An Approach for Solving Linear Fractional Programming Problems
Andrew Oyakhobo Odior
2012-01-01
Linear fractional programming problems are useful tools in production planning, financial and corporate planning, health care and hospital planning and as such have attracted considerable research interest. The paper presents a new approach for solving a fractional linear programming problem in which the objective function is a linear fractional function, while the constraint functions are in the form of linear inequalities. The approach adopted is based mainly upon solving the problem algebr...
An approach for solving linear fractional programming problems ...
African Journals Online (AJOL)
The paper presents a new approach for solving a fractional linear programming problem in which the objective function is a linear fractional function, while the constraint functions are in the form of linear inequalities. The approach adopted is based mainly upon solving the problem algebraically using the concept of duality ...
A goal programming procedure for solving fuzzy multiobjective fractional linear programming problems
Directory of Open Access Journals (Sweden)
Tunjo Perić
2014-12-01
Full Text Available This paper presents a modification of Pal, Moitra and Maulik's goal programming procedure for fuzzy multiobjective linear fractional programming problem solving. The proposed modification of the method allows simpler solving of economic multiple objective fractional linear programming (MOFLP problems, enabling the obtained solutions to express the preferences of the decision maker defined by the objective function weights. The proposed method is tested on the production planning example.
Directory of Open Access Journals (Sweden)
Tunjo Perić
2017-01-01
Full Text Available This paper presents and analyzes the applicability of three linearization techniques used for solving multi-objective linear fractional programming problems using the goal programming method. The three linearization techniques are: (1 Taylor’s polynomial linearization approximation, (2 the method of variable change, and (3 a modification of the method of variable change proposed in [20]. All three linearization techniques are presented and analyzed in two variants: (a using the optimal value of the objective functions as the decision makers’ aspirations, and (b the decision makers’ aspirations are given by the decision makers. As the criteria for the analysis we use the efficiency of the obtained solutions and the difficulties the analyst comes upon in preparing the linearization models. To analyze the applicability of the linearization techniques incorporated in the linear goal programming method we use an example of a financial structure optimization problem.
Shen, Peiping; Zhang, Tongli; Wang, Chunfeng
2017-01-01
This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions. To solve this problem, the algorithm solves an equivalent optimization problem (Q) via an exploration of a suitably defined nonuniform grid. The main work of the algorithm involves checking the feasibility of linear programs associated with the interesting grid points. It is proved that the proposed algorithm is a fully polynomial time approximation scheme as the ratio terms are fixed in the objective function to problem (P), based on the computational complexity result. In contrast to existing results in literature, the algorithm does not require the assumptions on quasi-concavity or low-rank of the objective function to problem (P). Numerical results are given to illustrate the feasibility and effectiveness of the proposed algorithm.
SLFP: a stochastic linear fractional programming approach for sustainable waste management.
Zhu, H; Huang, G H
2011-12-01
A stochastic linear fractional programming (SLFP) approach is developed for supporting sustainable municipal solid waste management under uncertainty. The SLFP method can solve ratio optimization problems associated with random information, where chance-constrained programming is integrated into a linear fractional programming framework. It has advantages in: (1) comparing objectives of two aspects, (2) reflecting system efficiency, (3) dealing with uncertainty expressed as probability distributions, and (4) providing optimal-ratio solutions under different system-reliability conditions. The method is applied to a case study of waste flow allocation within a municipal solid waste (MSW) management system. The obtained solutions are useful for identifying sustainable MSW management schemes with maximized system efficiency under various constraint-violation risks. The results indicate that SLFP can support in-depth analysis of the interrelationships among system efficiency, system cost and system-failure risk. Copyright © 2011 Elsevier Ltd. All rights reserved.
An Improved Method for Solving Multiobjective Integer Linear Fractional Programming Problem
Directory of Open Access Journals (Sweden)
Meriem Ait Mehdi
2014-01-01
Full Text Available We describe an improvement of Chergui and Moulaï’s method (2008 that generates the whole efficient set of a multiobjective integer linear fractional program based on the branch and cut concept. The general step of this method consists in optimizing (maximizing without loss of generality one of the fractional objective functions over a subset of the original continuous feasible set; then if necessary, a branching process is carried out until obtaining an integer feasible solution. At this stage, an efficient cut is built from the criteria’s growth directions in order to discard a part of the feasible domain containing only nonefficient solutions. Our contribution concerns firstly the optimization process where a linear program that we define later will be solved at each step rather than a fractional linear program. Secondly, local ideal and nadir points will be used as bounds to prune some branches leading to nonefficient solutions. The computational experiments show that the new method outperforms the old one in all the treated instances.
Solow, Daniel
2014-01-01
This text covers the basic theory and computation for a first course in linear programming, including substantial material on mathematical proof techniques and sophisticated computation methods. Includes Appendix on using Excel. 1984 edition.
Karloff, Howard
1991-01-01
To this reviewer’s knowledge, this is the first book accessible to the upper division undergraduate or beginning graduate student that surveys linear programming from the Simplex Method…via the Ellipsoid algorithm to Karmarkar’s algorithm. Moreover, its point of view is algorithmic and thus it provides both a history and a case history of work in complexity theory. The presentation is admirable; Karloff's style is informal (even humorous at times) without sacrificing anything necessary for understanding. Diagrams (including horizontal brackets that group terms) aid in providing clarity. The end-of-chapter notes are helpful...Recommended highly for acquisition, since it is not only a textbook, but can also be used for independent reading and study. —Choice Reviews The reader will be well served by reading the monograph from cover to cover. The author succeeds in providing a concise, readable, understandable introduction to modern linear programming. —Mathematics of Computing This is a textbook intend...
Quadratic-linear pattern in cancer fractional radiotherapy. Equations for a computering program
International Nuclear Information System (INIS)
Burgos, D.; Bullejos, J.; Garcia Puche, J.L.; Pedraza, V.
1990-01-01
Knowledge of equivalence between different tratment schemes with the same iso-effect is the essential thing in clinical cancer radiotherapy. For this purpose it is very useful the group of ideas derived from quadratic-linear pattern (Q-L) proposed in order to analyze cell survival curve to radiation. Iso-effect definition caused by several irradiation rules is done by extrapolated tolerance dose (ETD). Because equations for ETD are complex, a computering program have been carried out. In this paper, iso-effect equations for well defined therapeutic situations and flow diagram proposed for resolution, have been studied. (Author)
Zhang, Chenglong; Guo, Ping
2017-10-01
The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.
Reduction of Linear Programming to Linear Approximation
Vaserstein, Leonid N.
2006-01-01
It is well known that every Chebyshev linear approximation problem can be reduced to a linear program. In this paper we show that conversely every linear program can be reduced to a Chebyshev linear approximation problem.
Tuey, R. C.
1972-01-01
Computer solutions of linear programming problems are outlined. Information covers vector spaces, convex sets, and matrix algebra elements for solving simultaneous linear equations. Dual problems, reduced cost analysis, ranges, and error analysis are illustrated.
Lawson, C. L.; Krogh, F. T.; Gold, S. S.; Kincaid, D. R.; Sullivan, J.; Williams, E.; Hanson, R. J.; Haskell, K.; Dongarra, J.; Moler, C. B.
1982-01-01
The Basic Linear Algebra Subprograms (BLAS) library is a collection of 38 FORTRAN-callable routines for performing basic operations of numerical linear algebra. BLAS library is portable and efficient source of basic operations for designers of programs involving linear algebriac computations. BLAS library is supplied in portable FORTRAN and Assembler code versions for IBM 370, UNIVAC 1100 and CDC 6000 series computers.
International Nuclear Information System (INIS)
Rogner, H.H.
1989-01-01
The submitted sections on linear programming are extracted from 'Theorie und Technik der Planung' (1978) by W. Blaas and P. Henseler and reformulated for presentation at the Workshop. They consider a brief introduction to the theory of linear programming and to some essential aspects of the SIMPLEX solution algorithm for the purposes of economic planning processes. 1 fig
Directory of Open Access Journals (Sweden)
Qiang Fu
2018-05-01
Full Text Available The potential influence of natural variations in a climate system on global warming can change the hydrological cycle and threaten current strategies of water management. A simulation-based linear fractional programming (SLFP model, which integrates a runoff simulation model (RSM into a linear fractional programming (LFP framework, is developed for optimal water resource planning. The SLFP model has multiple objectives such as benefit maximization and water supply minimization, balancing water conflicts among various water demand sectors, and addressing complexities of water resource allocation system. Lingo and Excel programming solutions were used to solve the model. Water resources in the main stream basin of the Songhua River are allocated for 4 water demand sectors in 8 regions during two planning periods under different scenarios. Results show that the increase or decrease of water supply to the domestic sector is related to the change in population density at different regions in different target years. In 2030, the water allocation in the industrial sector decreased by 1.03–3.52% compared with that in 2020, while the water allocation in the environmental sector increased by 0.12–1.29%. Agricultural water supply accounts for 54.79–77.68% of total water supply in different regions. These changes in water resource allocation for various sectors were affected by different scenarios in 2020; however, water resource allocation for each sector was relatively stable under different scenarios in 2030. These results suggest that the developed SLFP model can help to improve the adjustment of water use structure and water utilization efficiency.
Brameier, Markus
2007-01-01
Presents a variant of Genetic Programming that evolves imperative computer programs as linear sequences of instructions, in contrast to the more traditional functional expressions or syntax trees. This book serves as a reference for researchers, but also contains sufficient introduction for students and those who are new to the field
Linear programming using Matlab
Ploskas, Nikolaos
2017-01-01
This book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms. As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus. The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting ru...
Klumpp, A. R.; Lawson, C. L.
1988-01-01
Routines provided for common scalar, vector, matrix, and quaternion operations. Computer program extends Ada programming language to include linear-algebra capabilities similar to HAS/S programming language. Designed for such avionics applications as software for Space Station.
Linear Programming and Network Flows
Bazaraa, Mokhtar S; Sherali, Hanif D
2011-01-01
The authoritative guide to modeling and solving complex problems with linear programming-extensively revised, expanded, and updated The only book to treat both linear programming techniques and network flows under one cover, Linear Programming and Network Flows, Fourth Edition has been completely updated with the latest developments on the topic. This new edition continues to successfully emphasize modeling concepts, the design and analysis of algorithms, and implementation strategies for problems in a variety of fields, including industrial engineering, management science, operations research
Semi-infinite fractional programming
Verma, Ram U
2017-01-01
This book presents a smooth and unified transitional framework from generalised fractional programming, with a finite number of variables and a finite number of constraints, to semi-infinite fractional programming, where a number of variables are finite but with infinite constraints. It focuses on empowering graduate students, faculty and other research enthusiasts to pursue more accelerated research advances with significant interdisciplinary applications without borders. In terms of developing general frameworks for theoretical foundations and real-world applications, it discusses a number of new classes of generalised second-order invex functions and second-order univex functions, new sets of second-order necessary optimality conditions, second-order sufficient optimality conditions, and second-order duality models for establishing numerous duality theorems for discrete minmax (or maxmin) semi-infinite fractional programming problems. In the current interdisciplinary supercomputer-oriented research envi...
Linear Matrix Inequality Based Fuzzy Synchronization for Fractional Order Chaos
Directory of Open Access Journals (Sweden)
Bin Wang
2015-01-01
Full Text Available This paper investigates fuzzy synchronization for fractional order chaos via linear matrix inequality. Based on generalized Takagi-Sugeno fuzzy model, one efficient stability condition for fractional order chaos synchronization or antisynchronization is given. The fractional order stability condition is transformed into a set of linear matrix inequalities and the rigorous proof details are presented. Furthermore, through fractional order linear time-invariant (LTI interval theory, the approach is developed for fractional order chaos synchronization regardless of the system with uncertain parameters. Three typical examples, including synchronization between an integer order three-dimensional (3D chaos and a fractional order 3D chaos, anti-synchronization of two fractional order hyperchaos, and the synchronization between an integer order 3D chaos and a fractional order 4D chaos, are employed to verify the theoretical results.
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.
Elementary linear programming with applications
Kolman, Bernard
1995-01-01
Linear programming finds the least expensive way to meet given needs with available resources. Its results are used in every area of engineering and commerce: agriculture, oil refining, banking, and air transport. Authors Kolman and Beck present the basic notions of linear programming and illustrate how they are used to solve important common problems. The software on the included disk leads students step-by-step through the calculations. The Second Edition is completely revised and provides additional review material on linear algebra as well as complete coverage of elementary linear program
Linear Programming across the Curriculum
Yoder, S. Elizabeth; Kurz, M. Elizabeth
2015-01-01
Linear programming (LP) is taught in different departments across college campuses with engineering and management curricula. Modeling an LP problem is taught in every linear programming class. As faculty teaching in Engineering and Management departments, the depth to which teachers should expect students to master this particular type of…
Directory of Open Access Journals (Sweden)
Ai-Min Yang
2014-01-01
Full Text Available The local fractional Laplace variational iteration method was applied to solve the linear local fractional partial differential equations. The local fractional Laplace variational iteration method is coupled by the local fractional variational iteration method and Laplace transform. The nondifferentiable approximate solutions are obtained and their graphs are also shown.
Linear programming foundations and extensions
Vanderbei, Robert J
2001-01-01
Linear Programming: Foundations and Extensions is an introduction to the field of optimization. The book emphasizes constrained optimization, beginning with a substantial treatment of linear programming, and proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. The book is carefully written. Specific examples and concrete algorithms precede more abstract topics. Topics are clearly developed with a large number of numerical examples worked out in detail. Moreover, Linear Programming: Foundations and Extensions underscores the purpose of optimization: to solve practical problems on a computer. Accordingly, the book is coordinated with free efficient C programs that implement the major algorithms studied: -The two-phase simplex method; -The primal-dual simplex method; -The path-following interior-point method; -The homogeneous self-dual methods. In addition, there are online JAVA applets that illustrate various pivot rules and variants of the simplex m...
On the discretization of linear fractional representations of LPV systems
Toth, R.; Lovera, M.; Heuberger, P.S.C.; Corno, M.; Hof, Van den P.M.J.
2012-01-01
Commonly, controllers for linear parameter-varying (LPV) systems are designed in continuous time using a linear fractional representation (LFR) of the plant. However, the resulting controllers are implemented on digital hardware. Furthermore, discrete-time LPV synthesis approaches require a
Fractional order differentiation by integration: An application to fractional linear systems
Liu, Dayan
2013-02-04
In this article, we propose a robust method to compute the output of a fractional linear system defined through a linear fractional differential equation (FDE) with time-varying coefficients, where the input can be noisy. We firstly introduce an estimator of the fractional derivative of an unknown signal, which is defined by an integral formula obtained by calculating the fractional derivative of a truncated Jacobi polynomial series expansion. We then approximate the FDE by applying to each fractional derivative this formal algebraic integral estimator. Consequently, the fractional derivatives of the solution are applied on the used Jacobi polynomials and then we need to identify the unknown coefficients of the truncated series expansion of the solution. Modulating functions method is used to estimate these coefficients by solving a linear system issued from the approximated FDE and some initial conditions. A numerical result is given to confirm the reliability of the proposed method. © 2013 IFAC.
175 Years of Linear Programming
Indian Academy of Sciences (India)
polynomial-time solvability of linear programming, that is, testing if a polyhedron Q E ~ ... Q is rational, i.e. all extreme points and rays of Q are ra- tional vectors or ..... rithrll terminates with an interior solution, a post-processing step is usually ...
