z" such that n = xy = wz and x ? y = w + z. This paper characterizes all sum-difference numbers…

Order and Value: Transitioning to Integers

ERIC Educational Resources Information Center

Bofferding, Laura

2014-01-01

As students progress from working with whole numbers to working with integers, they must wrestle with the big ideas of number values and order. Using objects to show positive quantities is easy, but no physical negative quantities exist. Therefore, when talking about integers, the author refers to number values instead of number quantities. The…

A time series model: First-order integer-valued autoregressive (INAR(1))

NASA Astrophysics Data System (ADS)

Simarmata, D. M.; Novkaniza, F.; Widyaningsih, Y.

2017-07-01

Nonnegative integer-valued time series arises in many applications. A time series model: first-order Integer-valued AutoRegressive (INAR(1)) is constructed by binomial thinning operator to model nonnegative integer-valued time series. INAR (1) depends on one period from the process before. The parameter of the model can be estimated by Conditional Least Squares (CLS). Specification of INAR(1) is following the specification of (AR(1)). Forecasting in INAR(1) uses median or Bayesian forecasting methodology. Median forecasting methodology obtains integer s, which is cumulative density function (CDF) until s, is more than or equal to 0.5. Bayesian forecasting methodology forecasts h-step-ahead of generating the parameter of the model and parameter of innovation term using Adaptive Rejection Metropolis Sampling within Gibbs sampling (ARMS), then finding the least integer s, where CDF until s is more than or equal to u . u is a value taken from the Uniform(0,1) distribution. INAR(1) is applied on pneumonia case in Penjaringan, Jakarta Utara, January 2008 until April 2016 monthly.

Vector calculus in non-integer dimensional space and its applications to fractal media

NASA Astrophysics Data System (ADS)

Tarasov, Vasily E.

2015-02-01

We suggest a generalization of vector calculus for the case of non-integer dimensional space. The first and second orders operations such as gradient, divergence, the scalar and vector Laplace operators for non-integer dimensional space are defined. For simplification we consider scalar and vector fields that are independent of angles. We formulate a generalization of vector calculus for rotationally covariant scalar and vector functions. This generalization allows us to describe fractal media and materials in the framework of continuum models with non-integer dimensional space. As examples of application of the suggested calculus, we consider elasticity of fractal materials (fractal hollow ball and fractal cylindrical pipe with pressure inside and outside), steady distribution of heat in fractal media, electric field of fractal charged cylinder. We solve the correspondent equations for non-integer dimensional space models.

Trace of totally positive algebraic integers and integer transfinite diameter

NASA Astrophysics Data System (ADS)

Flammang, V.

2009-06-01

Explicit auxiliary functions can be used in the ``Schur-Siegel- Smyth trace problem''. In the previous works, these functions were constructed only with polynomials having all their roots positive. Here, we use several polynomials with complex roots, which are found with Wu's algorithm, and we improve the known lower bounds for the absolute trace of totally positive algebraic integers. This improvement has a consequence for the search of Salem numbers that have a negative trace. The same method also gives a small improvement of the upper bound for the integer transfinite diameter of [0,1].

Integer cosine transform for image compression

NASA Technical Reports Server (NTRS)

Cheung, K.-M.; Pollara, F.; Shahshahani, M.

1991-01-01

This article describes a recently introduced transform algorithm called the integer cosine transform (ICT), which is used in transform-based data compression schemes. The ICT algorithm requires only integer operations on small integers and at the same time gives a rate-distortion performance comparable to that offered by the floating-point discrete cosine transform (DCT). The article addresses the issue of implementation complexity, which is of prime concern for source coding applications of interest in deep-space communications. Complexity reduction in the transform stage of the compression scheme is particularly relevant, since this stage accounts for most (typically over 80 percent) of the computational load.

Solving a mathematical model integrating unequal-area facilities layout and part scheduling in a cellular manufacturing system by a genetic algorithm.

PubMed

Ebrahimi, Ahmad; Kia, Reza; Komijan, Alireza Rashidi

2016-01-01

In this article, a novel integrated mixed-integer nonlinear programming model is presented for designing a cellular manufacturing system (CMS) considering machine layout and part scheduling problems simultaneously as interrelated decisions. The integrated CMS model is formulated to incorporate several design features including part due date, material handling time, operation sequence, processing time, an intra-cell layout of unequal-area facilities, and part scheduling. The objective function is to minimize makespan, tardiness penalties, and material handling costs of inter-cell and intra-cell movements. Two numerical examples are solved by the Lingo software to illustrate the results obtained by the incorporated features. In order to assess the effects and importance of integration of machine layout and part scheduling in designing a CMS, two approaches, sequentially and concurrent are investigated and the improvement resulted from a concurrent approach is revealed. Also, due to the NP-hardness of the integrated model, an efficient genetic algorithm is designed. As a consequence, computational results of this study indicate that the best solutions found by GA are better than the solutions found by B&B in much less time for both sequential and concurrent approaches. Moreover, the comparisons between the objective function values (OFVs) obtained by sequential and concurrent approaches demonstrate that the OFV improvement is averagely around 17 % by GA and 14 % by B&B.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

New mathematical modeling for a location-routing-inventory problem in a multi-period closed-loop supply chain in a car industry

NASA Astrophysics Data System (ADS)

Forouzanfar, F.; Tavakkoli-Moghaddam, R.; Bashiri, M.; Baboli, A.; Hadji Molana, S. M.

2017-11-01

This paper studies a location-routing-inventory problem in a multi-period closed-loop supply chain with multiple suppliers, producers, distribution centers, customers, collection centers, recovery, and recycling centers. In this supply chain, centers are multiple levels, a price increase factor is considered for operational costs at centers, inventory and shortage (including lost sales and backlog) are allowed at production centers, arrival time of vehicles of each plant to its dedicated distribution centers and also departure from them are considered, in such a way that the sum of system costs and the sum of maximum time at each level should be minimized. The aforementioned problem is formulated in the form of a bi-objective nonlinear integer programming model. Due to the NP-hard nature of the problem, two meta-heuristics, namely, non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO), are used in large sizes. In addition, a Taguchi method is used to set the parameters of these algorithms to enhance their performance. To evaluate the efficiency of the proposed algorithms, the results for small-sized problems are compared with the results of the ɛ-constraint method. Finally, four measuring metrics, namely, the number of Pareto solutions, mean ideal distance, spacing metric, and quality metric, are used to compare NSGA-II and MOPSO.

High Penetration of Electrical Vehicles in Microgrids: Threats and Opportunities

NASA Astrophysics Data System (ADS)

Khederzadeh, Mojtaba; Khalili, Mohammad

2014-10-01

Given that the microgrid concept is the building block of future electric distribution systems and electrical vehicles (EVs) are the future of transportation market, in this paper, the impact of EVs on the performance of microgrids is investigated. Demand-side participation is used to cope with increasing demand for EV charging. The problem of coordination of EV charging and discharging (with vehicle-to-grid (V2G) functionality) and demand response is formulated as a market-clearing mechanism that accepts bids from the demand and supply sides and takes into account the constraints put forward by different parts. Therefore, a day-ahead market with detailed bids and offers within the microgrid is designed whose objective is to maximize the social welfare which is the difference between the value that consumers attach to the electrical energy they buy plus the benefit of the EV owners participating in the V2G functionality and the cost of producing/purchasing this energy. As the optimization problem is a mixed integer nonlinear programming one, it is decomposed into one master problem for energy scheduling and one subproblem for power flow computation. The two problems are solved iteratively by interfacing MATLAB with GAMS. Simulation results on a sample microgrid with different residential, commercial and industrial consumers with associated demand-side biddings and different penetration level of EVs support the proposed formulation of the problem and the applied methods.

A multistage stochastic programming model for a multi-period strategic expansion of biofuel supply chain under evolving uncertainties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Fei; Huang, Yongxi

Here, we develop a multistage, stochastic mixed-integer model to support biofuel supply chain expansion under evolving uncertainties. By utilizing the block-separable recourse property, we reformulate the multistage program in an equivalent two-stage program and solve it using an enhanced nested decomposition method with maximal non-dominated cuts. We conduct extensive numerical experiments and demonstrate the application of the model and algorithm in a case study based on the South Carolina settings. The value of multistage stochastic programming method is also explored by comparing the model solution with the counterparts of an expected value based deterministic model and a two-stage stochastic model.

A multistage stochastic programming model for a multi-period strategic expansion of biofuel supply chain under evolving uncertainties

DOE PAGES

Xie, Fei; Huang, Yongxi

2018-02-04

Here, we develop a multistage, stochastic mixed-integer model to support biofuel supply chain expansion under evolving uncertainties. By utilizing the block-separable recourse property, we reformulate the multistage program in an equivalent two-stage program and solve it using an enhanced nested decomposition method with maximal non-dominated cuts. We conduct extensive numerical experiments and demonstrate the application of the model and algorithm in a case study based on the South Carolina settings. The value of multistage stochastic programming method is also explored by comparing the model solution with the counterparts of an expected value based deterministic model and a two-stage stochastic model.

Non-Destructive Evaluation of Kissing Bonds using Local Defect Resonance (LDR) Spectroscopy: A Simulation Study

NASA Astrophysics Data System (ADS)

Delrue, S.; Tabatabaeipour, M.; Hettler, J.; Van Den Abeele, K.

With the growing demand from industry to optimize and further develop existing Non-Destructive Testing & Evaluation (NDT&E) techniques or new methods to detect and characterize incipient damage with high sensitivity and increased quality, ample efforts have been devoted to better understand the typical behavior of kissing bonds, such as delaminations and cracks. Recently, it has been shown experimentally that the nonlinear ultrasonic response of kissing bonds could be enhanced by using Local Defect Resonance (LDR) spectroscopy. LDR spectroscopy is an efficient NDT technique that takes advantage of the characteristic fre- quencies of the defect (defect resonances) in order to provide maximum acoustic wave-defect interaction. In fact, for nonlinear methodologies, the ultrasonic excitation of the sample should occur at either multiples or integer ratios of the characteristic defect resonance frequencies, in order to obtain the highest signal-to-noise response in the nonlinear LDR spectroscopy. In this paper, the potential of using LDR spectroscopy for the detection, localization and characterization of kissing bonds is illustrated using a 3D simulation code for elastic wave propagation in materials containing closed but dynamically active cracks or delaminations. Using the model, we are able to define an appropriate method, based on the Scaling Subtraction Method (SSM), to determine the local defect resonance frequencies of a delamination in a composite plate and to illustrate an increase in defect nonlinearity due to LDR. The simulation results will help us to obtain a better understanding of the concept of LDR and to assist in the further design and testing of LDR spectroscopy for the detection, localization and characterization of kissing bonds.

Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities.

PubMed

Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad

2018-06-01

This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.

Elliptic Curve Integral Points on y2 = x3 + 3x ‑ 14

NASA Astrophysics Data System (ADS)

Zhao, Jianhong

2018-03-01

The positive integer points and integral points of elliptic curves are very important in the theory of number and arithmetic algebra, it has a wide range of applications in cryptography and other fields. There are some results of positive integer points of elliptic curve y 2 = x 3 + ax + b, a, b ∈ Z In 1987, D. Zagier submit the question of the integer points on y 2 = x 3 ‑ 27x + 62, it count a great deal to the study of the arithmetic properties of elliptic curves. In 2009, Zhu H L and Chen J H solved the problem of the integer points on y 2 = x 3 ‑ 27x + 62 by using algebraic number theory and P-adic analysis method. In 2010, By using the elementary method, Wu H M obtain all the integral points of elliptic curves y 2 = x 3 ‑ 27x ‑ 62. In 2015, Li Y Z and Cui B J solved the problem of the integer points on y 2 = x 3 ‑ 21x ‑ 90 By using the elementary method. In 2016, Guo J solved the problem of the integer points on y 2 = x 3 + 27x + 62 by using the elementary method. In 2017, Guo J proved that y 2 = x 3 ‑ 21x + 90 has no integer points by using the elementary method. Up to now, there is no relevant conclusions on the integral points of elliptic curves y 2 = x 3 + 3x ‑ 14, which is the subject of this paper. By using congruence and Legendre Symbol, it can be proved that elliptic curve y 2 = x 3 + 3x ‑ 14 has only one integer point: (x, y) = (2, 0).

Integer aperture ambiguity resolution based on difference test

NASA Astrophysics Data System (ADS)

Zhang, Jingyu; Wu, Meiping; Li, Tao; Zhang, Kaidong

2015-07-01

Carrier-phase integer ambiguity resolution (IAR) is the key to highly precise, fast positioning and attitude determination with Global Navigation Satellite System (GNSS). It can be seen as the process of estimating the unknown cycle ambiguities of the carrier-phase observations as integers. Once the ambiguities are fixed, carrier phase data will act as the very precise range data. Integer aperture (IA) ambiguity resolution is the combination of acceptance testing and integer ambiguity resolution, which can realize better quality control of IAR. Difference test (DT) is one of the most popular acceptance tests. This contribution will give a detailed analysis about the following properties of IA ambiguity resolution based on DT: 1. The sharpest and loose upper bounds of DT are derived from the perspective of geometry. These bounds are very simple and easy to be computed, which give the range for the critical values of DT.

Naval Postgraduate School Aircraft Synthesis Program (User’s Manual)

DTIC Science & Technology

1991-09-01

LOGICAL DVFLAG CHARACTER ANS*6, TITLE*80, PHASE*8 INTEGER EN REAL MACHI, M&CH2 DIMENSION ALTD(6), XM& CH (6) 6590 IF(DVFLAG.EQ. .FALSE.) THEN !GIVE OPTION TO...7800 7840 WRITE (6, 78 45) 7845 FORMAT(/7X,’ENTER THE HORIZONTAL TAIL/CANARD’/ &7X,’WEIGHT SLOPE: ’,$) READ(5,7826,ERR-7840) SLOPE(3) IF((SLOPE(3).LT

Formal Semanol Specification of Ada.

DTIC Science & Technology

1980-09-01

concurrent task modeling involved very little change to the SEMANOL metalanguage. A primitive capable of initiating concurrent SEMANOL task processors...i.e., #CO-COMPUTE) and two primitivc-; corresponding to integer semaphores (i.c., #P and #V) were all that were required. In addition, these changes... synchronization techniques and choice of correct unblocking alternatives. We should note that it had been our original intention to use the Ada Translator program

HIPPO Unit Commitment Version 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

2017-01-17

Developed for the Midcontinent Independent System Operator, Inc. (MISO), HIPPO-Unit Commitment Version 1 is for solving security constrained unit commitment problem. The model was developed to solve MISO's cases. This version of codes includes I/O module to read in MISO's csv files, modules to create a state-based mixed integer programming formulation for solving MIP, and modules to test basic procedures to solve MIP via HPC.

Item Selection for the Development of Parallel Forms from an IRT-Based Seed Test Using a Sampling and Classification Approach

ERIC Educational Resources Information Center

Chen, Pei-Hua; Chang, Hua-Hua; Wu, Haiyan

2012-01-01

Two sampling-and-classification-based procedures were developed for automated test assembly: the Cell Only and the Cell and Cube methods. A simulation study based on a 540-item bank was conducted to compare the performance of the procedures with the performance of a mixed-integer programming (MIP) method for assembling multiple parallel test…

Optimum use of air tankers in initial attack: selection, basing, and transfer rules

Treesearch

Francis E. Greulich; William G. O' Regan

1982-01-01

Fire managers face two interrelated problems in deciding the most efficient use of air tankers: where best to base them, and how best to reallocate them each day in anticipation of fire occurrence. A computerized model based on a mixed integer linear program can help in assigning air tankers throughout the fire season. The model was tested using information from...