175 Years of Linear Programming
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 10. 175 Years of Linear Programming - Max Flow = Min Cut. Vijay Chandru M R Rao. Series Article Volume 4 Issue 10 October 1999 pp 22-39. Fulltext. Click here to view fulltext PDF. Permanent link:
175 Years of Linear Programming
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 5. 175 Years of Linear Programming - Pune's Gift. Vijay Chandru M R Rao. Series Article Volume 4 Issue 5 May ... Computer Science and Automation, IISc Bangalore 560012, India. Director, Indian Institute of Management, Bannerghatta Road, ...
Linear fractional diffusion-wave equation for scientists and engineers
Povstenko, Yuriy
2015-01-01
This book systematically presents solutions to the linear time-fractional diffusion-wave equation. It introduces the integral transform technique and discusses the properties of the Mittag-Leffler, Wright, and Mainardi functions that appear in the solutions. The time-nonlocal dependence between the flux and the gradient of the transported quantity with the “long-tail” power kernel results in the time-fractional diffusion-wave equation with the Caputo fractional derivative. Time-nonlocal generalizations of classical Fourier’s, Fick’s and Darcy’s laws are considered and different kinds of boundary conditions for this equation are discussed (Dirichlet, Neumann, Robin, perfect contact). The book provides solutions to the fractional diffusion-wave equation with one, two and three space variables in Cartesian, cylindrical and spherical coordinates. The respective sections of the book can be used for university courses on fractional calculus, heat and mass transfer, transport processes in porous media and ...
ALPS - A LINEAR PROGRAM SOLVER
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.
A Solution to the Fundamental Linear Fractional Order Differential Equation
Hartley, Tom T.; Lorenzo, Carl F.
1998-01-01
This paper provides a solution to the fundamental linear fractional order differential equation, namely, (sub c)d(sup q, sub t) + ax(t) = bu(t). The impulse response solution is shown to be a series, named the F-function, which generalizes the normal exponential function. The F-function provides the basis for a qth order "fractional pole". Complex plane behavior is elucidated and a simple example, the inductor terminated semi- infinite lossy line, is used to demonstrate the theory.
On the linear programming bound for linear Lee codes.
Astola, Helena; Tabus, Ioan
2016-01-01
Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.
Ranking Forestry Investments With Parametric Linear Programming
Paul A. Murphy
1976-01-01
Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.
Influence of the void fraction in the linear reactivity model
International Nuclear Information System (INIS)
Castillo, J.A.; Ramirez, J.R.; Alonso, G.
2003-01-01
The linear reactivity model allows the multicycle analysis in pressurized water reactors in a simple and quick way. In the case of the Boiling water reactors the void fraction it varies axially from 0% of voids in the inferior part of the fuel assemblies until approximately 70% of voids to the exit of the same ones. Due to this it is very important the determination of the average void fraction during different stages of the reactor operation to predict the burnt one appropriately of the same ones to inclination of the pattern of linear reactivity. In this work a pursuit is made of the profile of power for different steps of burnt of a typical operation cycle of a Boiling water reactor. Starting from these profiles it builds an algorithm that allows to determine the voids profile and this way to obtain the average value of the same one. The results are compared against those reported by the CM-PRESTO code that uses another method to carry out this calculation. Finally, the range in which is the average value of the void fraction during a typical cycle is determined and an estimate of the impact that it would have the use of this value in the prediction of the reactivity produced by the fuel assemblies is made. (Author)
Computer Program For Linear Algebra
Krogh, F. T.; Hanson, R. J.
1987-01-01
Collection of routines provided for basic vector operations. Basic Linear Algebra Subprogram (BLAS) library is collection from FORTRAN-callable routines for employing standard techniques to perform basic operations of numerical linear algebra.
The linear programming bound for binary linear codes
Brouwer, A.E.
1993-01-01
Combining Delsarte's (1973) linear programming bound with the information that certain weights cannot occur, new upper bounds for dmin (n,k), the maximum possible minimum distance of a binary linear code with given word length n and dimension k, are derived.
Linear programming algorithms and applications
Vajda, S
1981-01-01
This text is based on a course of about 16 hours lectures to students of mathematics, statistics, and/or operational research. It is intended to introduce readers to the very wide range of applicability of linear programming, covering problems of manage ment, administration, transportation and a number of other uses which are mentioned in their context. The emphasis is on numerical algorithms, which are illustrated by examples of such modest size that the solutions can be obtained using pen and paper. It is clear that these methods, if applied to larger problems, can also be carried out on automatic (electronic) computers. Commercially available computer packages are, in fact, mainly based on algorithms explained in this book. The author is convinced that the user of these algorithms ought to be knowledgeable about the underlying theory. Therefore this volume is not merely addressed to the practitioner, but also to the mathematician who is interested in relatively new developments in algebraic theory and in...
Investigating Integer Restrictions in Linear Programming
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…
Results of fractionated stereotactic radiotherapy with linear accelerator
Energy Technology Data Exchange (ETDEWEB)
Aoki, Masahiko; Watanabe, Sadao [Aomori Prefectural Central Hospital (Japan); Mariya, Yasushi [and others
1997-03-01
A lot of clinical data about stereotactic radiotherapy (SRT) were reported, however, standard fractionated schedules were not shown. In this paper, our clinical results of SRT, 3 fractions of 10 Gy, are reported. Between February 1992 and March 1995, we treated 41 patients with 7 arteriovenous malformations and 41 intracranial tumors using a stereotactic technique implemented by a standard 10MV X-ray linear accelerator. Average age was 47.4 years (range 3-80 years) and average follow-up time was 16.7 months (range 3.5-46.1 months). The patients received 3 fractions of 10 Gy for 3 days delivered by multiple arc narrow beams under 3 cm in width and length. A three-pieces handmade shell was used for head fixation without any anesthetic procedures. Three-dimensional treatment planning system (Focus) was applied for the dose calculation. All patients have received at least one follow-up radiographic study and one clinical examination. In four of the 7 patients with AVM the nidus has become smaller, 9 of the 21 patients with benign intracranial tumors and 9 of the 13 patients with intracranial malignant tumors have shown complete or partial response to the therapy. In 14 patients, diseases were stable or unevaluable due to the short follow-up time. In 5 patients (3 with astrocytoma, 1 each with meningioma and craniopharyngioma), diseases were progressive. Only 1 patient with falx meningioma had minor complication due to the symptomatic brain edema around the tumor. Although, further evaluation of target control (i.e. tumor and nidus) and late normal tissue damage is needed, preliminary clinical results indicate that SRT with our methods is safe and effective. (author)
Joint shape segmentation with linear programming
Huang, Qixing; Koltun, Vladlen; Guibas, Leonidas
2011-01-01
program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape
Timetabling an Academic Department with Linear Programming.
Bezeau, Lawrence M.
This paper describes an approach to faculty timetabling and course scheduling that uses computerized linear programming. After reviewing the literature on linear programming, the paper discusses the process whereby a timetable was created for a department at the University of New Brunswick. Faculty were surveyed with respect to course offerings…
A new algorithm for generalized fractional programs
J.B.G. Frenk (Hans); A.I. Barros (Ana); S. Schaible; S. Zhang (Shuzhong)
1996-01-01
textabstractA new dual problem for convex generalized fractional programs with no duality gap is presented and it is shown how this dual problem can be efficiently solved using a parametric approach. The resulting algorithm can be seen as “dual” to the Dinkelbach-type algorithm for generalized
M. ZANGIABADI; H. R. MALEKI
2007-01-01
In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters based on those for multiobjective linear programming problems. Then by using the concept of comparison of fuzzy numbers, we transform a linear programming problem with fuzzy parameters to a multiobjective linear programming problem. To this end, w...
Enhancement of Linear Circuit Program
DEFF Research Database (Denmark)
Gaunholt, Hans; Dabu, Mihaela; Beldiman, Octavian
1996-01-01
In this report a preliminary user friendly interface has been added to the LCP2 program making it possible to describe an electronic circuit by actually drawing the circuit on the screen. Component values and other options and parameters can easily be set by the aid of the interface. The interface...
Linear and integer programming made easy
Hu, T C
2016-01-01
Linear and integer programming are fundamental toolkits for data and information science and technology, particularly in the context of today’s megatrends toward statistical optimization, machine learning, and big data analytics. Drawn from over 30 years of classroom teaching and applied research experience, this textbook provides a crisp and practical introduction to the basics of linear and integer programming. The authors’ approach is accessible to students from all fields of engineering, including operations research, statistics, machine learning, control system design, scheduling, formal verification, and computer vision. Readers will learn to cast hard combinatorial problems as mathematical programming optimizations, understand how to achieve formulations where the objective and constraints are linear, choose appropriate solution methods, and interpret results appropriately. •Provides a concise introduction to linear and integer programming, appropriate for undergraduates, graduates, a short cours...
The Use of Linear Programming for Prediction.
Schnittjer, Carl J.
The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)
Sparsity Prevention Pivoting Method for Linear Programming
DEFF Research Database (Denmark)
Li, Peiqiang; Li, Qiyuan; Li, Canbing
2018-01-01
When the simplex algorithm is used to calculate a linear programming problem, if the matrix is a sparse matrix, it will be possible to lead to many zero-length calculation steps, and even iterative cycle will appear. To deal with the problem, a new pivoting method is proposed in this paper....... The principle of this method is avoided choosing the row which the value of the element in the b vector is zero as the row of the pivot element to make the matrix in linear programming density and ensure that most subsequent steps will improve the value of the objective function. One step following...... this principle is inserted to reselect the pivot element in the existing linear programming algorithm. Both the conditions for inserting this step and the maximum number of allowed insertion steps are determined. In the case study, taking several numbers of linear programming problems as examples, the results...
Sparsity Prevention Pivoting Method for Linear Programming
DEFF Research Database (Denmark)
Li, Peiqiang; Li, Qiyuan; Li, Canbing
2018-01-01
. The principle of this method is avoided choosing the row which the value of the element in the b vector is zero as the row of the pivot element to make the matrix in linear programming density and ensure that most subsequent steps will improve the value of the objective function. One step following......When the simplex algorithm is used to calculate a linear programming problem, if the matrix is a sparse matrix, it will be possible to lead to many zero-length calculation steps, and even iterative cycle will appear. To deal with the problem, a new pivoting method is proposed in this paper...... this principle is inserted to reselect the pivot element in the existing linear programming algorithm. Both the conditions for inserting this step and the maximum number of allowed insertion steps are determined. In the case study, taking several numbers of linear programming problems as examples, the results...
A Direct Heuristic Algorithm for Linear Programming
Indian Academy of Sciences (India)
Abstract. An (3) mathematically non-iterative heuristic procedure that needs no artificial variable is presented for solving linear programming problems. An optimality test is included. Numerical experiments depict the utility/scope of such a procedure.
Evaluation of film dosemeters by linear programming
International Nuclear Information System (INIS)
Kragh, P.; Nitschke, J.
1992-01-01
An evaluation method for multi-component dosemeters is described which uses linear programming in order to decrease the dependence on energy and direction. The results of this method are more accurate than those obtained with the evaluation methods so far applied in film dosimetry. In addition, systematic errors can be given when evaluating individual measurements. Combined linear programming, as a special case of the presented method, is described taking a film dosemeter of particular type as an example. (orig.) [de
The intelligence of dual simplex method to solve linear fractional fuzzy transportation problem.
Narayanamoorthy, S; Kalyani, S
2015-01-01
An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example.
The Intelligence of Dual Simplex Method to Solve Linear Fractional Fuzzy Transportation Problem
Directory of Open Access Journals (Sweden)
S. Narayanamoorthy
2015-01-01
Full Text Available An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example.
Linear programming mathematics, theory and algorithms
1996-01-01
Linear Programming provides an in-depth look at simplex based as well as the more recent interior point techniques for solving linear programming problems. Starting with a review of the mathematical underpinnings of these approaches, the text provides details of the primal and dual simplex methods with the primal-dual, composite, and steepest edge simplex algorithms. This then is followed by a discussion of interior point techniques, including projective and affine potential reduction, primal and dual affine scaling, and path following algorithms. Also covered is the theory and solution of the linear complementarity problem using both the complementary pivot algorithm and interior point routines. A feature of the book is its early and extensive development and use of duality theory. Audience: The book is written for students in the areas of mathematics, economics, engineering and management science, and professionals who need a sound foundation in the important and dynamic discipline of linear programming.
Fuzzy Multi-objective Linear Programming Approach
Directory of Open Access Journals (Sweden)
Amna Rehmat
2007-07-01
Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.
Portfolio optimization using fuzzy linear programming
Pandit, Purnima K.
2013-09-01
Portfolio Optimization (PO) is a problem in Finance, in which investor tries to maximize return and minimize risk by carefully choosing different assets. Expected return and risk are the most important parameters with regard to optimal portfolios. In the simple form PO can be modeled as quadratic programming problem which can be put into equivalent linear form. PO problems with the fuzzy parameters can be solved as multi-objective fuzzy linear programming problem. In this paper we give the solution to such problems with an illustrative example.
Some Properties of Multiple Parameters Linear Programming
Directory of Open Access Journals (Sweden)
Maoqin Li
2010-01-01
Full Text Available We consider a linear programming problem in which the right-hand side vector depends on multiple parameters. We study the characters of the optimal value function and the critical regions based on the concept of the optimal partition. We show that the domain of the optimal value function f can be decomposed into finitely many subsets with disjoint relative interiors, which is different from the result based on the concept of the optimal basis. And any directional derivative of f at any point can be computed by solving a linear programming problem when only an optimal solution is available at the point.
Some Properties of Multiple Parameters Linear Programming
Directory of Open Access Journals (Sweden)
Yan Hong
2010-01-01
Full Text Available Abstract We consider a linear programming problem in which the right-hand side vector depends on multiple parameters. We study the characters of the optimal value function and the critical regions based on the concept of the optimal partition. We show that the domain of the optimal value function can be decomposed into finitely many subsets with disjoint relative interiors, which is different from the result based on the concept of the optimal basis. And any directional derivative of at any point can be computed by solving a linear programming problem when only an optimal solution is available at the point.
PCX, Interior-Point Linear Programming Solver
International Nuclear Information System (INIS)
Czyzyk, J.
2004-01-01
1 - Description of program or function: PCX solves linear programming problems using the Mehrota predictor-corrector interior-point algorithm. PCX can be called as a subroutine or used in stand-alone mode, with data supplied from an MPS file. The software incorporates modules that can be used separately from the linear programming solver, including a pre-solve routine and data structure definitions. 2 - Methods: The Mehrota predictor-corrector method is a primal-dual interior-point method for linear programming. The starting point is determined from a modified least squares heuristic. Linear systems of equations are solved at each interior-point iteration via a sparse Cholesky algorithm native to the code. A pre-solver is incorporated in the code to eliminate inefficiencies in the user's formulation of the problem. 3 - Restriction on the complexity of the problem: There are no size limitations built into the program. The size of problem solved is limited by RAM and swap space on the user's computer
Belkhatir, Zehor
2015-11-05
This paper deals with the joint estimation of the unknown input and the fractional differentiation orders of a linear fractional order system. A two-stage algorithm combining the modulating functions with a first-order Newton method is applied to solve this estimation problem. First, the modulating functions approach is used to estimate the unknown input for a given fractional differentiation orders. Then, the method is combined with a first-order Newton technique to identify the fractional orders jointly with the input. To show the efficiency of the proposed method, numerical examples illustrating the estimation of the neural activity, considered as input of a fractional model of the neurovascular coupling, along with the fractional differentiation orders are presented in both noise-free and noisy cases.