Towards a theory of automated elliptic mesh generation

NASA Technical Reports Server (NTRS)

Cordova, J. Q.

1992-01-01

The theory of elliptic mesh generation is reviewed and the fundamental problem of constructing computational space is discussed. It is argued that the construction of computational space is an NP-Complete problem and therefore requires a nonstandard approach for its solution. This leads to the development of graph-theoretic, combinatorial optimization and integer programming algorithms. Methods for the construction of two dimensional computational space are presented.

A Generalized Distance’ Estimation Procedure for Intra-Urban Interaction

DTIC Science & Technology

Bettinger . It is found that available estimation techniques necessarily result in non-integer solutions. A mathematical device is therefore...The estimation of urban and regional travel patterns has been a necessary part of current efforts to establish land use guidelines for the Texas...paper details computational experience with travel estimation within Corpus Christi, Texas, using a new convex programming approach of Charnes, Raike and

MIADS2 ... an alphanumeric map information assembly and display system for a large computer

Treesearch

Elliot L. Amidon

1966-01-01

A major improvement and extension of the Map Information Assembly and Display System (MIADS) developed in 1964 is described. Basic principles remain unchanged, but the computer programs have been expanded and rewritten for a large computer, in Fortran IV and MAP languages. The code system is extended from 99 integers to about 2,200 alphanumeric 2-character codes. Hand-...

Cloud-based large-scale air traffic flow optimization

NASA Astrophysics Data System (ADS)

Cao, Yi

The ever-increasing traffic demand makes the efficient use of airspace an imperative mission, and this paper presents an effort in response to this call. Firstly, a new aggregate model, called Link Transmission Model (LTM), is proposed, which models the nationwide traffic as a network of flight routes identified by origin-destination pairs. The traversal time of a flight route is assumed to be the mode of distribution of historical flight records, and the mode is estimated by using Kernel Density Estimation. As this simplification abstracts away physical trajectory details, the complexity of modeling is drastically decreased, resulting in efficient traffic forecasting. The predicative capability of LTM is validated against recorded traffic data. Secondly, a nationwide traffic flow optimization problem with airport and en route capacity constraints is formulated based on LTM. The optimization problem aims at alleviating traffic congestions with minimal global delays. This problem is intractable due to millions of variables. A dual decomposition method is applied to decompose the large-scale problem such that the subproblems are solvable. However, the whole problem is still computational expensive to solve since each subproblem is an smaller integer programming problem that pursues integer solutions. Solving an integer programing problem is known to be far more time-consuming than solving its linear relaxation. In addition, sequential execution on a standalone computer leads to linear runtime increase when the problem size increases. To address the computational efficiency problem, a parallel computing framework is designed which accommodates concurrent executions via multithreading programming. The multithreaded version is compared with its monolithic version to show decreased runtime. Finally, an open-source cloud computing framework, Hadoop MapReduce, is employed for better scalability and reliability. This framework is an "off-the-shelf" parallel computing model that can be used for both offline historical traffic data analysis and online traffic flow optimization. It provides an efficient and robust platform for easy deployment and implementation. A small cloud consisting of five workstations was configured and used to demonstrate the advantages of cloud computing in dealing with large-scale parallelizable traffic problems.

Nonlinear acoustic experiments for landmine detection: the significance of the top-plate normal modes

NASA Astrophysics Data System (ADS)

Korman, Murray S.; Alberts, W. C. K., II; Sabatier, James M.

2004-09-01

In nonlinear acoustic detection experiments involving a buried inert VS 2.2 anti-tank landmine, airborne sound at two closely spaced primary frequencies f1 and f2 couple into the ground and interact nonlinearly with the soil-top pressure plate interface. Scattering generates soil vibration at the surface at the combination frequencies | m f1 +- n f2 | , where m and n are integers. The normal component of the particle velocity at the soil surface has been measured with a laser Doppler velocimeter (LDV) and with a geophone by Sabatier et. al. [SPIE Proceedings Vol. 4742, (695-700), 2002; Vol. 5089, (476-486), 2003] at the gravel lane test site. Spatial profiles of the particle velocity measured for both primary components and for various combination frequencies indicate that the modal structure of the mine is playing an important role. Here, an experimental modal analysis is performed on a VS 1.6 inert anti-tank mine that is resting on sand but is not buried. Five top-plate mode shapes are described. The mine is then buried in dry finely sifted natural loess soil and excited at f1 = 120 Hz and f2 = 130 Hz. Spatial profiles at the primary components and the nonlinearly generated f1 - (f2 - f1) component are characterized by a single peak. For the 2f1+f2 and 2f2 + f1 components, the doubly peaked profiles can be attributed to the familiar mode shape of a timpani drum (that is shifted lower in frequency due to soil mass loading). Other nonlinear profiles appear to be due to a mixture of modes. This material is based upon work supported by the U. S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate under Contract DAAB15-02-C-0024.

Solving intuitionistic fuzzy multi-objective nonlinear programming problem

NASA Astrophysics Data System (ADS)

Anuradha, D.; Sobana, V. E.

2017-11-01

This paper presents intuitionistic fuzzy multi-objective nonlinear programming problem (IFMONLPP). All the coefficients of the multi-objective nonlinear programming problem (MONLPP) and the constraints are taken to be intuitionistic fuzzy numbers (IFN). The IFMONLPP has been transformed into crisp one and solved by using Kuhn-Tucker condition. Numerical example is provided to illustrate the approach.

A Converse of a Result about the Floor Function by Hermite

ERIC Educational Resources Information Center

Mortici, Cristinel

2012-01-01

The floor function maps a real number to the largest previous integer. More precisely, floor(x)=[x] is the largest integer not greater than x. The square bracket notation [x] for the floor function was introduced by Gauss in his third proof of quadratic reciprocity in 1808. The floor function is also called the greatest integer or entier (French…

Using Integer Clocks to Verify the Timing-Sync Sensor Network Protocol

NASA Technical Reports Server (NTRS)

Huang, Xiaowan; Singh, Anu; Smolka, Scott A.

2010-01-01

We use the UPPAAL model checker for Timed Automata to verify the Timing-Sync time-synchronization protocol for sensor networks (TPSN). The TPSN protocol seeks to provide network-wide synchronization of the distributed clocks in a sensor network. Clock-synchronization algorithms for sensor networks such as TPSN must be able to perform arithmetic on clock values to calculate clock drift and network propagation delays. They must be able to read the value of a local clock and assign it to another local clock. Such operations are not directly supported by the theory of Timed Automata. To overcome this formal-modeling obstacle, we augment the UPPAAL specification language with the integer clock derived type. Integer clocks, which are essentially integer variables that are periodically incremented by a global pulse generator, greatly facilitate the encoding of the operations required to synchronize clocks as in the TPSN protocol. With this integer-clock-based model of TPSN in hand, we use UPPAAL to verify that the protocol achieves network-wide time synchronization and is devoid of deadlock. We also use the UPPAAL Tracer tool to illustrate how integer clocks can be used to capture clock drift and resynchronization during protocol execution

System and method for generating attitude determinations using GPS

NASA Technical Reports Server (NTRS)

Cohen, Clark E. (Inventor)

1996-01-01

A GPS attitude receiver for determining the attitude of a moving vehicle in conjunction with a first, a second, a third, and a fourth antenna mounted to the moving vehicle. Each of the antennas receives a plurality of GPS signals that each include a carrier component. For each of the carrier components of the received GPS signals there is an integer ambiguity associated with the first and fourth antennas, an integer ambiguity associated with second and fourth antennas, and an integer ambiguity associated with the third and fourth antennas. The GPS attitude receiver measures phase values for the carrier components of the GPS signals received from each of the antennas at a plurality of measurement epochs during an initialization period and at a measurement epoch after the initialization period. In response to the phase values measured at the measurement epochs during the initialization period, the GPS attitude receiver computes integer ambiguity resolution values representing resolution of the integer ambiguities. Then, in response to the computed integer ambiguity resolution values and the phase value measured at the measurement epoch after the initialization period, it computes values defining the attitude of the moving vehicle at the measurement epoch after the initialization period.