Analysis of fractional non-linear diffusion behaviors based on Adomian polynomials
Directory of Open Access Journals (Sweden)
Wu Guo-Cheng
2017-01-01
Full Text Available A time-fractional non-linear diffusion equation of two orders is considered to investigate strong non-linearity through porous media. An equivalent integral equation is established and Adomian polynomials are adopted to linearize non-linear terms. With the Taylor expansion of fractional order, recurrence formulae are proposed and novel numerical solutions are obtained to depict the diffusion behaviors more accurately. The result shows that the method is suitable for numerical simulation of the fractional diffusion equations of multi-orders.
Stability Tests of Positive Fractional Continuous-time Linear Systems with Delays
Directory of Open Access Journals (Sweden)
Tadeusz Kaczorek
2013-06-01
Full Text Available Necessary and sufficient conditions for the asymptotic stability of positive fractional continuous-time linear systems with many delays are established. It is shown that: 1 the asymptotic stability of the positive fractional system is independent of their delays, 2 the checking of the asymptotic stability of the positive fractional systems with delays can be reduced to checking of the asymptotic stability of positive standard linear systems without delays.
Spline smoothing of histograms by linear programming
Bennett, J. O.
1972-01-01
An algorithm for an approximating function to the frequency distribution is obtained from a sample of size n. To obtain the approximating function a histogram is made from the data. Next, Euclidean space approximations to the graph of the histogram using central B-splines as basis elements are obtained by linear programming. The approximating function has area one and is nonnegative.
Generalised Assignment Matrix Methodology in Linear Programming
Jerome, Lawrence
2012-01-01
Discrete Mathematics instructors and students have long been struggling with various labelling and scanning algorithms for solving many important problems. This paper shows how to solve a wide variety of Discrete Mathematics and OR problems using assignment matrices and linear programming, specifically using Excel Solvers although the same…
Fuzzy linear programming approach for solving transportation
Indian Academy of Sciences (India)
Transportation problem (TP) is an important network structured linear programming problem that arises in several contexts and has deservedly received a great deal of attention in the literature. The central concept in this problem is to find the least total transportation cost of a commodity in order to satisfy demands at ...
Menu-Driven Solver Of Linear-Programming Problems
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 simplex method of linear programming
Ficken, Frederick A
1961-01-01
This concise but detailed and thorough treatment discusses the rudiments of the well-known simplex method for solving optimization problems in linear programming. Geared toward undergraduate students, the approach offers sufficient material for readers without a strong background in linear algebra. Many different kinds of problems further enrich the presentation. The text begins with examinations of the allocation problem, matrix notation for dual problems, feasibility, and theorems on duality and existence. Subsequent chapters address convex sets and boundedness, the prepared problem and boun
Updating Linear Schedules with Lowest Cost: a Linear Programming Model
Biruk, Sławomir; Jaśkowski, Piotr; Czarnigowska, Agata
2017-10-01
Many civil engineering projects involve sets of tasks repeated in a predefined sequence in a number of work areas along a particular route. A useful graphical representation of schedules of such projects is time-distance diagrams that clearly show what process is conducted at a particular point of time and in particular location. With repetitive tasks, the quality of project performance is conditioned by the ability of the planner to optimize workflow by synchronizing the works and resources, which usually means that resources are planned to be continuously utilized. However, construction processes are prone to risks, and a fully synchronized schedule may expire if a disturbance (bad weather, machine failure etc.) affects even one task. In such cases, works need to be rescheduled, and another optimal schedule should be built for the changed circumstances. This typically means that, to meet the fixed completion date, durations of operations have to be reduced. A number of measures are possible to achieve such reduction: working overtime, employing more resources or relocating resources from less to more critical tasks, but they all come at a considerable cost and affect the whole project. The paper investigates the problem of selecting the measures that reduce durations of tasks of a linear project so that the cost of these measures is kept to the minimum and proposes an algorithm that could be applied to find optimal solutions as the need to reschedule arises. Considering that civil engineering projects, such as road building, usually involve less process types than construction projects, the complexity of scheduling problems is lower, and precise optimization algorithms can be applied. Therefore, the authors put forward a linear programming model of the problem and illustrate its principle of operation with an example.
2010-01-01
... program use by fractional ownership program manager. 91.1411 Section 91.1411 Aeronautics and Space FEDERAL... airworthiness maintenance program use by fractional ownership program manager. Fractional ownership program... through 91.1443. Any program manager who elects to maintain the program aircraft using a continuous...
Fractional hereditariness of lipid membranes: Instabilities and linearized evolution.
Deseri, L; Pollaci, P; Zingales, M; Dayal, K
2016-05-01
In this work lipid ordering phase changes arising in planar membrane bilayers is investigated both accounting for elasticity alone and for effective viscoelastic response of such assemblies. The mechanical response of such membranes is studied by minimizing the Gibbs free energy which penalizes perturbations of the changes of areal stretch and their gradients only (Deseri and Zurlo, 2013). As material instabilities arise whenever areal stretches characterizing homogeneous configurations lie inside the spinoidal zone of the free energy density, bifurcations from such configurations are shown to occur as oscillatory perturbations of the in-plane displacement. Experimental observations (Espinosa et al., 2011) show a power-law in-plane viscous behavior of lipid structures allowing for an effective viscoelastic behavior of lipid membranes, which falls in the framework of Fractional Hereditariness. A suitable generalization of the variational principle invoked for the elasticity is applied in this case, and the corresponding Euler-Lagrange equation is found together with a set of boundary and initial conditions. Separation of variables allows for showing how Fractional Hereditariness owes bifurcated modes with a larger number of spatial oscillations than the corresponding elastic analog. Indeed, the available range of areal stresses for material instabilities is found to increase with respect to the purely elastic case. Nevertheless, the time evolution of the perturbations solving the Euler-Lagrange equation above exhibits time-decay and the large number of spatial oscillation slowly relaxes, thereby keeping the features of a long-tail type time-response. Copyright © 2015 Elsevier Ltd. All rights reserved.
Joint shape segmentation with linear programming
Huang, Qixing
2011-01-01
We present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. © 2011 ACM.
Estimation of Multiple Point Sources for Linear Fractional Order Systems Using Modulating Functions
Belkhatir, Zehor; Laleg-Kirati, Taous-Meriem
2017-01-01
This paper proposes an estimation algorithm for the characterization of multiple point inputs for linear fractional order systems. First, using polynomial modulating functions method and a suitable change of variables the problem of estimating
Belkhatir, Zehor; Laleg-Kirati, Taous-Meriem
2017-01-01
This paper proposes a two-stage estimation algorithm to solve the problem of joint estimation of the parameters and the fractional differentiation orders of a linear continuous-time fractional system with non-commensurate orders. The proposed algorithm combines the modulating functions and the first-order Newton methods. Sufficient conditions ensuring the convergence of the method are provided. An error analysis in the discrete case is performed. Moreover, the method is extended to the joint estimation of smooth unknown input and fractional differentiation orders. The performance of the proposed approach is illustrated with different numerical examples. Furthermore, a potential application of the algorithm is proposed which consists in the estimation of the differentiation orders of a fractional neurovascular model along with the neural activity considered as input for this model.
Belkhatir, Zehor
2017-05-31
This paper proposes a two-stage estimation algorithm to solve the problem of joint estimation of the parameters and the fractional differentiation orders of a linear continuous-time fractional system with non-commensurate orders. The proposed algorithm combines the modulating functions and the first-order Newton methods. Sufficient conditions ensuring the convergence of the method are provided. An error analysis in the discrete case is performed. Moreover, the method is extended to the joint estimation of smooth unknown input and fractional differentiation orders. The performance of the proposed approach is illustrated with different numerical examples. Furthermore, a potential application of the algorithm is proposed which consists in the estimation of the differentiation orders of a fractional neurovascular model along with the neural activity considered as input for this model.
DEFF Research Database (Denmark)
Christensen, Bent Jesper; Kruse, Robinson; Sibbertsen, Philipp
We consider hypothesis testing in a general linear time series regression framework when the possibly fractional order of integration of the error term is unknown. We show that the approach suggested by Vogelsang (1998a) for the case of integer integration does not apply to the case of fractional...
Asymptotic behavior of solutions of linear multi-order fractional differential equation systems
Diethelm, Kai; Siegmund, Stefan; Tuan, H. T.
2017-01-01
In this paper, we investigate some aspects of the qualitative theory for multi-order fractional differential equation systems. First, we obtain a fundamental result on the existence and uniqueness for multi-order fractional differential equation systems. Next, a representation of solutions of homogeneous linear multi-order fractional differential equation systems in series form is provided. Finally, we give characteristics regarding the asymptotic behavior of solutions to some classes of line...
International program on linear electric motors
Energy Technology Data Exchange (ETDEWEB)
Dawson, G.E.; Eastham, A.R.; Parker, J.H.
1992-05-01
The International Program on Linear Electric Motors (LEM) was initiated for the purposes of commumication and coordination between various centers of expertise in LEM technology in Germany, Japan and Canada. Furthermore, it was intended to provide assessment and support of the planning of technological developments and for dissemination of information to researchers, service operators and policy makers, and to ensure that full advantage can be taken if opportunities for technology transfer occur. In the process, the program was able to provide closer contacts between researchers, to enhance and encourage collaborative research and development, and to facilitate joint ventures in advanced transportation technologies. Work done under the program is documented, and seminar materials presented by Canadian researchers in Italy, and by Italian researchers at Queen's University in Canada are presented. Five separate abstracts have been prepared for the main body of the report and the seminar materials.
Controller design approach based on linear programming.
Tanaka, Ryo; Shibasaki, Hiroki; Ogawa, Hiromitsu; Murakami, Takahiro; Ishida, Yoshihisa
2013-11-01
This study explains and demonstrates the design method for a control system with a load disturbance observer. Observer gains are determined by linear programming (LP) in terms of the Routh-Hurwitz stability criterion and the final-value theorem. In addition, the control model has a feedback structure, and feedback gains are determined to be the linear quadratic regulator. The simulation results confirmed that compared with the conventional method, the output estimated by our proposed method converges to a reference input faster when a load disturbance is added to a control system. In addition, we also confirmed the effectiveness of the proposed method by performing an experiment with a DC motor. © 2013 ISA. Published by ISA. All rights reserved.
Linear-quadratic model underestimates sparing effect of small doses per fraction in rat spinal cord
International Nuclear Information System (INIS)
Shun Wong, C.; Toronto University; Minkin, S.; Hill, R.P.; Toronto University
1993-01-01
The application of the linear-quadratic (LQ) model to describe iso-effective fractionation schedules for dose fraction sizes less than 2 Gy has been controversial. Experiments are described in which the effect of daily fractionated irradiation given with a wide range of fraction sizes was assessed in rat cervical spine cord. The first group of rats was given doses in 1, 2, 4, 8 and 40 fractions/day. The second group received 3 initial 'top-up'doses of 9 Gy given once daily, representing 3/4 tolerance, followed by doses in 1, 2, 10, 20, 30 and 40 fractions/day. The fractionated portion of the irradiation schedule therefore constituted only the final quarter of the tolerance dose. The endpoint of the experiments was paralysis of forelimbs secondary to white matter necrosis. Direct analysis of data from experiments with full course fractionation up to 40 fractions/day (25.0-1.98 Gy/fraction) indicated consistency with the LQ model yielding an α/β value of 2.41 Gy. Analysis of data from experiments in which the 3 'top-up' doses were followed by up to 10 fractions (10.0-1.64 Gy/fraction) gave an α/β value of 3.41 Gy. However, data from 'top-up' experiments with 20, 30 and 40 fractions (1.60-0.55 Gy/fraction) were inconsistent with LQ model and gave a very small α/β of 0.48 Gy. It is concluded that LQ model based on data from large doses/fraction underestimates the sparing effect of small doses/fraction, provided sufficient time is allowed between each fraction for repair of sublethal damage. (author). 28 refs., 5 figs., 1 tab
Optimization of refinery product blending by using linear programming
International Nuclear Information System (INIS)
Ristikj, Julija; Tripcheva-Trajkovska, Loreta; Rikaloski, Ice; Markovska, Liljana
1999-01-01
The product slate of a simple refinery consists mainly of liquefied petroleum gas, leaded and unleaded gasoline, jet fuel, diesel fuel, extra light heating oil and fuel oil. The quality of the oil products (fuels) for sale has to comply with the adopted standards for liquid fuels, and the produced quantities have to be comply with the market needs. The oil products are manufactured by blending two or more different fractions which quantities and physical-chemical properties depend on the crude oil type, the way and conditions of processing, and at the same time the fractions are used to blend one or more products. It is in producer's interest to do the blending in an optimal way, namely, to satisfy the requirements for the oil products quality and quantity with a maximal usage of the available fractions and, of course, with a maximal profit out of the sold products. This could be accomplished by applying linear programming, that is by using a linear model for oil products blending optimization. (Author)
A program package for solving linear optimization problems
International Nuclear Information System (INIS)
Horikami, Kunihiko; Fujimura, Toichiro; Nakahara, Yasuaki
1980-09-01
Seven computer programs for the solution of linear, integer and quadratic programming (four programs for linear programming, one for integer programming and two for quadratic programming) have been prepared and tested on FACOM M200 computer, and auxiliary programs have been written to make it easy to use the optimization program package. The characteristics of each program are explained and the detailed input/output descriptions are given in order to let users know how to use them. (author)
Underprediction of human skin erythema at low doses per fraction by the linear quadratic model
International Nuclear Information System (INIS)
Hamilton, Christopher S.; Denham, James W.; O'Brien, Maree; Ostwald, Patricia; Kron, Tomas; Wright, Suzanne; Doerr, Wolfgang
1996-01-01
Background and purpose. The erythematous response of human skin to radiotherapy has proven useful for testing the predictions of the linear quadratic (LQ) model in terms of fractionation sensitivity and repair half time. No formal investigation of the response of human skin to doses less than 2 Gy per fraction has occurred. This study aims to test the validity of the LQ model for human skin at doses ranging from 0.4 to 5.2 Gy per fraction. Materials and methods. Complete erythema reaction profiles were obtained using reflectance spectrophotometry in two patient populations: 65 patients treated palliatively with 5, 10, 12 and 20 daily treatment fractions (varying thicknesses of bolus, various body sites) and 52 patients undergoing prostatic irradiation for localised carcinoma of the prostate (no bolus, 30-32 fractions). Results and conclusions. Gender, age, site and prior sun exposure influence pre- and post-treatment erythema values independently of dose administered. Out-of-field effects were also noted. The linear quadratic model significantly underpredicted peak erythema values at doses less than 1.5 Gy per fraction. This suggests that either the conventional linear quadratic model does not apply for low doses per fraction in human skin or that erythema is not exclusively initiated by radiation damage to the basal layer. The data are potentially explained by an induced repair model
Game Theory and its Relationship with Linear Programming Models ...
African Journals Online (AJOL)
Game Theory and its Relationship with Linear Programming Models. ... This paper shows that game theory and linear programming problem are closely related subjects since any computing method devised for ... AJOL African Journals Online.
Introduction to linear programming: Coalitional game experiments
Energy Technology Data Exchange (ETDEWEB)
Lucas, W.
1994-12-31
Many solution notions in the multiperson cooperative games (in characteristic function form) make use of linear programming (LP). The popular concept of the {open_quotes}core{close_quotes} of a coalitional game is a special type of LP. It can be introduced in a very simple and quite exciting manner by means of a group experiment. A total of fifty dollars will be given to three randomly selected attendees who will take part in an experiment during this talk, presuming they behave in a Pareto optimal manner. Furthermore, the dual of the particular LP for the core gives rise to the idea of {open_quotes}balanced sets{close_quotes} which is an interesting combinatorial structure in its own right.
Robust Control Design via Linear Programming
Keel, L. H.; Bhattacharyya, S. P.
1998-01-01
This paper deals with the problem of synthesizing or designing a feedback controller of fixed dynamic order. The closed loop specifications considered here are given in terms of a target performance vector representing a desired set of closed loop transfer functions connecting various signals. In general these point targets are unattainable with a fixed order controller. By enlarging the target from a fixed point set to an interval set the solvability conditions with a fixed order controller are relaxed and a solution is more easily enabled. Results from the parametric robust control literature can be used to design the interval target family so that the performance deterioration is acceptable, even when plant uncertainty is present. It is shown that it is possible to devise a computationally simple linear programming approach that attempts to meet the desired closed loop specifications.
Stochastic linear programming models, theory, and computation
Kall, Peter
2011-01-01
This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors’ SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. … T...
The numerical solution of linear multi-term fractional differential equations: systems of equations
Edwards, John T.; Ford, Neville J.; Simpson, A. Charles
2002-11-01
In this paper, we show how the numerical approximation of the solution of a linear multi-term fractional differential equation can be calculated by reduction of the problem to a system of ordinary and fractional differential equations each of order at most unity. We begin by showing how our method applies to a simple class of problems and we give a convergence result. We solve the Bagley Torvik equation as an example. We show how the method can be applied to a general linear multi-term equation and give two further examples.
Guo, Feng; Wang, Xue-Yuan; Zhu, Cheng-Yin; Cheng, Xiao-Feng; Zhang, Zheng-Yu; Huang, Xu-Hui
2017-12-01
The stochastic resonance for a fractional oscillator with time-delayed kernel and quadratic trichotomous noise is investigated. Applying linear system theory and Laplace transform, the system output amplitude (SPA) for the fractional oscillator is obtained. It is found that the SPA is a periodical function of the kernel delayed-time. Stochastic multiplicative phenomenon appears on the SPA versus the driving frequency, versus the noise amplitude, and versus the fractional exponent. The non-monotonous dependence of the SPA on the system parameters is also discussed.
International Nuclear Information System (INIS)
Sasaki, Takehito; Kamata, Rikisaburo; Urahashi, Shingo; Yamaguchi, Tetsuji.
1993-01-01
One hundred and sixty-nine cervical lymph node-metastases from head and neck squamous cell carcinomas treated with either even fractionation or uneven fractionation regimens were analyzed in the present investigation. Logistic multivariate regression analysis indicated that: type of fractionation (even vs uneven), size of metastases, T value of primary tumors, and total dose are independent variables out of 18 variables that significantly influenced the rate of tumor clearance. The data, with statistical bias corrected by the regression equation, indicated that the uneven fractionation scheme significantly improved the rate of tumor clearance for the same size of metastases, total dose, and overall time compared to the even fractionation scheme. Further analysis by a linear-quadratic cell survival model indicated that the clinical improvement by uneven fractionation might not be explained entirely by a larger dose per fraction. It is suggested that tumor cells irradiated with an uneven fractionation regimen might repopulate more slowly, or they might be either less hypoxic or redistributed in a more radiosensitive phase in the cell cycle than those irradiated with even fractionation. This conclusion is clearly not definite, but it is suitable, pending the results of further investigation. (author)
A uniform law for convergence to the local times of linear fractional stable motions
Duffy, James A.
2016-01-01
We provide a uniform law for the weak convergence of additive functionals of partial sum processes to the local times of linear fractional stable motions, in a setting sufficiently general for statistical applications. Our results are fundamental to the analysis of the global properties of nonparametric estimators of nonlinear statistical models that involve such processes as covariates.
Stochastic Fractional Programming Approach to a Mean and Variance Model of a Transportation Problem
Directory of Open Access Journals (Sweden)
V. Charles
2011-01-01
Full Text Available In this paper, we propose a stochastic programming model, which considers a ratio of two nonlinear functions and probabilistic constraints. In the former, only expected model has been proposed without caring variability in the model. On the other hand, in the variance model, the variability played a vital role without concerning its counterpart, namely, the expected model. Further, the expected model optimizes the ratio of two linear cost functions where as variance model optimize the ratio of two non-linear functions, that is, the stochastic nature in the denominator and numerator and considering expectation and variability as well leads to a non-linear fractional program. In this paper, a transportation model with stochastic fractional programming (SFP problem approach is proposed, which strikes the balance between previous models available in the literature.
Optimized remedial groundwater extraction using linear programming
International Nuclear Information System (INIS)
Quinn, J.J.
1995-01-01
Groundwater extraction systems are typically installed to remediate contaminant plumes or prevent further spread of contamination. These systems are expensive to install and maintain. A traditional approach to designing such a wellfield uses a series of trial-and-error simulations to test the effects of various well locations and pump rates. However, the optimal locations and pump rates of extraction wells are difficult to determine when objectives related to the site hydrogeology and potential pumping scheme are considered. This paper describes a case study of an application of linear programming theory to determine optimal well placement and pump rates. The objectives of the pumping scheme were to contain contaminant migration and reduce contaminant concentrations while minimizing the total amount of water pumped and treated. Past site activities at the area under study included disposal of contaminants in pits. Several groundwater plumes have been identified, and others may be present. The area of concern is bordered on three sides by a wetland, which receives a portion of its input budget as groundwater discharge from the pits. Optimization of the containment pumping scheme was intended to meet three goals: (1) prevent discharge of contaminated groundwater to the wetland, (2) minimize the total water pumped and treated (cost benefit), and (3) avoid dewatering of the wetland (cost and ecological benefits). Possible well locations were placed at known source areas. To constrain the problem, the optimization program was instructed to prevent any flow toward the wetland along a user-specified border. In this manner, the optimization routine selects well locations and pump rates so that a groundwater divide is produced along this boundary
Uniqueness of non-linear ground states for fractional Laplacians in R
DEFF Research Database (Denmark)
Frank, Rupert L.; Lenzmann, Enno
2013-01-01
We prove uniqueness of ground state solutions Q = Q(|x|) ≥ 0 of the non-linear equation (−Δ)sQ+Q−Qα+1=0inR,where 0 fractional Laplacian in one dimension. In particular, we answer affirmatively an open question...... recently raised by Kenig–Martel–Robbiano and we generalize (by completely different techniques) the specific uniqueness result obtained by Amick and Toland for s=12 and α = 1 in [5] for the Benjamin–Ono equation. As a technical key result in this paper, we show that the associated linearized operator L...... + = (−Δ) s +1−(α+1)Q α is non-degenerate; i.e., its kernel satisfies ker L + = span{Q′}. This result about L + proves a spectral assumption, which plays a central role for the stability of solitary waves and blowup analysis for non-linear dispersive PDEs with fractional Laplacians, such as the generalized...
Liu, Da-Yan; Tian, Yang; Boutat, Driss; Laleg-Kirati, Taous-Meriem
2015-01-01
This paper aims at designing a digital fractional order differentiator for a class of signals satisfying a linear differential equation to estimate fractional derivatives with an arbitrary order in noisy case, where the input can be unknown or known with noises. Firstly, an integer order differentiator for the input is constructed using a truncated Jacobi orthogonal series expansion. Then, a new algebraic formula for the Riemann-Liouville derivative is derived, which is enlightened by the algebraic parametric method. Secondly, a digital fractional order differentiator is proposed using a numerical integration method in discrete noisy case. Then, the noise error contribution is analyzed, where an error bound useful for the selection of the design parameter is provided. Finally, numerical examples illustrate the accuracy and the robustness of the proposed fractional order differentiator.
Analytical approach to linear fractional partial differential equations arising in fluid mechanics
International Nuclear Information System (INIS)
Momani, Shaher; Odibat, Zaid
2006-01-01
In this Letter, we implement relatively new analytical techniques, the variational iteration method and the Adomian decomposition method, for solving linear fractional partial differential equations arising in fluid mechanics. The fractional derivatives are described in the Caputo sense. The two methods in applied mathematics can be used as alternative methods for obtaining analytic and approximate solutions for different types of fractional differential equations. In these methods, the solution takes the form of a convergent series with easily computable components. The corresponding solutions of the integer order equations are found to follow as special cases of those of fractional order equations. Some numerical examples are presented to illustrate the efficiency and reliability of the two methods
Liu, Da-Yan
2015-04-30
This paper aims at designing a digital fractional order differentiator for a class of signals satisfying a linear differential equation to estimate fractional derivatives with an arbitrary order in noisy case, where the input can be unknown or known with noises. Firstly, an integer order differentiator for the input is constructed using a truncated Jacobi orthogonal series expansion. Then, a new algebraic formula for the Riemann-Liouville derivative is derived, which is enlightened by the algebraic parametric method. Secondly, a digital fractional order differentiator is proposed using a numerical integration method in discrete noisy case. Then, the noise error contribution is analyzed, where an error bound useful for the selection of the design parameter is provided. Finally, numerical examples illustrate the accuracy and the robustness of the proposed fractional order differentiator.
Lorenzo, C F; Hartley, T T; Malti, R
2013-05-13
A new and simplified method for the solution of linear constant coefficient fractional differential equations of any commensurate order is presented. The solutions are based on the R-function and on specialized Laplace transform pairs derived from the principal fractional meta-trigonometric functions. The new method simplifies the solution of such fractional differential equations and presents the solutions in the form of real functions as opposed to fractional complex exponential functions, and thus is directly applicable to real-world physics.
Asymptotical Behavior of the Solution of a SDOF Linear Fractionally Damped Vibration System
Directory of Open Access Journals (Sweden)
Z.H. Wang
2011-01-01
Full Text Available Fractional-order derivative has been shown an adequate tool to the study of so-called "anomalous" social and physical behaviors, in reflecting their non-local, frequency- and history-dependent properties, and it has been used to model practical systems in engineering successfully, including the famous Bagley-Torvik equation modeling forced motion of a rigid plate immersed in Newtonian fluid. The solutions of the initial value problems of linear fractional differential equations are usually expressed in terms of Mittag-Leffler functions or some other kind of power series. Such forms of solutions are not good for engineers not only in understanding the solutions but also in investigation. This paper proves that for the linear SDOF oscillator with a damping described by fractional-order derivative whose order is between 1 and 2, the solution of its initial value problem free of external excitation consists of two parts, the first one is the 'eigenfunction expansion' that is similar to the case without fractional-order derivative, and the second one is a definite integral that is independent of the eigenvalues (or characteristic roots. The integral disappears in the classical linear oscillator and it can be neglected from the solution when stationary solution is addressed. Moreover, the response of the fractionally damped oscillator under harmonic excitation is calculated in a similar way, and it is found that the fractional damping with order between 1 and 2 can be used to produce oscillation with large amplitude as well as to suppress oscillation, depending on the ratio of the excitation frequency and the natural frequency.
A Fuzzy Linear Programming Approach for Aggregate Production Planning
DEFF Research Database (Denmark)
Iris, Cagatay; Cevikcan, Emre
2014-01-01
a mathematical programming framework for aggregate production planning problem under imprecise data environment. After providing background information about APP problem, together with fuzzy linear programming, the fuzzy linear programming model of APP is solved on an illustrative example for different a...
Kassa, Semu Mitiku; Tsegay, Teklay Hailay
2017-08-01
Tri-level optimization problems are optimization problems with three nested hierarchical structures, where in most cases conflicting objectives are set at each level of hierarchy. Such problems are common in management, engineering designs and in decision making situations in general, and are known to be strongly NP-hard. Existing solution methods lack universality in solving these types of problems. In this paper, we investigate a tri-level programming problem with quadratic fractional objective functions at each of the three levels. A solution algorithm has been proposed by applying fuzzy goal programming approach and by reformulating the fractional constraints to equivalent but non-fractional non-linear constraints. Based on the transformed formulation, an iterative procedure is developed that can yield a satisfactory solution to the tri-level problem. The numerical results on various illustrative examples demonstrated that the proposed algorithm is very much promising and it can also be used to solve larger-sized as well as n-level problems of similar structure.
A New Finite Continuation Algorithm for Linear Programming
DEFF Research Database (Denmark)
Madsen, Kaj; Nielsen, Hans Bruun; Pinar, Mustafa
1996-01-01
We describe a new finite continuation algorithm for linear programming. The dual of the linear programming problem with unit lower and upper bounds is formulated as an $\\ell_1$ minimization problem augmented with the addition of a linear term. This nondifferentiable problem is approximated...... by a smooth problem. It is shown that the minimizers of the smooth problem define a family of piecewise-linear paths as a function of a smoothing parameter. Based on this property, a finite algorithm that traces these paths to arrive at an optimal solution of the linear program is developed. The smooth...
Optimization Research of Generation Investment Based on Linear Programming Model
Wu, Juan; Ge, Xueqian
Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.
Arcentales, Andres; Rivera, Patricio; Caminal, Pere; Voss, Andreas; Bayes-Genis, Antonio; Giraldo, Beatriz F
2016-08-01
Changes in the left ventricle function produce alternans in the hemodynamic and electric behavior of the cardiovascular system. A total of 49 cardiomyopathy patients have been studied based on the blood pressure signal (BP), and were classified according to the left ventricular ejection fraction (LVEF) in low risk (LR: LVEF>35%, 17 patients) and high risk (HR: LVEF≤35, 32 patients) groups. We propose to characterize these patients using a linear and a nonlinear methods, based on the spectral estimation and the recurrence plot, respectively. From BP signal, we extracted each systolic time interval (STI), upward systolic slope (BPsl), and the difference between systolic and diastolic BP, defined as pulse pressure (PP). After, the best subset of parameters were obtained through the sequential feature selection (SFS) method. According to the results, the best classification was obtained using a combination of linear and nonlinear features from STI and PP parameters. For STI, the best combination was obtained considering the frequency peak and the diagonal structures of RP, with an area under the curve (AUC) of 79%. The same results were obtained when comparing PP values. Consequently, the use of combined linear and nonlinear parameters could improve the risk stratification of cardiomyopathy patients.
Estimation of Multiple Point Sources for Linear Fractional Order Systems Using Modulating Functions
Belkhatir, Zehor
2017-06-28
This paper proposes an estimation algorithm for the characterization of multiple point inputs for linear fractional order systems. First, using polynomial modulating functions method and a suitable change of variables the problem of estimating the locations and the amplitudes of a multi-pointwise input is decoupled into two algebraic systems of equations. The first system is nonlinear and solves for the time locations iteratively, whereas the second system is linear and solves for the input’s amplitudes. Second, closed form formulas for both the time location and the amplitude are provided in the particular case of single point input. Finally, numerical examples are given to illustrate the performance of the proposed technique in both noise-free and noisy cases. The joint estimation of pointwise input and fractional differentiation orders is also presented. Furthermore, a discussion on the performance of the proposed algorithm is provided.
Stability Analysis for Fractional-Order Linear Singular Delay Differential Systems
Directory of Open Access Journals (Sweden)
Hai Zhang
2014-01-01
Full Text Available We investigate the delay-independently asymptotic stability of fractional-order linear singular delay differential systems. Based on the algebraic approach, the sufficient conditions are presented to ensure the asymptotic stability for any delay parameter. By applying the stability criteria, one can avoid solving the roots of transcendental equations. An example is also provided to illustrate the effectiveness and applicability of the theoretical results.
High-order sliding mode observer for fractional commensurate linear systems with unknown input
Belkhatir, Zehor
2017-05-20
In this paper, a high-order sliding mode observer (HOSMO) is proposed for the joint estimation of the pseudo-state and the unknown input of fractional commensurate linear systems with single unknown input and a single output. The convergence of the proposed observer is proved using a Lyapunov-based approach. In addition, an enhanced variant of the proposed fractional-HOSMO is introduced to avoid the peaking phenomenon and thus to improve the estimation results in the transient phase. Simulation results are provided to illustrate the performance of the proposed fractional observer in both noise-free and noisy cases. The effect of the observer’s gains on the estimated pseudo-state and unknown input is also discussed.