A parallel metaheuristic for large mixed-integer dynamic optimization problems, with applications in computational biology

PubMed Central

Henriques, David; González, Patricia; Doallo, Ramón; Saez-Rodriguez, Julio; Banga, Julio R.

2017-01-01

Background We consider a general class of global optimization problems dealing with nonlinear dynamic models. Although this class is relevant to many areas of science and engineering, here we are interested in applying this framework to the reverse engineering problem in computational systems biology, which yields very large mixed-integer dynamic optimization (MIDO) problems. In particular, we consider the framework of logic-based ordinary differential equations (ODEs). Methods We present saCeSS2, a parallel method for the solution of this class of problems. This method is based on an parallel cooperative scatter search metaheuristic, with new mechanisms of self-adaptation and specific extensions to handle large mixed-integer problems. We have paid special attention to the avoidance of convergence stagnation using adaptive cooperation strategies tailored to this class of problems. Results We illustrate its performance with a set of three very challenging case studies from the domain of dynamic modelling of cell signaling. The simpler case study considers a synthetic signaling pathway and has 84 continuous and 34 binary decision variables. A second case study considers the dynamic modeling of signaling in liver cancer using high-throughput data, and has 135 continuous and 109 binaries decision variables. The third case study is an extremely difficult problem related with breast cancer, involving 690 continuous and 138 binary decision variables. We report computational results obtained in different infrastructures, including a local cluster, a large supercomputer and a public cloud platform. Interestingly, the results show how the cooperation of individual parallel searches modifies the systemic properties of the sequential algorithm, achieving superlinear speedups compared to an individual search (e.g. speedups of 15 with 10 cores), and significantly improving (above a 60%) the performance with respect to a non-cooperative parallel scheme. The scalability of the method is also good (tests were performed using up to 300 cores). Conclusions These results demonstrate that saCeSS2 can be used to successfully reverse engineer large dynamic models of complex biological pathways. Further, these results open up new possibilities for other MIDO-based large-scale applications in the life sciences such as metabolic engineering, synthetic biology, drug scheduling. PMID:28813442

A parallel metaheuristic for large mixed-integer dynamic optimization problems, with applications in computational biology.

PubMed

Penas, David R; Henriques, David; González, Patricia; Doallo, Ramón; Saez-Rodriguez, Julio; Banga, Julio R

2017-01-01

We consider a general class of global optimization problems dealing with nonlinear dynamic models. Although this class is relevant to many areas of science and engineering, here we are interested in applying this framework to the reverse engineering problem in computational systems biology, which yields very large mixed-integer dynamic optimization (MIDO) problems. In particular, we consider the framework of logic-based ordinary differential equations (ODEs). We present saCeSS2, a parallel method for the solution of this class of problems. This method is based on an parallel cooperative scatter search metaheuristic, with new mechanisms of self-adaptation and specific extensions to handle large mixed-integer problems. We have paid special attention to the avoidance of convergence stagnation using adaptive cooperation strategies tailored to this class of problems. We illustrate its performance with a set of three very challenging case studies from the domain of dynamic modelling of cell signaling. The simpler case study considers a synthetic signaling pathway and has 84 continuous and 34 binary decision variables. A second case study considers the dynamic modeling of signaling in liver cancer using high-throughput data, and has 135 continuous and 109 binaries decision variables. The third case study is an extremely difficult problem related with breast cancer, involving 690 continuous and 138 binary decision variables. We report computational results obtained in different infrastructures, including a local cluster, a large supercomputer and a public cloud platform. Interestingly, the results show how the cooperation of individual parallel searches modifies the systemic properties of the sequential algorithm, achieving superlinear speedups compared to an individual search (e.g. speedups of 15 with 10 cores), and significantly improving (above a 60%) the performance with respect to a non-cooperative parallel scheme. The scalability of the method is also good (tests were performed using up to 300 cores). These results demonstrate that saCeSS2 can be used to successfully reverse engineer large dynamic models of complex biological pathways. Further, these results open up new possibilities for other MIDO-based large-scale applications in the life sciences such as metabolic engineering, synthetic biology, drug scheduling.

Scheduling the resident 80-hour work week: an operations research algorithm.

PubMed

Day, T Eugene; Napoli, Joseph T; Kuo, Paul C

2006-01-01

The resident 80-hour work week requires that programs now schedule duty hours. Typically, scheduling is performed in an empirical "trial-and-error" fashion. However, this is a classic "scheduling" problem from the field of operations research (OR). It is similar to scheduling issues that airlines must face with pilots and planes routing through various airports at various times. The authors hypothesized that an OR approach using iterative computer algorithms could provide a rational scheduling solution. Institution-specific constraints of the residency problem were formulated. A total of 56 residents are rotating through 4 hospitals. Additional constraints were dictated by the Residency Review Committee (RRC) rules or the specific surgical service. For example, at Hospital 1, during the weekday hours between 6 am and 6 pm, there will be a PGY4 or PGY5 and a PGY2 or PGY3 on-duty to cover Service "A." A series of equations and logic statements was generated to satisfy all constraints and requirements. These were restated in the Optimization Programming Language used by the ILOG software suite for solving mixed integer programming problems. An integer programming solution was generated to this resource-constrained assignment problem. A total of 30,900 variables and 12,443 constraints were required. A total of man-hours of programming were used; computer run-time was 25.9 hours. A weekly schedule was generated for each resident that satisfied the RRC regulations while fulfilling all stated surgical service requirements. Each required between 64 and 80 weekly resident duty hours. The authors conclude that OR is a viable approach to schedule resident work hours. This technique is sufficiently robust to accommodate changes in resident numbers, service requirements, and service and hospital rotations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cook, J.; Derrida, B.

The problem of directed polymers on disordered hierarchical and hypercubic lattices is considered. For the hierarchical lattices the problem can be reduced to the study of the stable laws for combining random variables in a nonlinear way. The authors present the results of numerical simulations of two hierarchical lattices, finding evidence of a phase transition in one case. For a limiting case they extend the perturbation theory developed by Derrida and Griffiths to nonzero temperature and to higher order and use this approach to calculate thermal and geometrical properties (overlaps) of the model. In this limit they obtain an interpolationmore » formula, allowing one to obtain the noninteger moments of the partition function from the integer moments. They obtain bounds for the transition temperature for hierarchical and hypercubic lattices, and some similarities between the problem on the two different types of lattice are discussed.« less

A chaotic secure communication scheme using fractional chaotic systems based on an extended fractional Kalman filter

NASA Astrophysics Data System (ADS)

Kiani-B, Arman; Fallahi, Kia; Pariz, Naser; Leung, Henry

2009-03-01

In recent years chaotic secure communication and chaos synchronization have received ever increasing attention. In this paper, for the first time, a fractional chaotic communication method using an extended fractional Kalman filter is presented. The chaotic synchronization is implemented by the EFKF design in the presence of channel additive noise and processing noise. Encoding chaotic communication achieves a satisfactory, typical secure communication scheme. In the proposed system, security is enhanced based on spreading the signal in frequency and encrypting it in time domain. In this paper, the main advantages of using fractional order systems, increasing nonlinearity and spreading the power spectrum are highlighted. To illustrate the effectiveness of the proposed scheme, a numerical example based on the fractional Lorenz dynamical system is presented and the results are compared to the integer Lorenz system.