High-order sliding mode observer for fractional commensurate linear systems with unknown input
Belkhatir, Zehor; Laleg-Kirati, Taous-Meriem
2017-01-01
In this paper, a high-order sliding mode observer (HOSMO) is proposed for the joint estimation of the pseudo-state and the unknown input of fractional commensurate linear systems with single unknown input and a single output. The convergence of the proposed observer is proved using a Lyapunov-based approach. In addition, an enhanced variant of the proposed fractional-HOSMO is introduced to avoid the peaking phenomenon and thus to improve the estimation results in the transient phase. Simulation results are provided to illustrate the performance of the proposed fractional observer in both noise-free and noisy cases. The effect of the observer’s gains on the estimated pseudo-state and unknown input is also discussed.
Directory of Open Access Journals (Sweden)
Baogui Xin
2012-01-01
Full Text Available Based on linear feedback control technique, a projective synchronization scheme of N-dimensional chaotic fractional-order systems is proposed, which consists of master and slave fractional-order financial systems coupled by linear state error variables. It is shown that the slave system can be projectively synchronized with the master system constructed by state transformation. Based on the stability theory of linear fractional order systems, a suitable controller for achieving synchronization is designed. The given scheme is applied to achieve projective synchronization of chaotic fractional-order financial systems. Numerical simulations are given to verify the effectiveness of the proposed projective synchronization scheme.
Output feedback control of linear fractional transformation systems subject to actuator saturation
Ban, Xiaojun; Wu, Fen
2016-11-01
In this paper, the control problem for a class of linear parameter varying (LPV) plant subject to actuator saturation is investigated. For the saturated LPV plant depending on the scheduling parameters in linear fractional transformation (LFT) fashion, a gain-scheduled output feedback controller in the LFT form is designed to guarantee the stability of the closed-loop LPV system and provide optimised disturbance/error attenuation performance. By using the congruent transformation, the synthesis condition is formulated as a convex optimisation problem in terms of a finite number of LMIs for which efficient optimisation techniques are available. The nonlinear inverted pendulum problem is employed to demonstrate the effectiveness of the proposed approach. Moreover, the comparison between our LPV saturated approach with an existing linear saturated method reveals the advantage of the LPV controller when handling nonlinear plants.
A Sawmill Manager Adapts To Change With Linear Programming
George F. Dutrow; James E. Granskog
1973-01-01
Linear programming provides guidelines for increasing sawmill capacity and flexibility and for determining stumpagepurchasing strategy. The operator of a medium-sized sawmill implemented improvements suggested by linear programming analysis; results indicate a 45 percent increase in revenue and a 36 percent hike in volume processed.
Analytic central path, sensitivity analysis and parametric linear programming
A.G. Holder; J.F. Sturm; S. Zhang (Shuzhong)
1998-01-01
textabstractIn this paper we consider properties of the central path and the analytic center of the optimal face in the context of parametric linear programming. We first show that if the right-hand side vector of a standard linear program is perturbed, then the analytic center of the optimal face
Application of the simplex method of linear programming model to ...
African Journals Online (AJOL)
This work discussed how the simplex method of linear programming could be used to maximize the profit of any business firm using Saclux Paint Company as a case study. It equally elucidated the effect variation in the optimal result obtained from linear programming model, will have on any given firm. It was demonstrated ...
Comparison of open-source linear programming solvers.
Energy Technology Data Exchange (ETDEWEB)
Gearhart, Jared Lee; Adair, Kristin Lynn; Durfee, Justin David.; Jones, Katherine A.; Martin, Nathaniel; Detry, Richard Joseph
2013-10-01
When developing linear programming models, issues such as budget limitations, customer requirements, or licensing may preclude the use of commercial linear programming solvers. In such cases, one option is to use an open-source linear programming solver. A survey of linear programming tools was conducted to identify potential open-source solvers. From this survey, four open-source solvers were tested using a collection of linear programming test problems and the results were compared to IBM ILOG CPLEX Optimizer (CPLEX) [1], an industry standard. The solvers considered were: COIN-OR Linear Programming (CLP) [2], [3], GNU Linear Programming Kit (GLPK) [4], lp_solve [5] and Modular In-core Nonlinear Optimization System (MINOS) [6]. As no open-source solver outperforms CPLEX, this study demonstrates the power of commercial linear programming software. CLP was found to be the top performing open-source solver considered in terms of capability and speed. GLPK also performed well but cannot match the speed of CLP or CPLEX. lp_solve and MINOS were considerably slower and encountered issues when solving several test problems.
Integrating Linear Programming and Analytical Hierarchical ...
African Journals Online (AJOL)
Study area is about 28000 ha of Keleibar- Chai Watershed, located in eastern Azerbaijan, Iran. Socio-economic information collected through a two-stage survey of 19 villages, including 300 samples. Thematic maps also have summarized Ecological factors, including physical and economic data. A comprehensive Linear ...
Introductory Linear Regression Programs in Undergraduate Chemistry.
Gale, Robert J.
1982-01-01
Presented are simple programs in BASIC and FORTRAN to apply the method of least squares. They calculate gradients and intercepts and express errors as standard deviations. An introduction of undergraduate students to such programs in a chemistry class is reviewed, and issues instructors should be aware of are noted. (MP)
Directory of Open Access Journals (Sweden)
M.S. Osman
2018-03-01
Full Text Available In this paper, an interactive approach for solving multi-level multi-objective fractional programming (ML-MOFP problems with fuzzy parameters is presented. The proposed interactive approach makes an extended work of Shi and Xia (1997. In the first phase, the numerical crisp model of the ML-MOFP problem has been developed at a confidence level without changing the fuzzy gist of the problem. Then, the linear model for the ML-MOFP problem is formulated. In the second phase, the interactive approach simplifies the linear multi-level multi-objective model by converting it into separate multi-objective programming problems. Also, each separate multi-objective programming problem of the linear model is solved by the ∊-constraint method and the concept of satisfactoriness. Finally, illustrative examples and comparisons with the previous approaches are utilized to evince the feasibility of the proposed approach.
Non-linear programming method in optimization of fast reactors
International Nuclear Information System (INIS)
Pavelesku, M.; Dumitresku, Kh.; Adam, S.
1975-01-01
Application of the non-linear programming methods on optimization of nuclear materials distribution in fast reactor is discussed. The programming task composition is made on the basis of the reactor calculation dependent on the fuel distribution strategy. As an illustration of this method application the solution of simple example is given. Solution of the non-linear program is done on the basis of the numerical method SUMT. (I.T.)
Directory of Open Access Journals (Sweden)
Nurdan Cetin
2014-01-01
Full Text Available We consider a multiobjective linear fractional transportation problem (MLFTP with several fractional criteria, such as, the maximization of the transport profitability like profit/cost or profit/time, and its two properties are source and destination. Our aim is to introduce MLFTP which has not been studied in literature before and to provide a fuzzy approach which obtain a compromise Pareto-optimal solution for this problem. To do this, first, we present a theorem which shows that MLFTP is always solvable. And then, reducing MLFTP to the Zimmermann’s “min” operator model which is the max-min problem, we construct Generalized Dinkelbach’s Algorithm for solving the obtained problem. Furthermore, we provide an illustrative numerical example to explain this fuzzy approach.
International Nuclear Information System (INIS)
Hariz, M.I.; Laitinen, L.V.; Henriksson, R.; Saeterborg, N.-E.; Loefroth, P.-O.
1990-01-01
A new technique for fractionated stereotactic irradiation of intracranial lesions is described. The treatment is based on a versatile, non-invasive interface for stereotactic localization of the brain target imaged by computed tomography (CT), angiography or magnetic resonance tomography (MRT), and subsequent repetitive stereotactic irradiation of the target using a linear accelerator. The fractionation of the stereotactic irradiation was intended to meet the requirements of the basic principles of radiobiology. The radiophysical evaluation using phantoms, and the clinical results in a small number of patients, demonstrated a good reproducibilit between repeated positionings of the target in the isocenter of the accelerator, and a high degree of accuracy in the treatment of brain lesions. (authors). 28 refs.; 11 figs.; 1 tab
Pop, P.C.; Still, Georg J.
1999-01-01
In linear programming it is known that an appropriate non-homogeneous Farkas Lemma leads to a short proof of the strong duality results for a pair of primal and dual programs. By using a corresponding generalized Farkas lemma we give a similar proof of the strong duality results for semidefinite
Linear System of Equations, Matrix Inversion, and Linear Programming Using MS Excel
El-Gebeily, M.; Yushau, B.
2008-01-01
In this note, we demonstrate with illustrations two different ways that MS Excel can be used to solve Linear Systems of Equation, Linear Programming Problems, and Matrix Inversion Problems. The advantage of using MS Excel is its availability and transparency (the user is responsible for most of the details of how a problem is solved). Further, we…
Duality in non-linear programming
Jeyalakshmi, K.
2018-04-01
In this paper we consider duality and converse duality for a programming problem involving convex objective and constraint functions with finite dimensional range. We do not assume any constraint qualification. The dual is presented by reducing the problem to a standard Lagrange multiplier problem.
Directory of Open Access Journals (Sweden)
Yi-hua Zhong
2013-01-01
Full Text Available Recently, various methods have been developed for solving linear programming problems with fuzzy number, such as simplex method and dual simplex method. But their computational complexities are exponential, which is not satisfactory for solving large-scale fuzzy linear programming problems, especially in the engineering field. A new method which can solve large-scale fuzzy number linear programming problems is presented in this paper, which is named a revised interior point method. Its idea is similar to that of interior point method used for solving linear programming problems in crisp environment before, but its feasible direction and step size are chosen by using trapezoidal fuzzy numbers, linear ranking function, fuzzy vector, and their operations, and its end condition is involved in linear ranking function. Their correctness and rationality are proved. Moreover, choice of the initial interior point and some factors influencing the results of this method are also discussed and analyzed. The result of algorithm analysis and example study that shows proper safety factor parameter, accuracy parameter, and initial interior point of this method may reduce iterations and they can be selected easily according to the actual needs. Finally, the method proposed in this paper is an alternative method for solving fuzzy number linear programming problems.
Optical Measurement of Radiocarbon below Unity Fraction Modern by Linear Absorption Spectroscopy.
Fleisher, Adam J; Long, David A; Liu, Qingnan; Gameson, Lyn; Hodges, Joseph T
2017-09-21
High-precision measurements of radiocarbon ( 14 C) near or below a fraction modern 14 C of 1 (F 14 C ≤ 1) are challenging and costly. An accurate, ultrasensitive linear absorption approach to detecting 14 C would provide a simple and robust benchtop alternative to off-site accelerator mass spectrometry facilities. Here we report the quantitative measurement of 14 C in gas-phase samples of CO 2 with F 14 C radiocarbon measurement science including the study of biofuels and bioplastics, illicitly traded specimens, bomb dating, and atmospheric transport.
Linear Parametric Sensitivity Analysis of the Constraint Coefficient Matrix in Linear Programs
Zuidwijk, Rob
2005-01-01
textabstractSensitivity analysis is used to quantify the impact of changes in the initial data of linear programs on the optimal value. In particular, parametric sensitivity analysis involves a perturbation analysis in which the effects of small changes of some or all of the initial data on an optimal solution are investigated, and the optimal solution is studied on a so-called critical range of the initial data, in which certain properties such as the optimal basis in linear programming are ...
Pei, Soo-Chang; Ding, Jian-Jiun
2005-03-01
Prolate spheroidal wave functions (PSWFs) are known to be useful for analyzing the properties of the finite-extension Fourier transform (fi-FT). We extend the theory of PSWFs for the finite-extension fractional Fourier transform, the finite-extension linear canonical transform, and the finite-extension offset linear canonical transform. These finite transforms are more flexible than the fi-FT and can model much more generalized optical systems. We also illustrate how to use the generalized prolate spheroidal functions we derive to analyze the energy-preservation ratio, the self-imaging phenomenon, and the resonance phenomenon of the finite-sized one-stage or multiple-stage optical systems.
General guidelines solution for linear programming with fuzzy coefficients
Directory of Open Access Journals (Sweden)
Sergio Gerardo de los Cobos Silva
2013-08-01
Full Text Available This work introduce to the Possibilistic Programming and the Fuzzy Programming as paradigms that allow to resolve problems of linear programming when the coefficients of the model or the restrictions on the same are presented as fuzzy numbers, rather than exact numbers (crisp. This work presents some examples based on [1].
Large-scale linear programs in planning and prediction.
2017-06-01
Large-scale linear programs are at the core of many traffic-related optimization problems in both planning and prediction. Moreover, many of these involve significant uncertainty, and hence are modeled using either chance constraints, or robust optim...
Evaluating forest management policies by parametric linear programing
Daniel I. Navon; Richard J. McConnen
1967-01-01
An analytical and simulation technique, parametric linear programing explores alternative conditions and devises an optimal management plan for each condition. Its application in solving policy-decision problems in the management of forest lands is illustrated in an example.
Formulated linear programming problems from game theory and its ...
African Journals Online (AJOL)
Formulated linear programming problems from game theory and its computer implementation using Tora package. ... Game theory, a branch of operations research examines the various concepts of decision ... AJOL African Journals Online.
Near-Regular Structure Discovery Using Linear Programming
Huang, Qixing; Guibas, Leonidas J.; Mitra, Niloy J.
2014-01-01
as an optimization and efficiently solve it using linear programming techniques. Our optimization has a discrete aspect, that is, the connectivity relationships among the elements, as well as a continuous aspect, namely the locations of the elements of interest. Both
A property of assignment type mixed integer linear programming problems
Benders, J.F.; van Nunen, J.A.E.E.
1982-01-01
In this paper we will proof that rather tight upper bounds can be given for the number of non-unique assignments that are achieved after solving the linear programming relaxation of some types of mixed integer linear assignment problems. Since in these cases the number of splitted assignments is
Scatter fractions from linear accelerators with x-ray energies from 6 to 24 MV.
Taylor, P L; Rodgers, J E; Shobe, J
1999-08-01
Computation of shielding requirements for a linear accelerator must take into account the amount of radiation scattered from the patient to areas outside the primary beam. Currently, the most frequently used data are from NCRP 49 that only includes data for x-ray energies up to 6 MV and angles from 30 degrees to 135 degrees. In this work we have determined by Monte Carlo simulation the scattered fractions of dose for a wide range of energies and angles of clinical significance including 6, 10, 18, and 24 MV and scattering angles from 10 degrees to 150 degrees. Calculations were made for a 400 cm2 circular field size impinging onto a spherical phantom. Scattered fractions of dose were determined at 1 m from the phantom. Angles from 10 degrees to 30 degrees are of concern for higher energies where the scatter is primarily in the forward direction. An error in scatter fraction may result in too little secondary shielding near the junction with the primary barrier. The Monte Carlo code ITS (Version 3.0) developed at Sandia National Laboratory and NIST was used to simulate scatter from the patient to the barrier. Of significance was the variation of calculated scattered dose with depth of measurement within the barrier indicating that accurate values may be difficult to obtain. Mean energies of scatter x-ray spectra are presented.
Linear Programming and Its Application to Pattern Recognition Problems
Omalley, M. J.
1973-01-01
Linear programming and linear programming like techniques as applied to pattern recognition problems are discussed. Three relatively recent research articles on such applications are summarized. The main results of each paper are described, indicating the theoretical tools needed to obtain them. A synopsis of the author's comments is presented with regard to the applicability or non-applicability of his methods to particular problems, including computational results wherever given.
International Nuclear Information System (INIS)
Stiebel-Kalish, Hadas; Reich, Ehud; Gal, Lior; Rappaport, Zvi Harry; Nissim, Ouzi; Pfeffer, Raphael; Spiegelmann, Roberto
2012-01-01
Purpose: Meningiomas threatening the anterior visual pathways (AVPs) and not amenable for surgery are currently treated with multisession stereotactic radiotherapy. Stereotactic radiotherapy is available with a number of devices. The most ubiquitous include the gamma knife, CyberKnife, tomotherapy, and isocentric linear accelerator systems. The purpose of our study was to describe a case series of AVP meningiomas treated with linear accelerator fractionated stereotactic radiotherapy (FSRT) using the multiple, noncoplanar, dynamic conformal rotation paradigm and to compare the success and complication rates with those reported for other techniques. Patients and Methods: We included all patients with AVP meningiomas followed up at our neuro-ophthalmology unit for a minimum of 12 months after FSRT. We compared the details of the neuro-ophthalmologic examinations and tumor size before and after FSRT and at the end of follow-up. Results: Of 87 patients with AVP meningiomas, 17 had been referred for FSRT. Of the 17 patients, 16 completed >12 months of follow-up (mean 39). Of the 16 patients, 11 had undergone surgery before FSRT and 5 had undergone FSRT as first-line management. Tumor control was achieved in 14 of the 16 patients, with three meningiomas shrinking in size after RT. Two meningiomas progressed, one in an area that was outside the radiation field. The visual function had improved in 6 or stabilized in 8 of the 16 patients (88%) and worsened in 2 (12%). Conclusions: Linear accelerator fractionated RT using the multiple noncoplanar dynamic rotation conformal paradigm can be offered to patients with meningiomas that threaten the anterior visual pathways as an adjunct to surgery or as first-line treatment, with results comparable to those reported for other stereotactic RT techniques.
EZLP: An Interactive Computer Program for Solving Linear Programming Problems. Final Report.
Jarvis, John J.; And Others
Designed for student use in solving linear programming problems, the interactive computer program described (EZLP) permits the student to input the linear programming model in exactly the same manner in which it would be written on paper. This report includes a brief review of the development of EZLP; narrative descriptions of program features,…
The RANDOM computer program: A linear congruential random number generator
Miles, R. F., Jr.
1986-01-01
The RANDOM Computer Program is a FORTRAN program for generating random number sequences and testing linear congruential random number generators (LCGs). The linear congruential form of random number generator is discussed, and the selection of parameters of an LCG for a microcomputer described. This document describes the following: (1) The RANDOM Computer Program; (2) RANDOM.MOD, the computer code needed to implement an LCG in a FORTRAN program; and (3) The RANCYCLE and the ARITH Computer Programs that provide computational assistance in the selection of parameters for an LCG. The RANDOM, RANCYCLE, and ARITH Computer Programs are written in Microsoft FORTRAN for the IBM PC microcomputer and its compatibles. With only minor modifications, the RANDOM Computer Program and its LCG can be run on most micromputers or mainframe computers.
Planning Student Flow with Linear Programming: A Tunisian Case Study.
Bezeau, Lawrence
A student flow model in linear programming format, designed to plan the movement of students into secondary and university programs in Tunisia, is described. The purpose of the plan is to determine a sufficient number of graduating students that would flow back into the system as teachers or move into the labor market to meet fixed manpower…
Linear Programming for Vocational Education Planning. Interim Report.
Young, Robert C.; And Others
The purpose of the paper is to define for potential users of vocational education management information systems a quantitative analysis technique and its utilization to facilitate more effective planning of vocational education programs. Defining linear programming (LP) as a management technique used to solve complex resource allocation problems…
Using linear programming to analyze and optimize stochastic flow lines
DEFF Research Database (Denmark)
Helber, Stefan; Schimmelpfeng, Katja; Stolletz, Raik
2011-01-01
This paper presents a linear programming approach to analyze and optimize flow lines with limited buffer capacities and stochastic processing times. The basic idea is to solve a huge but simple linear program that models an entire simulation run of a multi-stage production process in discrete time...... programming and hence allows us to solve buffer allocation problems. We show under which conditions our method works well by comparing its results to exact values for two-machine models and approximate simulation results for longer lines....
Linear combination of forecasts with numerical adjustment via MINIMAX non-linear programming
Directory of Open Access Journals (Sweden)
Jairo Marlon Corrêa
2016-03-01
Full Text Available This paper proposes a linear combination of forecasts obtained from three forecasting methods (namely, ARIMA, Exponential Smoothing and Artificial Neural Networks whose adaptive weights are determined via a multi-objective non-linear programming problem, which seeks to minimize, simultaneously, the statistics: MAE, MAPE and MSE. The results achieved by the proposed combination are compared with the traditional approach of linear combinations of forecasts, where the optimum adaptive weights are determined only by minimizing the MSE; with the combination method by arithmetic mean; and with individual methods
Directory of Open Access Journals (Sweden)
Hua Wang
2017-01-01
Full Text Available Abstract In this paper, we first introduce some new Morrey-type spaces containing generalized Morrey space and weighted Morrey space with two weights as special cases. Then we give the weighted strong type and weak type estimates for fractional integral operators I α $I_{\\alpha}$ in these new Morrey-type spaces. Furthermore, the weighted strong type estimate and endpoint estimate of linear commutators [ b , I α ] $[b,I_{\\alpha}]$ formed by b and I α $I_{\\alpha}$ are established. Also we study related problems about two-weight, weak type inequalities for I α $I_{\\alpha}$ and [ b , I α ] $[b,I_{\\alpha}]$ in the Morrey-type spaces and give partial results.
Measuring the Higgs branching fraction into two photons at future linear e+e- colliders
International Nuclear Information System (INIS)
Boos, E.; Schreiber, H.J.; Shanidze, R.
2001-01-01
We examine the prospects for a measurement of the branching fraction of the γγ decay mode of a Standard Model-like Higgs boson with a mass of 120 GeV/c 2 at the future TESLA linear e + e - collider, assuming an integrated luminosity of 1 ab -1 and centre-of-mass energies of 350 GeV and 500 GeV. A relative uncertainty on BF(H→γγ) of 16% can be achieved in unpolarised e + e - collisions at √(s) = 500 GeV, while for √(s) = 350 GeV the expected precision is slightly poorer. With appropriate initial state polarisations the uncertainty can be improved to 10%. If this measurement is combined with a measurement of the total Higgs width, a precision of 10% on the Higgs boson partial width for the γγ decay mode appears feasible. (orig.)
Application of the method of continued fractions for electron scattering by linear molecules
International Nuclear Information System (INIS)
Lee, M.-T.; Iga, I.; Fujimoto, M.M.; Lara, O.; Brasilia Univ., DF
1995-01-01
The method of continued fractions (MCF) of Horacek and Sasakawa is adapted for the first time to study low-energy electron scattering by linear molecules. Particularly, we have calculated the reactance K-matrices for an electron scattered by hydrogen molecule and hydrogen molecular ion as well as by a polar LiH molecule in the static-exchange level. For all the applications studied herein. the calculated physical quantities converge rapidly, even for a strongly polar molecule such as LiH, to the correct values and in most cases the convergence is monotonic. Our study suggests that the MCF could be an efficient method for studying electron-molecule scattering and also photoionization of molecules. (Author)
Hennelly, Bryan M.; Sheridan, John T.
2005-05-01
By use of matrix-based techniques it is shown how the space-bandwidth product (SBP) of a signal, as indicated by the location of the signal energy in the Wigner distribution function, can be tracked through any quadratic-phase optical system whose operation is described by the linear canonical transform. Then, applying the regular uniform sampling criteria imposed by the SBP and linking the criteria explicitly to a decomposition of the optical matrix of the system, it is shown how numerical algorithms (employing interpolation and decimation), which exhibit both invertibility and additivity, can be implemented. Algorithms appearing in the literature for a variety of transforms (Fresnel, fractional Fourier) are shown to be special cases of our general approach. The method is shown to allow the existing algorithms to be optimized and is also shown to permit the invention of many new algorithms.
Scattered fractions of dose from 18 and 25 MV X-ray radiotherapy linear accelerators
International Nuclear Information System (INIS)
Shobe, J.; Rodgers, J.E.; Taylor, P.L.; Jackson, J.; Popescu, G.
1996-01-01
Over the years, measurements have been made at a few energies to estimate the scattered fraction of dose from the patient in medical radiotherapy operations. This information has been a useful aid in the determination of shielding requirements for these facilities. With these measurements, known characteriztics of photons, and various other known parameters, Monte Carlo codes are being used to calculate the scattered fractions and hence the shielding requirements for the photons of other energies commonly used in radiotherapeutic applications. The National Institute of Standards and Technology (NIST) acquired a Sagittaire medical linear accelerator (linac) which was previously located at the Yale-New Haven Hospital. This linac provides an X-ray beam of 25 MV photons and electron beams with energies up to 32 MeV. The housing on the gantry was permanently removed from the accelerator during installation. A Varian Clinac 1800 linear accelerator was used to produce the 18 MV photons at the Frederick Memorial Hospital Regional Cancer Therapy Center in Frederick, MD. This paper represents a study of the photon dose scattered from a patient in typical radiation treatment situations as it relates to the dose delivered at the isocenter in water. The results of these measurements will be compared to Monte Carlo calculations. Photon spectral measurements were not made at this time. Neutron spectral measurements were made on this Sagittaire machine in its previous location and that work was not repeated here, although a brief study of the neutron component of the 18 and 25 MV linacs was performed utilizing thermoluminescent dosimetry (TLD) to determine the isotropy of the neutron dose. (author)
Merrikh-Bayat, Farshad
2011-04-01
One main approach for time-domain simulation of the linear output-feedback systems containing fractional-order controllers is to approximate the transfer function of the controller with an integer-order transfer function and then perform the simulation. In general, this approach suffers from two main disadvantages: first, the internal stability of the resulting feedback system is not guaranteed, and second, the amount of error caused by this approximation is not exactly known. The aim of this paper is to propose an efficient method for time-domain simulation of such systems without facing the above mentioned drawbacks. For this purpose, the fractional-order controller is approximated with an integer-order transfer function (possibly in combination with the delay term) such that the internal stability of the closed-loop system is guaranteed, and then the simulation is performed. It is also shown that the resulting approximate controller can effectively be realized by using the proposed method. Some formulas for estimating and correcting the simulation error, when the feedback system under consideration is subjected to the unit step command or the unit step disturbance, are also presented. Finally, three numerical examples are studied and the results are compared with the Oustaloup continuous approximation method. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
A Recurrent Neural Network for Nonlinear Fractional Programming
Directory of Open Access Journals (Sweden)
Quan-Ju Zhang
2012-01-01
Full Text Available This paper presents a novel recurrent time continuous neural network model which performs nonlinear fractional optimization subject to interval constraints on each of the optimization variables. The network is proved to be complete in the sense that the set of optima of the objective function to be minimized with interval constraints coincides with the set of equilibria of the neural network. It is also shown that the network is primal and globally convergent in the sense that its trajectory cannot escape from the feasible region and will converge to an exact optimal solution for any initial point being chosen in the feasible interval region. Simulation results are given to demonstrate further the global convergence and good performance of the proposing neural network for nonlinear fractional programming problems with interval constraints.
Linear program differentiation for single-channel speech separation
DEFF Research Database (Denmark)
Pearlmutter, Barak A.; Olsson, Rasmus Kongsgaard
2006-01-01
Many apparently difficult problems can be solved by reduction to linear programming. Such problems are often subproblems within larger systems. When gradient optimisation of the entire larger system is desired, it is necessary to propagate gradients through the internally-invoked LP solver....... For instance, when an intermediate quantity z is the solution to a linear program involving constraint matrix A, a vector of sensitivities dE/dz will induce sensitivities dE/dA. Here we show how these can be efficiently calculated, when they exist. This allows algorithmic differentiation to be applied...... to algorithms that invoke linear programming solvers as subroutines, as is common when using sparse representations in signal processing. Here we apply it to gradient optimisation of over complete dictionaries for maximally sparse representations of a speech corpus. The dictionaries are employed in a single...
Linear Parametric Sensitivity Analysis of the Constraint Coefficient Matrix in Linear Programs
R.A. Zuidwijk (Rob)
2005-01-01
textabstractSensitivity analysis is used to quantify the impact of changes in the initial data of linear programs on the optimal value. In particular, parametric sensitivity analysis involves a perturbation analysis in which the effects of small changes of some or all of the initial data on an
Synthesizing Dynamic Programming Algorithms from Linear Temporal Logic Formulae
Rosu, Grigore; Havelund, Klaus
2001-01-01
The problem of testing a linear temporal logic (LTL) formula on a finite execution trace of events, generated by an executing program, occurs naturally in runtime analysis of software. We present an algorithm which takes an LTL formula and generates an efficient dynamic programming algorithm. The generated algorithm tests whether the LTL formula is satisfied by a finite trace of events given as input. The generated algorithm runs in linear time, its constant depending on the size of the LTL formula. The memory needed is constant, also depending on the size of the formula.
An Instructional Note on Linear Programming--A Pedagogically Sound Approach.
Mitchell, Richard
1998-01-01
Discusses the place of linear programming in college curricula and the advantages of using linear-programming software. Lists important characteristics of computer software used in linear programming for more effective teaching and learning. (ASK)
Applied Research of Enterprise Cost Control Based on Linear Programming
Directory of Open Access Journals (Sweden)
Yu Shuo
2015-01-01
This paper researches the enterprise cost control through the linear programming model, and analyzes the restriction factors of the labor of enterprise production, raw materials, processing equipment, sales price, and other factors affecting the enterprise income, so as to obtain an enterprise cost control model based on the linear programming. This model can calculate rational production mode in the case of limited resources, and acquire optimal enterprise income. The production guiding program and scheduling arrangement of the enterprise can be obtained through calculation results, so as to provide scientific and effective guidance for the enterprise production. This paper adds the sensitivity analysis in the linear programming model, so as to learn about the stability of the enterprise cost control model based on linear programming through the sensitivity analysis, and verify the rationality of the model, and indicate the direction for the enterprise cost control. The calculation results of the model can provide a certain reference for the enterprise planning in the market economy environment, which have strong reference and practical significance in terms of the enterprise cost control.
Non-linear nuclear engineering models as genetic programming application
International Nuclear Information System (INIS)
Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S.
1997-01-01
This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs
A MICROCOMPUTER LINEAR PROGRAMMING PACKAGE: AN ALTERNATIVE TO MAINFRAMES
Laughlin, David H.
1984-01-01
This paper presents the capabilities and limitations of a microcomputer linear programming package. The solution algorithm is a version of the revised simplex. Rapid problem entry, user ease of operation, sensitivity analyses on objective function and right hand sides are advantages. A problem size of 150 activities and 64 constraints can be solved in present form. Due to problem size, limitations and lack of parametric and integer programming routines, this package is thought to have the mos...
Optimal traffic control in highway transportation networks using linear programming
Li, Yanning; Canepa, Edward S.; Claudel, Christian G.
2014-01-01
of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can
LCPT: a program for finding linear canonical transformations
International Nuclear Information System (INIS)
Char, B.W.; McNamara, B.
1979-01-01
This article describes a MACSYMA program to compute symbolically a canonical linear transformation between coordinate systems. The difficulties in implementation of this canonical small physics problem are also discussed, along with the implications that may be drawn from such difficulties about widespread MACSYMA usage by the community of computational/theoretical physicists
Fitting program for linear regressions according to Mahon (1996)
Energy Technology Data Exchange (ETDEWEB)
2018-01-09
This program takes the users' Input data and fits a linear regression to it using the prescription presented by Mahon (1996). Compared to the commonly used York fit, this method has the correct prescription for measurement error propagation. This software should facilitate the proper fitting of measurements with a simple Interface.