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

NASA Astrophysics Data System (ADS)

Ghosh, Pradipto

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

Process simulation and dynamic control for marine oily wastewater treatment using UV irradiation.

PubMed

Jing, Liang; Chen, Bing; Zhang, Baiyu; Li, Pu

2015-09-15

UV irradiation and advanced oxidation processes have been recently regarded as promising solutions in removing polycyclic aromatic hydrocarbons (PAHs) from marine oily wastewater. However, such treatment methods are generally not sufficiently understood in terms of reaction mechanisms, process simulation and process control. These deficiencies can drastically hinder their application in shipping and offshore petroleum industries which produce bilge/ballast water and produced water as the main streams of marine oily wastewater. In this study, the factorial design of experiment was carried out to investigate the degradation mechanism of a typical PAH, namely naphthalene, under UV irradiation in seawater. Based on the experimental results, a three-layer feed-forward artificial neural network simulation model was developed to simulate the treatment process and to forecast the removal performance. A simulation-based dynamic mixed integer nonlinear programming (SDMINP) approach was then proposed to intelligently control the treatment process by integrating the developed simulation model, genetic algorithm and multi-stage programming. The applicability and effectiveness of the developed approach were further tested though a case study. The experimental results showed that the influences of fluence rate and temperature on the removal of naphthalene were greater than those of salinity and initial concentration. The developed simulation model could well predict the UV-induced removal process under varying conditions. The case study suggested that the SDMINP approach, with the aid of the multi-stage control strategy, was able to significantly reduce treatment cost when comparing to the traditional single-stage process optimization. The developed approach and its concept/framework have high potential of applicability in other environmental fields where a treatment process is involved and experimentation and modeling are used for process simulation and control. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dynamic Distributed Cooperative Control of Multiple Heterogeneous Resources

DTIC Science & Technology

2012-10-01

of the UAVs to maximize the total sensor footprint over the region of interest. The algorithm utilized to solve this problem was based on sampling a...and moving obstacles. Obstacle positions were assumed known a priori. Kingston and Beard [22] presented an algorithm to keep moving UAVs equally spaced...Planning Algorithms , Cambridge University Press, 2006. 11. Ma, C. S. and Miller, R. H., “Mixed integer linear programming trajectory generation for

An Advanced Tabu Search Approach to Solving the Mixed Payload Airlift Load Planning Problem

DTIC Science & Technology

2009-03-01

cargo, and the problem therefore becomes trivial. 3. Shoring: Some cargo requires shoring which is small planks of plywood stacked on top of each...Integer Programming Method In 1989, Kevin Ng examined the bin-packing MPALP for Canada’s C-130 aircraft (Ng 1992). His goal was to move a set of... leadership & ethics [ ] warfighting [ ] international security [ ] doctrine [X] other (specify): Military Airlift

Optimal Partitioning of a Surveillance Space for Persistent Coverage Using Multiple Autonomous Unmanned Aerial Vehicles: An Integer Programming Approach

DTIC Science & Technology

2014-03-27

asymptotically equal. Carlsson shows that the problem is solved by treating each subregion Ri as a traveling salesman problem (TSP) with a set of points that...terminal state to the goal. If no- travel zones are repre- sented as the union of regions Akx > Bk, the coverage problem can be expressed as an IP [14...3 1.2 Problem Statement

Optimized Waterspace Management and Scheduling Using Mixed-Integer Linear Programming

DTIC Science & Technology

2016-01-01

Complete [30]. Proposition 4.1 satisfies the first criterion. For the second criterion, we will use the Traveling Salesman Problem (TSP), which has been...A branch and cut algorithm for the symmetric generalized traveling salesman problem , Operations Research 45 (1997) 378–394. [33] J. Silberholz, B...Golden, The generalized traveling salesman problem : A new genetic algorithm ap- proach, Extended Horizons: Advances in Computing, Optimization, and

Uncluttered Single-Image Visualization of Vascular Structures using GPU and Integer Programming

PubMed Central

Won, Joong-Ho; Jeon, Yongkweon; Rosenberg, Jarrett; Yoon, Sungroh; Rubin, Geoffrey D.; Napel, Sandy

2013-01-01

Direct projection of three-dimensional branching structures, such as networks of cables, blood vessels, or neurons onto a 2D image creates the illusion of intersecting structural parts and creates challenges for understanding and communication. We present a method for visualizing such structures, and demonstrate its utility in visualizing the abdominal aorta and its branches, whose tomographic images might be obtained by computed tomography or magnetic resonance angiography, in a single two-dimensional stylistic image, without overlaps among branches. The visualization method, termed uncluttered single-image visualization (USIV), involves optimization of geometry. This paper proposes a novel optimization technique that utilizes an interesting connection of the optimization problem regarding USIV to the protein structure prediction problem. Adopting the integer linear programming-based formulation for the protein structure prediction problem, we tested the proposed technique using 30 visualizations produced from five patient scans with representative anatomical variants in the abdominal aortic vessel tree. The novel technique can exploit commodity-level parallelism, enabling use of general-purpose graphics processing unit (GPGPU) technology that yields a significant speedup. Comparison of the results with the other optimization technique previously reported elsewhere suggests that, in most aspects, the quality of the visualization is comparable to that of the previous one, with a significant gain in the computation time of the algorithm. PMID:22291148

An integer programming formulation of the parsimonious loss of heterozygosity problem.

PubMed

Catanzaro, Daniele; Labbé, Martine; Halldórsson, Bjarni V

2013-01-01

A loss of heterozygosity (LOH) event occurs when, by the laws of Mendelian inheritance, an individual should be heterozygote at a given site but, due to a deletion polymorphism, is not. Deletions play an important role in human disease and their detection could provide fundamental insights for the development of new diagnostics and treatments. In this paper, we investigate the parsimonious loss of heterozygosity problem (PLOHP), i.e., the problem of partitioning suspected polymorphisms from a set of individuals into a minimum number of deletion areas. Specifically, we generalize Halldórsson et al.'s work by providing a more general formulation of the PLOHP and by showing how one can incorporate different recombination rates and prior knowledge about the locations of deletions. Moreover, we show that the PLOHP can be formulated as a specific version of the clique partition problem in a particular class of graphs called undirected catch-point interval graphs and we prove its general $({\\cal NP})$-hardness. Finally, we provide a state-of-the-art integer programming (IP) formulation and strengthening valid inequalities to exactly solve real instances of the PLOHP containing up to 9,000 individuals and 3,000 SNPs. Our results give perspectives on the mathematics of the PLOHP and suggest new directions on the development of future efficient exact solution approaches.

Predicting protein contact map using evolutionary and physical constraints by integer programming.

PubMed

Wang, Zhiyong; Xu, Jinbo

2013-07-01

Protein contact map describes the pairwise spatial and functional relationship of residues in a protein and contains key information for protein 3D structure prediction. Although studied extensively, it remains challenging to predict contact map using only sequence information. Most existing methods predict the contact map matrix element-by-element, ignoring correlation among contacts and physical feasibility of the whole-contact map. A couple of recent methods predict contact map by using mutual information, taking into consideration contact correlation and enforcing a sparsity restraint, but these methods demand for a very large number of sequence homologs for the protein under consideration and the resultant contact map may be still physically infeasible. This article presents a novel method PhyCMAP for contact map prediction, integrating both evolutionary and physical restraints by machine learning and integer linear programming. The evolutionary restraints are much more informative than mutual information, and the physical restraints specify more concrete relationship among contacts than the sparsity restraint. As such, our method greatly reduces the solution space of the contact map matrix and, thus, significantly improves prediction accuracy. Experimental results confirm that PhyCMAP outperforms currently popular methods no matter how many sequence homologs are available for the protein under consideration. http://raptorx.uchicago.edu.