Linear Programming, the Simplex Algorithm and Simple Polytopes
Directory of Open Access Journals (Sweden)
Das Bhusan
2010-09-01
Full Text Available In the first part of the paper we survey some far reaching applications of the basis facts of linear programming to the combinatorial theory of simple polytopes. In the second part we discuss some recent developments concurring the simplex algorithm. We describe sub-exponential randomized pivot roles and upper bounds on the diameter of graphs of polytopes.
A mixed integer linear program for an integrated fishery | Hasan ...
African Journals Online (AJOL)
... and labour allocation of quota based integrated fisheries. We demonstrate the workability of our model with a numerical example and sensitivity analysis based on data obtained from one of the major fisheries in New Zealand. Keywords: mixed integer linear program, fishing, trawler scheduling, processing, quotas ORiON: ...
Interior-Point Methods for Linear Programming: A Review
Singh, J. N.; Singh, D.
2002-01-01
The paper reviews some recent advances in interior-point methods for linear programming and indicates directions in which future progress can be made. Most of the interior-point methods belong to any of three categories: affine-scaling methods, potential reduction methods and central path methods. These methods are discussed together with…
A Partitioning and Bounded Variable Algorithm for Linear Programming
Sheskin, Theodore J.
2006-01-01
An interesting new partitioning and bounded variable algorithm (PBVA) is proposed for solving linear programming problems. The PBVA is a variant of the simplex algorithm which uses a modified form of the simplex method followed by the dual simplex method for bounded variables. In contrast to the two-phase method and the big M method, the PBVA does…
A Spreadsheet-Based, Matrix Formulation Linear Programming Lesson
DEFF Research Database (Denmark)
Harrod, Steven
2009-01-01
The article focuses on the spreadsheet-based, matrix formulation linear programming lesson. According to the article, it makes a higher level of theoretical mathematics approachable by a wide spectrum of students wherein many may not be decision sciences or quantitative methods majors. Moreover...
175 Years of Linear Programming - Minimax and Cake Topography
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 7. 175 Years of Linear Programming - Minimax and Cake Topography. Vijay Chandru M R Rao. Series Article Volume 4 Issue 7 July 1999 pp 4-13. Fulltext. Click here to view fulltext PDF. Permanent link:
Analysis of Students' Errors on Linear Programming at Secondary ...
African Journals Online (AJOL)
The purpose of this study was to identify secondary school students' errors on linear programming at 'O' level. It is based on the fact that students' errors inform teaching hence an essential tool for any serious mathematics teacher who intends to improve mathematics teaching. The study was guided by a descriptive survey ...
Belazi, Akram; Abd El-Latif, Ahmed A.; Diaconu, Adrian-Viorel; Rhouma, Rhouma; Belghith, Safya
2017-01-01
In this paper, a new chaos-based partial image encryption scheme based on Substitution-boxes (S-box) constructed by chaotic system and Linear Fractional Transform (LFT) is proposed. It encrypts only the requisite parts of the sensitive information in Lifting-Wavelet Transform (LWT) frequency domain based on hybrid of chaotic maps and a new S-box. In the proposed encryption scheme, the characteristics of confusion and diffusion are accomplished in three phases: block permutation, substitution, and diffusion. Then, we used dynamic keys instead of fixed keys used in other approaches, to control the encryption process and make any attack impossible. The new S-box was constructed by mixing of chaotic map and LFT to insure the high confidentiality in the inner encryption of the proposed approach. In addition, the hybrid compound of S-box and chaotic systems strengthened the whole encryption performance and enlarged the key space required to resist the brute force attacks. Extensive experiments were conducted to evaluate the security and efficiency of the proposed approach. In comparison with previous schemes, the proposed cryptosystem scheme showed high performances and great potential for prominent prevalence in cryptographic applications.
International Nuclear Information System (INIS)
Dale, R.G.
1986-01-01
By extending a previously developed mathematical model based on the linear-quadratic dose-effect relationship, it is possible to examine the consequences of performing fractionated treatments for which there is insufficient time between fractions to allow complete damage repair. Equations are derived which give the relative effectiveness of such treatments in terms of tissue-repair constants (μ values) and α/β ratios, and these are then applied to some examples of treatments involving multiple fractions per day. The interplay of the various mechanisms involved (including repopulation effects) and their possible influence on treatments involving closely spaced fractions are examined. If current indications of the differences in recovery rates between early- and late-reacting normal tissues are representative, then it is shown that such differences may limit the clinical potential of accelerated fractionation regimes, where several fractions per day are given in a relatively short overall time. (author)
Linear decomposition approach for a class of nonconvex programming problems.
Shen, Peiping; Wang, Chunfeng
2017-01-01
This paper presents a linear decomposition approach for a class of nonconvex programming problems by dividing the input space into polynomially many grids. It shows that under certain assumptions the original problem can be transformed and decomposed into a polynomial number of equivalent linear programming subproblems. Based on solving a series of liner programming subproblems corresponding to those grid points we can obtain the near-optimal solution of the original problem. Compared to existing results in the literature, the proposed algorithm does not require the assumptions of quasi-concavity and differentiability of the objective function, and it differs significantly giving an interesting approach to solving the problem with a reduced running time.
Directory of Open Access Journals (Sweden)
Rossikhin Yury A.
2018-01-01
Full Text Available Non-linear damped vibrations of a cylindrical shell embedded into a fractional derivative medium are investigated for the case of the combinational internal resonance, resulting in modal interaction, using two different numerical methods with further comparison of the results obtained. The damping properties of the surrounding medium are described by the fractional derivative Kelvin-Voigt model utilizing the Riemann-Liouville fractional derivatives. Within the first method, the generalized displacements of a coupled set of nonlinear ordinary differential equations of the second order are estimated using numerical solution of nonlinear multi-term fractional differential equations by the procedure based on the reduction of the problem to a system of fractional differential equations. According to the second method, the amplitudes and phases of nonlinear vibrations are estimated from the governing nonlinear differential equations describing amplitude-and-phase modulations for the case of the combinational internal resonance. A good agreement in results is declared.
Yang, Yongge; Xu, Wei; Yang, Guidong; Jia, Wantao
2016-08-01
The Poisson white noise, as a typical non-Gaussian excitation, has attracted much attention recently. However, little work was referred to the study of stochastic systems with fractional derivative under Poisson white noise excitation. This paper investigates the stationary response of a class of quasi-linear systems with fractional derivative excited by Poisson white noise. The equivalent stochastic system of the original stochastic system is obtained. Then, approximate stationary solutions are obtained with the help of the perturbation method. Finally, two typical examples are discussed in detail to demonstrate the effectiveness of the proposed method. The analysis also shows that the fractional order and the fractional coefficient significantly affect the responses of the stochastic systems with fractional derivative.
International Nuclear Information System (INIS)
Yang, Yongge; Xu, Wei; Yang, Guidong; Jia, Wantao
2016-01-01
The Poisson white noise, as a typical non-Gaussian excitation, has attracted much attention recently. However, little work was referred to the study of stochastic systems with fractional derivative under Poisson white noise excitation. This paper investigates the stationary response of a class of quasi-linear systems with fractional derivative excited by Poisson white noise. The equivalent stochastic system of the original stochastic system is obtained. Then, approximate stationary solutions are obtained with the help of the perturbation method. Finally, two typical examples are discussed in detail to demonstrate the effectiveness of the proposed method. The analysis also shows that the fractional order and the fractional coefficient significantly affect the responses of the stochastic systems with fractional derivative.
Energy Technology Data Exchange (ETDEWEB)
Yang, Yongge; Xu, Wei, E-mail: weixu@nwpu.edu.cn; Yang, Guidong; Jia, Wantao [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)
2016-08-15
The Poisson white noise, as a typical non-Gaussian excitation, has attracted much attention recently. However, little work was referred to the study of stochastic systems with fractional derivative under Poisson white noise excitation. This paper investigates the stationary response of a class of quasi-linear systems with fractional derivative excited by Poisson white noise. The equivalent stochastic system of the original stochastic system is obtained. Then, approximate stationary solutions are obtained with the help of the perturbation method. Finally, two typical examples are discussed in detail to demonstrate the effectiveness of the proposed method. The analysis also shows that the fractional order and the fractional coefficient significantly affect the responses of the stochastic systems with fractional derivative.
DEFF Research Database (Denmark)
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2014-01-01
In the paper, three frequently used operation optimisation methods are examined with respect to their impact on operation management of the combined utility technologies for electric power and DH (district heating) of eastern Denmark. The investigation focusses on individual plant operation...... differences and differences between the solution found by each optimisation method. One of the investigated approaches utilises LP (linear programming) for optimisation, one uses LP with binary operation constraints, while the third approach uses NLP (non-linear programming). The LP model is used...... as a benchmark, as this type is frequently used, and has the lowest amount of constraints of the three. A comparison of the optimised operation of a number of units shows significant differences between the three methods. Compared to the reference, the use of binary integer variables, increases operation...
Train Repathing in Emergencies Based on Fuzzy Linear Programming
Directory of Open Access Journals (Sweden)
Xuelei Meng
2014-01-01
Full Text Available Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.
Train repathing in emergencies based on fuzzy linear programming.
Meng, Xuelei; Cui, Bingmou
2014-01-01
Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.
Relaxation Methods for Strictly Convex Regularizations of Piecewise Linear Programs
International Nuclear Information System (INIS)
Kiwiel, K. C.
1998-01-01
We give an algorithm for minimizing the sum of a strictly convex function and a convex piecewise linear function. It extends several dual coordinate ascent methods for large-scale linearly constrained problems that occur in entropy maximization, quadratic programming, and network flows. In particular, it may solve exact penalty versions of such (possibly inconsistent) problems, and subproblems of bundle methods for nondifferentiable optimization. It is simple, can exploit sparsity, and in certain cases is highly parallelizable. Its global convergence is established in the recent framework of B -functions (generalized Bregman functions)
Cost Effectiveness of Iran National Plasma Contract Fractionation Program
Directory of Open Access Journals (Sweden)
Abdol Majid Cheraghali
2012-10-01
Full Text Available Plasma derived medicines (PDM including immunoglobulins, clotting factors and albumin are life saving medicines which due to their high costs are inaccessible for many patients living in developing countries. By contrary substantial volume of plasma as raw materials for production of these medicines are discarded worldwide. Good quality recovered plasma, as a result of separation of donated blood into its components, could be used for production of PDM. In 2011 Iranian donors donated about 2 million units of blood. A shift fromadministration of whole blood to components therapy has resulted in the generation of over 250,000 liters of surplus of recovered plasma. This created a good opportunity for Iran’s health care system to use this plasma for production of PDM. Therefore Iran national transfusion service has started a contract fractionation program for converting recovered plasma into PDM. This program not only provided essential PDM for Iran pharmaceutical market but also has created a direct saving of about 8.5 million Euros in 2011 for national health sector. In addition this program has drastically contributed to improvement of overall quality of working procedures and services provided by Iran national blood transfusion organization.
A LINEAR PROGRAMMING ALGORITHM FOR LEAST-COST SCHEDULING
Directory of Open Access Journals (Sweden)
AYMAN H AL-MOMANI
1999-12-01
Full Text Available In this research, some concepts of linear programming and critical path method are reviewed to describe recent modeling structures that have been of great value in analyzing extended planning horizon project time-cost trade-offs problems. A simplified representation of a small project and a linear programming model is formulated to represent this system. Procedures to solve these various problems formulations were cited and the final solution is obtained using LINDO program. The model developed represents many restrictions and management considerations of the project. It could be used by construction managers in a planning stage to explore numerous possible opportunities to the contractor and predict the effect of a decision on the construction to facilitate a preferred operating policy given different management objectives. An implementation using this method is shown to outperform several other techniques and a large class of test problems. Linear programming show that the algorithm is very promising in practice on a wide variety of time-cost trade-offs problems. This method is simple, applicable to a large network, and generates a shorter computational time at low cost, along with an increase in robustness.
No-signaling quantum key distribution: solution by linear programming
Hwang, Won-Young; Bae, Joonwoo; Killoran, Nathan
2015-02-01
We outline a straightforward approach for obtaining a secret key rate using only no-signaling constraints and linear programming. Assuming an individual attack, we consider all possible joint probabilities. Initially, we study only the case where Eve has binary outcomes, and we impose constraints due to the no-signaling principle and given measurement outcomes. Within the remaining space of joint probabilities, by using linear programming, we get bound on the probability of Eve correctly guessing Bob's bit. We then make use of an inequality that relates this guessing probability to the mutual information between Bob and a more general Eve, who is not binary-restricted. Putting our computed bound together with the Csiszár-Körner formula, we obtain a positive key generation rate. The optimal value of this rate agrees with known results, but was calculated in a more straightforward way, offering the potential of generalization to different scenarios.
Planning under uncertainty solving large-scale stochastic linear programs
Energy Technology Data Exchange (ETDEWEB)
Infanger, G. [Stanford Univ., CA (United States). Dept. of Operations Research]|[Technische Univ., Vienna (Austria). Inst. fuer Energiewirtschaft
1992-12-01
For many practical problems, solutions obtained from deterministic models are unsatisfactory because they fail to hedge against certain contingencies that may occur in the future. Stochastic models address this shortcoming, but up to recently seemed to be intractable due to their size. Recent advances both in solution algorithms and in computer technology now allow us to solve important and general classes of practical stochastic problems. We show how large-scale stochastic linear programs can be efficiently solved by combining classical decomposition and Monte Carlo (importance) sampling techniques. We discuss the methodology for solving two-stage stochastic linear programs with recourse, present numerical results of large problems with numerous stochastic parameters, show how to efficiently implement the methodology on a parallel multi-computer and derive the theory for solving a general class of multi-stage problems with dependency of the stochastic parameters within a stage and between different stages.
Optimal selection for shielding materials by fuzzy linear programming
International Nuclear Information System (INIS)
Kanai, Y.; Miura, N.; Sugasawa, S.
1996-01-01
An application of fuzzy linear programming methods to optimization of a radiation shield is presented. The main purpose of the present study is the choice of materials and the search of the ratio of mixture-component as the first stage of the methodology on optimum shielding design according to individual requirements of nuclear reactor, reprocessing facility, shipping cask installing spent fuel, ect. The characteristic values for the shield optimization may be considered their cost, spatial space, weight and some shielding qualities such as activation rate and total dose rate for neutron and gamma ray (includes secondary gamma ray). This new approach can reduce huge combination calculations for conventional two-valued logic approaches to representative single shielding calculation by group-wised optimization parameters determined in advance. Using the fuzzy linear programming method, possibilities for reducing radiation effects attainable in optimal compositions hydrated, lead- and boron-contained materials are investigated
Refining and end use study of coal liquids II - linear programming analysis
Energy Technology Data Exchange (ETDEWEB)
Lowe, C.; Tam, S.
1995-12-31
A DOE-funded study is underway to determine the optimum refinery processing schemes for producing transportation fuels that will meet CAAA regulations from direct and indirect coal liquids. The study consists of three major parts: pilot plant testing of critical upgrading processes, linear programming analysis of different processing schemes, and engine emission testing of final products. Currently, fractions of a direct coal liquid produced form bituminous coal are being tested in sequence of pilot plant upgrading processes. This work is discussed in a separate paper. The linear programming model, which is the subject of this paper, has been completed for the petroleum refinery and is being modified to handle coal liquids based on the pilot plant test results. Preliminary coal liquid evaluation studies indicate that, if a refinery expansion scenario is adopted, then the marginal value of the coal liquid (over the base petroleum crude) is $3-4/bbl.