The whole number axis integer linear transformation reversible information hiding algorithm on wavelet domain

NASA Astrophysics Data System (ADS)

Jiang, Zhuo; Xie, Chengjun

2013-12-01

This paper improved the algorithm of reversible integer linear transform on finite interval [0,255], which can realize reversible integer linear transform in whole number axis shielding data LSB (least significant bit). Firstly, this method use integer wavelet transformation based on lifting scheme to transform the original image, and select the transformed high frequency areas as information hiding area, meanwhile transform the high frequency coefficients blocks in integer linear way and embed the secret information in LSB of each coefficient, then information hiding by embedding the opposite steps. To extract data bits and recover the host image, a similar reverse procedure can be conducted, and the original host image can be lossless recovered. The simulation experimental results show that this method has good secrecy and concealment, after conducted the CDF (m, n) and DD (m, n) series of wavelet transformed. This method can be applied to information security domain, such as medicine, law and military.

A GA based penalty function technique for solving constrained redundancy allocation problem of series system with interval valued reliability of components

NASA Astrophysics Data System (ADS)

Gupta, R. K.; Bhunia, A. K.; Roy, D.

2009-10-01

In this paper, we have considered the problem of constrained redundancy allocation of series system with interval valued reliability of components. For maximizing the overall system reliability under limited resource constraints, the problem is formulated as an unconstrained integer programming problem with interval coefficients by penalty function technique and solved by an advanced GA for integer variables with interval fitness function, tournament selection, uniform crossover, uniform mutation and elitism. As a special case, considering the lower and upper bounds of the interval valued reliabilities of the components to be the same, the corresponding problem has been solved. The model has been illustrated with some numerical examples and the results of the series redundancy allocation problem with fixed value of reliability of the components have been compared with the existing results available in the literature. Finally, sensitivity analyses have been shown graphically to study the stability of our developed GA with respect to the different GA parameters.

Java Programming Language

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali

2007-01-01

The Java seminar covers the fundamentals of Java programming language. No prior programming experience is required for participation in the seminar. The first part of the seminar covers introductory concepts in Java programming including data types (integer, character, ..), operators, functions and constants, casts, input, output, control flow, scope, conditional statements, and arrays. Furthermore, introduction to Object-Oriented programming in Java, relationships between classes, using packages, constructors, private data and methods, final instance fields, static fields and methods, and overloading are explained. The second part of the seminar covers extending classes, inheritance hierarchies, polymorphism, dynamic binding, abstract classes, protected access. The seminar conclude by introducing interfaces, properties of interfaces, interfaces and abstract classes, interfaces and cailbacks, basics of event handling, user interface components with swing, applet basics, converting applications to applets, the applet HTML tags and attributes, exceptions and debugging.

Edgelist phase unwrapping algorithm for time series InSAR analysis.

PubMed

Shanker, A Piyush; Zebker, Howard

2010-03-01

We present here a new integer programming formulation for phase unwrapping of multidimensional data. Phase unwrapping is a key problem in many coherent imaging systems, including time series synthetic aperture radar interferometry (InSAR), with two spatial and one temporal data dimensions. The minimum cost flow (MCF) [IEEE Trans. Geosci. Remote Sens. 36, 813 (1998)] phase unwrapping algorithm describes a global cost minimization problem involving flow between phase residues computed over closed loops. Here we replace closed loops by reliable edges as the basic construct, thus leading to the name "edgelist." Our algorithm has several advantages over current methods-it simplifies the representation of multidimensional phase unwrapping, it incorporates data from external sources, such as GPS, where available to better constrain the unwrapped solution, and it treats regularly sampled or sparsely sampled data alike. It thus is particularly applicable to time series InSAR, where data are often irregularly spaced in time and individual interferograms can be corrupted with large decorrelated regions. We show that, similar to the MCF network problem, the edgelist formulation also exhibits total unimodularity, which enables us to solve the integer program problem by using efficient linear programming tools. We apply our method to a persistent scatterer-InSAR data set from the creeping section of the Central San Andreas Fault and find that the average creep rate of 22 mm/Yr is constant within 3 mm/Yr over 1992-2004 but varies systematically with ground location, with a slightly higher rate in 1992-1998 than in 1999-2003.

Introducing difference recurrence relations for faster semi-global alignment of long sequences.

PubMed

Suzuki, Hajime; Kasahara, Masahiro

2018-02-19

The read length of single-molecule DNA sequencers is reaching 1 Mb. Popular alignment software tools widely used for analyzing such long reads often take advantage of single-instruction multiple-data (SIMD) operations to accelerate calculation of dynamic programming (DP) matrices in the Smith-Waterman-Gotoh (SWG) algorithm with a fixed alignment start position at the origin. Nonetheless, 16-bit or 32-bit integers are necessary for storing the values in a DP matrix when sequences to be aligned are long; this situation hampers the use of the full SIMD width of modern processors. We proposed a faster semi-global alignment algorithm, "difference recurrence relations," that runs more rapidly than the state-of-the-art algorithm by a factor of 2.1. Instead of calculating and storing all the values in a DP matrix directly, our algorithm computes and stores mainly the differences between the values of adjacent cells in the matrix. Although the SWG algorithm and our algorithm can output exactly the same result, our algorithm mainly involves 8-bit integer operations, enabling us to exploit the full width of SIMD operations (e.g., 32) on modern processors. We also developed a library, libgaba, so that developers can easily integrate our algorithm into alignment programs. Our novel algorithm and optimized library implementation will facilitate accelerating nucleotide long-read analysis algorithms that use pairwise alignment stages. The library is implemented in the C programming language and available at https://github.com/ocxtal/libgaba .

Quantum Hall effect in ac driven graphene: From the half-integer to the integer case

NASA Astrophysics Data System (ADS)

Ding, Kai-He; Lim, Lih-King; Su, Gang; Weng, Zheng-Yu

2018-01-01

We theoretically study the quantum Hall effect (QHE) in graphene with an ac electric field. Based on the tight-binding model, the structure of the half-integer Hall plateaus at σxy=±(n +1 /2 ) 4 e2/h (n is an integer) gets qualitatively changed with the addition of new integer Hall plateaus at σxy=±n (4 e2/h ) starting from the edges of the band center regime towards the band center with an increasing ac field. Beyond a critical field strength, a Hall plateau with σxy=0 can be realized at the band center, hence fully restoring a conventional integer QHE with particle-hole symmetry. Within a low-energy Hamiltonian for Dirac cones merging, we show a very good agreement with the tight-binding calculations for the Hall plateau transitions. We also obtain the band structure for driven graphene ribbons to provide a further understanding on the appearance of the new Hall plateaus, showing a trivial insulator behavior for the σxy=0 state. In the presence of disorder, we numerically study the disorder-induced destruction of the quantum Hall states in a finite driven sample and find that qualitative features known in the undriven disordered case are maintained.

A Polynomial Time, Numerically Stable Integer Relation Algorithm

NASA Technical Reports Server (NTRS)

Ferguson, Helaman R. P.; Bailey, Daivd H.; Kutler, Paul (Technical Monitor)

1998-01-01

Let x = (x1, x2...,xn be a vector of real numbers. X is said to possess an integer relation if there exist integers a(sub i) not all zero such that a1x1 + a2x2 + ... a(sub n)Xn = 0. Beginning in 1977 several algorithms (with proofs) have been discovered to recover the a(sub i) given x. The most efficient of these existing integer relation algorithms (in terms of run time and the precision required of the input) has the drawback of being very unstable numerically. It often requires a numeric precision level in the thousands of digits to reliably recover relations in modest-sized test problems. We present here a new algorithm for finding integer relations, which we have named the "PSLQ" algorithm. It is proved in this paper that the PSLQ algorithm terminates with a relation in a number of iterations that is bounded by a polynomial in it. Because this algorithm employs a numerically stable matrix reduction procedure, it is free from the numerical difficulties, that plague other integer relation algorithms. Furthermore, its stability admits an efficient implementation with lower run times oil average than other algorithms currently in Use. Finally, this stability can be used to prove that relation bounds obtained from computer runs using this algorithm are numerically accurate.

Method for nonlinear exponential regression analysis

NASA Technical Reports Server (NTRS)

Junkin, B. G.

1972-01-01

Two computer programs developed according to two general types of exponential models for conducting nonlinear exponential regression analysis are described. Least squares procedure is used in which the nonlinear problem is linearized by expanding in a Taylor series. Program is written in FORTRAN 5 for the Univac 1108 computer.

Do's and don'ts in Fourier analysis of steady-state potentials.

PubMed

Bach, M; Meigen, T

1999-01-01

Fourier analysis is a powerful tool in signal analysis that can be very fruitfully applied to steady-state evoked potentials (flicker ERG, pattern ERG, VEP, etc.). However, there are some inherent assumptions in the underlying discrete Fourier transform (DFT) that are not necessarily fulfilled in typical electrophysiological recording and analysis conditions. Furthermore, engineering software-packages may be ill-suited and/or may not fully exploit the information of steady-state recordings. Specifically: * In the case of steady-state stimulation we know more about the stimulus than in standard textbook situations (exact frequency, phase stability), so 'windowing' and calculation of the 'periodogram' are not necessary. * It is mandatory to choose an integer relationship between sampling rate and frame rate when employing a raster-based CRT stimulator. * The analysis interval must comprise an exact integer number (e.g., 10) of stimulus periods. * The choice of the number of stimulus periods per analysis interval needs a wise compromise: A high number increases the frequency resolution, but makes artifact removal difficult; a low number 'spills' noise into the response frequency. * There is no need to feel tied to a power-of-two number of data points as required by standard FFT, 'resampling' is an easy and efficient alternative. * Proper estimates of noise-corrected Fourier magnitude and statistical significance can be calculated that take into account the non-linear superposition of signal and noise. These aspects are developed in an intuitive approach with examples using both simulations and recordings. Proper use of Fourier analysis of our electrophysiological records will reduce recording time and/or increase the reliability of physiologic or pathologic interpretations.

Nonlinear integral equations for the sausage model

NASA Astrophysics Data System (ADS)

Ahn, Changrim; Balog, Janos; Ravanini, Francesco

2017-08-01

The sausage model, first proposed by Fateev, Onofri, and Zamolodchikov, is a deformation of the O(3) sigma model preserving integrability. The target space is deformed from the sphere to ‘sausage’ shape by a deformation parameter ν. This model is defined by a factorizable S-matrix which is obtained by deforming that of the O(3) sigma model by a parameter λ. Clues for the deformed sigma model are provided by various UV and IR information through the thermodynamic Bethe ansatz (TBA) analysis based on the S-matrix. Application of TBA to the sausage model is, however, limited to the case of 1/λ integer where the coupled integral equations can be truncated to a finite number. In this paper, we propose a finite set of nonlinear integral equations (NLIEs), which are applicable to generic value of λ. Our derivation is based on T-Q relations extracted from the truncated TBA equations. For a consistency check, we compute next-leading order corrections of the vacuum energy and extract the S-matrix information in the IR limit. We also solved the NLIE both analytically and numerically in the UV limit to get the effective central charge and compared with that of the zero-mode dynamics to obtain exact relation between ν and λ. Dedicated to the memory of Petr Petrovich Kulish.

IMPLICATIONS OF NON-LOCALITY OF TRANSPORT IN GEOMORPHIC TRANSPORT LAWS: HILLSLOPES AND LANDSCAPE EVOLUTION MODELING

NASA Astrophysics Data System (ADS)

Foufoula-Georgiou, E.; Ganti, V. K.; Dietrich, W. E.

2009-12-01

Sediment transport on hillslopes can be thought of as a hopping process, where the sediment moves in a series of jumps. A wide range of processes shape the hillslopes which can move sediment to a large distance in the downslope direction, thus, resulting in a broad-tail in the probability density function (PDF) of hopping lengths. Here, we argue that such a broad-tailed distribution calls for a non-local computation of sediment flux, where the sediment flux is not only a function of local topographic quantities but is an integral flux which takes into account the upslope topographic “memory” of the point of interest. We encapsulate this non-local behavior into a simple fractional diffusive model that involves fractional (non-integer) derivatives. We present theoretical predictions from this nonlocal model and demonstrate a nonlinear dependence of sediment flux on local gradient, consistent with observations. Further, we demonstrate that the non-local model naturally eliminates the scale-dependence exhibited by any local (linear or nonlinear) sediment transport model. An extension to a 2-D framework, where the fractional derivative can be cast into a mixture of directional derivatives, is discussed together with the implications of introducing non-locality into existing landscape evolution models.

Development of solution techniques for nonlinear structural analysis

NASA Technical Reports Server (NTRS)

Vos, R. G.; Andrews, J. S.

1974-01-01

Nonlinear structural solution methods in the current research literature are classified according to order of the solution scheme, and it is shown that the analytical tools for these methods are uniformly derivable by perturbation techniques. A new perturbation formulation is developed for treating an arbitrary nonlinear material, in terms of a finite-difference generated stress-strain expansion. Nonlinear geometric effects are included in an explicit manner by appropriate definition of an applicable strain tensor. A new finite-element pilot computer program PANES (Program for Analysis of Nonlinear Equilibrium and Stability) is presented for treatment of problems involving material and geometric nonlinearities, as well as certain forms on nonconservative loading.

Nonlinear Curve-Fitting Program

NASA Technical Reports Server (NTRS)

Everhart, Joel L.; Badavi, Forooz F.

1989-01-01

Nonlinear optimization algorithm helps in finding best-fit curve. Nonlinear Curve Fitting Program, NLINEAR, interactive curve-fitting routine based on description of quadratic expansion of X(sup 2) statistic. Utilizes nonlinear optimization algorithm calculating best statistically weighted values of parameters of fitting function and X(sup 2) minimized. Provides user with such statistical information as goodness of fit and estimated values of parameters producing highest degree of correlation between experimental data and mathematical model. Written in FORTRAN 77.

An Analysis of the Multiple Objective Capital Budgeting Problem via Fuzzy Linear Integer (0-1) Programming.

DTIC Science & Technology

1980-05-31

34 International Journal of Man- Machine Studies , Vol. 9, No. 1, 1977, pp. 1-68. [16] Zimmermann, H. J., Theory and Applications of Fuzzy Sets, Institut...Boston, Inc., Hingham, MA, 1978. [18] Yager, R. R., "Multiple Objective Decision-Making Using Fuzzy Sets," International Journal of Man- Machine Studies ...Professor of Industria Engineering ... iv t TABLE OF CONTENTS page ABSTRACT .. .. . ...... . .... ...... ........ iii LIST OF TABLES

Generating a 2D Representation of a Complex Data Structure

NASA Technical Reports Server (NTRS)

James, Mark

2006-01-01

A computer program, designed to assist in the development and debugging of other software, generates a two-dimensional (2D) representation of a possibly complex n-dimensional (where n is an integer >2) data structure or abstract rank-n object in that other software. The nature of the 2D representation is such that it can be displayed on a non-graphical output device and distributed by non-graphical means.

Graph Structured Program Evolution: Evolution of Loop Structures

NASA Astrophysics Data System (ADS)

Shirakawa, Shinichi; Nagao, Tomoharu

Recently, numerous automatic programming techniques have been developed and applied in various fields. A typical example is genetic programming (GP), and various extensions and representations of GP have been proposed thus far. Complex programs and hand-written programs, however, may contain several loops and handle multiple data types. In this chapter, we propose a new method called Graph Structured Program Evolution (GRAPE). The representation of GRAPE is a graph structure; therefore, it can represent branches and loops using this structure. Each programis constructed as an arbitrary directed graph of nodes and a data set. The GRAPE program handles multiple data types using the data set for each type, and the genotype of GRAPE takes the form of a linear string of integers. We apply GRAPE to three test problems, factorial, exponentiation, and list sorting, and demonstrate that the optimum solution in each problem is obtained by the GRAPE system.

Non-integer expansion embedding techniques for reversible image watermarking

NASA Astrophysics Data System (ADS)

Xiang, Shijun; Wang, Yi

2015-12-01

This work aims at reducing the embedding distortion of prediction-error expansion (PE)-based reversible watermarking. In the classical PE embedding method proposed by Thodi and Rodriguez, the predicted value is rounded to integer number for integer prediction-error expansion (IPE) embedding. The rounding operation makes a constraint on a predictor's performance. In this paper, we propose a non-integer PE (NIPE) embedding approach, which can proceed non-integer prediction errors for embedding data into an audio or image file by only expanding integer element of a prediction error while keeping its fractional element unchanged. The advantage of the NIPE embedding technique is that the NIPE technique can really bring a predictor into full play by estimating a sample/pixel in a noncausal way in a single pass since there is no rounding operation. A new noncausal image prediction method to estimate a pixel with four immediate pixels in a single pass is included in the proposed scheme. The proposed noncausal image predictor can provide better performance than Sachnev et al.'s noncausal double-set prediction method (where data prediction in two passes brings a distortion problem due to the fact that half of the pixels were predicted with the watermarked pixels). In comparison with existing several state-of-the-art works, experimental results have shown that the NIPE technique with the new noncausal prediction strategy can reduce the embedding distortion for the same embedding payload.

Generalized conformal realizations of Kac-Moody algebras

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmkvist, Jakob

2009-01-15

We present a construction which associates an infinite sequence of Kac-Moody algebras, labeled by a positive integer n, to one single Jordan algebra. For n=1, this reduces to the well known Kantor-Koecher-Tits construction. Our generalization utilizes a new relation between different generalized Jordan triple systems, together with their known connections to Jordan and Lie algebras. Applied to the Jordan algebra of Hermitian 3x3 matrices over the division algebras R, C, H, O, the construction gives the exceptional Lie algebras f{sub 4}, e{sub 6}, e{sub 7}, e{sub 8} for n=2. Moreover, we obtain their infinite-dimensional extensions for n{>=}3. In the casemore » of 2x2 matrices, the resulting Lie algebras are of the form so(p+n,q+n) and the concomitant nonlinear realization generalizes the conformal transformations in a spacetime of signature (p,q)« less

Symmetry and charge order in Fe2OBO3 studied through polarized resonant x-ray diffraction

NASA Astrophysics Data System (ADS)

Bland, S. R.; Angst, M.; Adiga, S.; Scagnoli, V.; Johnson, R. D.; Herrero-Martín, J.; Hatton, P. D.

2010-09-01

Bond valence sum calculations have previously suggested that iron oxyborate exhibits charge order of the Fe ions with integer 2+/3+ valence states. Meanwhile transition metal oxides typically show much smaller, fractional charge disproportionations. Using resonant x-ray diffraction at the iron K edge, we find resonant features which are much larger than those ordinarily observed in charge ordered oxides. Simulations were subsequently performed using a cluster-based, monoelectronic code. The nanoscale domain structure prevents precise fitting; nevertheless the simulations confirm the diagonal charge order symmetry, as well as the unusually large charge disproportionation. We have demonstrated the conversion of linearly to nonlinearly polarized light and vice versa through full polarization analysis. Simulations show that this effect principally results from interference between the isotropic and anisotropic scattering terms. This mechanism is likely to account for similar observations in alternative systems.

Epicyclic helical channels for parametric resonance ionization cooling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johson, Rolland Paul; Derbenev, Yaroslav

Proposed next-generation muon colliders will require major technical advances to achieve rapid muon beam cooling requirements. Parametric-resonance Ionization Cooling (PIC) is proposed as the final 6D cooling stage of a high-luminosity muon collider. In PIC, a half-integer parametric resonance causes strong focusing of a muon beam at appropriately placed energy absorbers while ionization cooling limits the beam’s angular spread. Combining muon ionization cooling with parametric resonant dynamics in this way should then allow much smaller final transverse muon beam sizes than conventional ionization cooling alone. One of the PIC challenges is compensation of beam aberrations over a sufficiently wide parametermore » range while maintaining the dynamical stability with correlated behavior of the horizontal and vertical betatron motion and dispersion. We explore use of a coupling resonance to reduce the dimensionality of the problem and to shift the dynamics away from non-linear resonances. PIC simulations are presented.« less

Designing optimal cell factories: integer programming couples elementary mode analysis with regulation

PubMed Central

2012-01-01

Background Elementary mode (EM) analysis is ideally suited for metabolic engineering as it allows for an unbiased decomposition of metabolic networks in biologically meaningful pathways. Recently, constrained minimal cut sets (cMCS) have been introduced to derive optimal design strategies for strain improvement by using the full potential of EM analysis. However, this approach does not allow for the inclusion of regulatory information. Results Here we present an alternative, novel and simple method for the prediction of cMCS, which allows to account for boolean transcriptional regulation. We use binary linear programming and show that the design of a regulated, optimal metabolic network of minimal functionality can be formulated as a standard optimization problem, where EM and regulation show up as constraints. We validated our tool by optimizing ethanol production in E. coli. Our study showed that up to 70% of the predicted cMCS contained non-enzymatic, non-annotated reactions, which are difficult to engineer. These cMCS are automatically excluded by our approach utilizing simple weight functions. Finally, due to efficient preprocessing, the binary program remains computationally feasible. Conclusions We used integer programming to predict efficient deletion strategies to metabolically engineer a production organism. Our formulation utilizes the full potential of cMCS but adds additional flexibility to the design process. In particular our method allows to integrate regulatory information into the metabolic design process and explicitly favors experimentally feasible deletions. Our method remains manageable even if millions or potentially billions of EM enter the analysis. We demonstrated that our approach is able to correctly predict the most efficient designs for ethanol production in E. coli. PMID:22898474

AN ADA LINEAR ALGEBRA PACKAGE MODELED AFTER HAL/S

NASA Technical Reports Server (NTRS)

Klumpp, A. R.

1994-01-01

This package extends the Ada programming language to include linear algebra capabilities similar to those of the HAL/S programming language. The package is designed for avionics applications such as Space Station flight software. In addition to the HAL/S built-in functions, the package incorporates the quaternion functions used in the Shuttle and Galileo projects, and routines from LINPAK that solve systems of equations involving general square matrices. Language conventions in this package follow those of HAL/S to the maximum extent practical and minimize the effort required for writing new avionics software and translating existent software into Ada. Valid numeric types in this package include scalar, vector, matrix, and quaternion declarations. (Quaternions are fourcomponent vectors used in representing motion between two coordinate frames). Single precision and double precision floating point arithmetic is available in addition to the standard double precision integer manipulation. Infix operators are used instead of function calls to define dot products, cross products, quaternion products, and mixed scalar-vector, scalar-matrix, and vector-matrix products. The package contains two generic programs: one for floating point, and one for integer. The actual component type is passed as a formal parameter to the generic linear algebra package. The procedures for solving systems of linear equations defined by general matrices include GEFA, GECO, GESL, and GIDI. The HAL/S functions include ABVAL, UNIT, TRACE, DET, INVERSE, TRANSPOSE, GET, PUT, FETCH, PLACE, and IDENTITY. This package is written in Ada (Version 1.2) for batch execution and is machine independent. The linear algebra software depends on nothing outside the Ada language except for a call to a square root function for floating point scalars (such as SQRT in the DEC VAX MATHLIB library). This program was developed in 1989, and is a copyrighted work with all copyright vested in NASA.