Algorithmic Trading with Developmental and Linear Genetic Programming
Wilson, Garnett; Banzhaf, Wolfgang
A developmental co-evolutionary genetic programming approach (PAM DGP) and a standard linear genetic programming (LGP) stock trading systemare applied to a number of stocks across market sectors. Both GP techniques were found to be robust to market fluctuations and reactive to opportunities associated with stock price rise and fall, with PAMDGP generating notably greater profit in some stock trend scenarios. Both algorithms were very accurate at buying to achieve profit and selling to protect assets, while exhibiting bothmoderate trading activity and the ability to maximize or minimize investment as appropriate. The content of the trading rules produced by both algorithms are also examined in relation to stock price trend scenarios.
Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution
Energy Technology Data Exchange (ETDEWEB)
Hamadameen, Abdulqader Othman [Optimization, Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia); Zainuddin, Zaitul Marlizawati [Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia)
2014-06-19
This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.
MAGDM linear-programming models with distinct uncertain preference structures.
Xu, Zeshui S; Chen, Jian
2008-10-01
Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.
An algorithm for the solution of dynamic linear programs
Psiaki, Mark L.
1989-01-01
The algorithm's objective is to efficiently solve Dynamic Linear Programs (DLP) by taking advantage of their special staircase structure. This algorithm constitutes a stepping stone to an improved algorithm for solving Dynamic Quadratic Programs, which, in turn, would make the nonlinear programming method of Successive Quadratic Programs more practical for solving trajectory optimization problems. The ultimate goal is to being trajectory optimization solution speeds into the realm of real-time control. The algorithm exploits the staircase nature of the large constraint matrix of the equality-constrained DLPs encountered when solving inequality-constrained DLPs by an active set approach. A numerically-stable, staircase QL factorization of the staircase constraint matrix is carried out starting from its last rows and columns. The resulting recursion is like the time-varying Riccati equation from multi-stage LQR theory. The resulting factorization increases the efficiency of all of the typical LP solution operations over that of a dense matrix LP code. At the same time numerical stability is ensured. The algorithm also takes advantage of dynamic programming ideas about the cost-to-go by relaxing active pseudo constraints in a backwards sweeping process. This further decreases the cost per update of the LP rank-1 updating procedure, although it may result in more changes of the active set that if pseudo constraints were relaxed in a non-stagewise fashion. The usual stability of closed-loop Linear/Quadratic optimally-controlled systems, if it carries over to strictly linear cost functions, implies that the saving due to reduced factor update effort may outweigh the cost of an increased number of updates. An aerospace example is presented in which a ground-to-ground rocket's distance is maximized. This example demonstrates the applicability of this class of algorithms to aerospace guidance. It also sheds light on the efficacy of the proposed pseudo constraint relaxation
Matzke, Orville R.
The purpose of this study was to formulate a linear programming model to simulate a foundation type support program and to apply this model to a state support program for the public elementary and secondary school districts in the State of Iowa. The model was successful in producing optimal solutions to five objective functions proposed for…
A Primal-Dual Interior Point-Linear Programming Algorithm for MPC
DEFF Research Database (Denmark)
Edlund, Kristian; Sokoler, Leo Emil; Jørgensen, John Bagterp
2009-01-01
Constrained optimal control problems for linear systems with linear constraints and an objective function consisting of linear and l1-norm terms can be expressed as linear programs. We develop an efficient primal-dual interior point algorithm for solution of such linear programs. The algorithm...
Optimal traffic control in highway transportation networks using linear programming
Li, Yanning
2014-06-01
This article presents a framework for the optimal control of boundary flows on transportation networks. The state of the system is modeled by a first order scalar conservation law (Lighthill-Whitham-Richards PDE). Based on an equivalent formulation of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can be extended to an arbitrary transportation network, preserving linear constraints. Unlike previously investigated transportation network control schemes, this framework leverages the intrinsic properties of the Halmilton-Jacobi equation, and does not require any discretization or boolean variables on the link. Hence this framework is very computational efficient and provides the globally optimal solution. The feasibility of this framework is illustrated by an on-ramp metering control example.
A recurrent neural network for solving bilevel linear programming problem.
He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie; Huang, Junjian
2014-04-01
In this brief, based on the method of penalty functions, a recurrent neural network (NN) modeled by means of a differential inclusion is proposed for solving the bilevel linear programming problem (BLPP). Compared with the existing NNs for BLPP, the model has the least number of state variables and simple structure. Using nonsmooth analysis, the theory of differential inclusions, and Lyapunov-like method, the equilibrium point sequence of the proposed NNs can approximately converge to an optimal solution of BLPP under certain conditions. Finally, the numerical simulations of a supply chain distribution model have shown excellent performance of the proposed recurrent NNs.
A scalable parallel algorithm for multiple objective linear programs
Wiecek, Malgorzata M.; Zhang, Hong
1994-01-01
This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.
The MARX Modulator Development Program for the International Linear Collider
International Nuclear Information System (INIS)
Leyh, G.E.
2006-01-01
The International Linear Collider (ILC) Marx Modulator Development Program at SLAC is working towards developing a full-scale ILC Marx ''Reference Design'' modulator prototype, with the goal of significantly reducing the size and cost of the ILC modulator while improving overall modulator efficiency and availability. The ILC Reference Design prototype will provide a proof-of-concept model to industry in advance of Phase II SBIR funding, and also allow operation of the new 10MW L-Band Klystron prototypes immediately upon their arrival at SLAC
Marginal cost of electricity conservation: an application of linear program
International Nuclear Information System (INIS)
Silveira, A.M. da; Hollanda, J.B. de
1987-01-01
This paper is addressed ti the planning of electricity industry when the use of energetically efficient appliances (conservation) is financed by the utilities. It is based on the Linear Programming Model proposed by Masse and Boiteaux for planning of conventional energy sources, where one unity of electricity (Kw/Kw h) saved is treated as if it were a generator of equivalent size. In spite of the formal simplicity of the models it can support interesting concessions on the subject of a electrical energy conservation policy. (author)
Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems
Directory of Open Access Journals (Sweden)
Xinbo Zhang
2014-01-01
Full Text Available A polymorphic uncertain linear programming (PULP model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems.
Directory of Open Access Journals (Sweden)
Iman Ghasemi
2017-05-01
Full Text Available In this paper, iterative learning control (ILC is combined with an optimal fractional order derivative (BBO-Da-type ILC and optimal fractional and proportional-derivative (BBO-PDa-type ILC. In the update law of Arimoto's derivative iterative learning control, a first order derivative of tracking error signal is used. In the proposed method, fractional order derivative of the error signal is stated in term of 'sa' where to update iterative learning control law. Two types of fractional order iterative learning control namely PDa-type ILC and Da-type ILC are gained for different value of a. In order to improve the performance of closed-loop control system, coefficients of both and learning law i.e. proportional , derivative and are optimized using Biogeography-Based optimization algorithm (BBO. Outcome of the simulation results are compared with those of the conventional fractional order iterative learning control to verify effectiveness of BBO-Da-type ILC and BBO-PDa-type ILC
AN APPLICATION FOR EFFICIENT TELECOMMUNICATION NETWORKS PROVISIONING USING LINEAR PROGRAMMING
Directory of Open Access Journals (Sweden)
Maria Augusta Soares Machado
2015-03-01
Full Text Available This paper presents a practical proposition for the application of the Linear Programming quantitative method in order to assist planning and control of customer circuit delivery activities in telecommunications companies working with the corporative market. Based upon data provided for by a telecom company operating in Brazil, the Linear Programming method was employed for one of the classical problems of determining the optimum mix of production quantities for a set of five products of that company: Private Telephone Network, Internet Network, Intranet Network, Low Speed Data Network, and High Speed Data Network, in face of several limitations of the productive resources, seeking to maximize the company’s monthly revenue. By fitting the production data available into a primary model, observation was made as to what number of monthly activations for each product would be mostly optimized in order to achieve maximum revenues in the company. The final delivery of a complete network was not observed but the delivery of the circuits that make it up, and this was a limiting factor for the study herein, which, however, brings an innovative proposition for the planning of private telecommunications network provisioning.
Assembling networks of microbial genomes using linear programming.
Holloway, Catherine; Beiko, Robert G
2010-11-20
Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem. We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas. The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.
Linear programming based on neural networks for radiotherapy treatment planning
International Nuclear Information System (INIS)
Xingen Wu; Limin Luo
2000-01-01
In this paper, we propose a neural network model for linear programming that is designed to optimize radiotherapy treatment planning (RTP). This kind of neural network can be easily implemented by using a kind of 'neural' electronic system in order to obtain an optimization solution in real time. We first give an introduction to the RTP problem and construct a non-constraint objective function for the neural network model. We adopt a gradient algorithm to minimize the objective function and design the structure of the neural network for RTP. Compared to traditional linear programming methods, this neural network model can reduce the time needed for convergence, the size of problems (i.e., the number of variables to be searched) and the number of extra slack and surplus variables needed. We obtained a set of optimized beam weights that result in a better dose distribution as compared to that obtained using the simplex algorithm under the same initial condition. The example presented in this paper shows that this model is feasible in three-dimensional RTP. (author)
A Study of Joint Cost Inclusion in Linear Programming Optimization
Directory of Open Access Journals (Sweden)
P. Armaos
2013-08-01
Full Text Available The concept of Structural Optimization has been a topic or research over the past century. Linear Programming Optimization has proved being the most reliable method of structural optimization. Global advances in linear programming optimization have been recently powered by University of Sheffield researchers, to include joint cost, self-weight and buckling considerations. A joint cost inclusion scopes to reduce the number of joints existing in an optimized structural solution, transforming it to a practically viable solution. The topic of the current paper is to investigate the effects of joint cost inclusion, as this is currently implemented in the optimization code. An extended literature review on this subject was conducted prior to familiarization with small scale optimization software. Using IntelliFORM software, a structured series of problems were set and analyzed. The joint cost tests examined benchmark problems and their consequent changes in the member topology, as the design domain was expanding. The findings of the analyses were remarkable and are being commented further on. The distinct topologies of solutions created by optimization processes are also recognized. Finally an alternative strategy of penalizing joints is presented.
How to Use Linear Programming for Information System Performances Optimization
Directory of Open Access Journals (Sweden)
Hell Marko
2014-09-01
Full Text Available Background: Organisations nowadays operate in a very dynamic environment, and therefore, their ability of continuously adjusting the strategic plan to the new conditions is a must for achieving their strategic objectives. BSC is a well-known methodology for measuring performances enabling organizations to learn how well they are doing. In this paper, “BSC for IS” will be proposed in order to measure the IS impact on the achievement of organizations’ business goals. Objectives: The objective of this paper is to present the original procedure which is used to enhance the BSC methodology in planning the optimal targets of IS performances value in order to maximize the organization's effectiveness. Methods/Approach: The method used in this paper is the quantitative methodology - linear programming. In the case study, linear programming is used for optimizing organization’s strategic performance. Results: Results are shown on the example of a case study national park. An optimal performance value for the strategic objective has been calculated, as well as an optimal performance value for each DO (derived objective. Results are calculated in Excel, using Solver Add-in. Conclusions: The presentation of methodology through the case study of a national park shows that this methodology, though it requires a high level of formalisation, provides a very transparent performance calculation.
Laxy, Michael; Stark, Renée; Peters, Annette; Hauner, Hans; Holle, Rolf; Teuner, Christina M
2017-08-30
This study aims to analyse the non-linear relationship between Body Mass Index (BMI) and direct health care costs, and to quantify the resulting cost fraction attributable to obesity in Germany. Five cross-sectional surveys of cohort studies in southern Germany were pooled, resulting in data of 6757 individuals (31-96 years old). Self-reported information on health care utilisation was used to estimate direct health care costs for the year 2011. The relationship between measured BMI and annual costs was analysed using generalised additive models, and the cost fraction attributable to obesity was calculated. We found a non-linear association of BMI and health care costs with a continuously increasing slope for increasing BMI without any clear threshold. Under the consideration of the non-linear BMI-cost relationship, a shift in the BMI distribution so that the BMI of each individual is lowered by one point is associated with a 2.1% reduction of mean direct costs in the population. If obesity was eliminated, and the BMI of all obese individuals were lowered to 29.9 kg/m², this would reduce the mean direct costs by 4.0% in the population. Results show a non-linear relationship between BMI and health care costs, with very high costs for a few individuals with high BMI. This indicates that population-based interventions in combination with selective measures for very obese individuals might be the preferred strategy.
Performance of a fully automated program for measurement of left ventricular ejection fraction
International Nuclear Information System (INIS)
Douglass, K.H.; Tibbits, P.; Kasecamp, W.; Han, S.T.; Koller, D.; Links, J.M.; Wagner, H.H. Jr.
1982-01-01
A fully automated program developed by us for measurement of left ventricular ejection fraction from equilibrium gated blood studies was evaluated in 130 additional patients. Both of 6-min (130 studies) and 2-min (142 studies in 31 patients) gated blood pool studies were acquired and processed. The program successfully generated ejection fractions in 86% of the studies. These automatically generated ejection fractions were compared with ejection fractions derived from manually drawn regions the interest. When studies were acquired for 6-min with the patient at rest, the correlation between automated and manual ejection fractions was 0.92. When studies were acquired for 2-min, both at rest and during bicycle exercise, the correlation was 0.81. In 25 studies from patients who also underwent contrast ventriculography, the program successfully generated regions of interest in 22 (88%). The correlation between the ejection fraction determined by contrast ventriculography and the automatically generated radionuclide ejection fraction was 0.79. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Regis, J.-M., E-mail: regis@ikp.uni-koeln.de [Institut fuer Kernphysik der Universitaet zu Koeln, Zuelpicher Str. 77, 50937 Koeln (Germany); Rudigier, M.; Jolie, J.; Blazhev, A.; Fransen, C.; Pascovici, G.; Warr, N. [Institut fuer Kernphysik der Universitaet zu Koeln, Zuelpicher Str. 77, 50937 Koeln (Germany)
2012-08-21
The electronic {gamma}-{gamma} fast timing technique allows for direct nuclear lifetime determination down to the few picoseconds region by measuring the time difference between two coincident {gamma}-ray transitions. Using high resolution ultra-fast LaBr{sub 3}(Ce) scintillator detectors in combination with the recently developed mirror symmetric centroid difference method, nuclear lifetimes are measured with a time resolving power of around 5 ps. The essence of the method is to calibrate the energy dependent position (centroid) of the prompt response function of the setup which is obtained for simultaneously occurring events. This time-walk of the prompt response function induced by the analog constant fraction discriminator has been determined by systematic measurements using different photomultiplier tubes and timing adjustments of the constant fraction discriminator. We propose a universal calibration function which describes the time-walk or the combined {gamma}-{gamma} time-walk characteristics, respectively, for either a linear or a non-linear amplitude versus energy dependency of the scintillator detector output pulses.
Aether: leveraging linear programming for optimal cloud computing in genomics.
Luber, Jacob M; Tierney, Braden T; Cofer, Evan M; Patel, Chirag J; Kostic, Aleksandar D
2018-05-01
Across biology, we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective and scalable framework that uses linear programming to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis and provides an easy transition from users' existing HPC pipelines. Data utilized are available at https://pubs.broadinstitute.org/diabimmune and with EBI SRA accession ERP005989. Source code is available at (https://github.com/kosticlab/aether). Examples, documentation and a tutorial are available at http://aether.kosticlab.org. chirag_patel@hms.harvard.edu or aleksandar.kostic@joslin.harvard.edu. Supplementary data are available at Bioinformatics online.
Linear programming phase unwrapping for dual-wavelength digital holography.
Wang, Zhaomin; Jiao, Jiannan; Qu, Weijuan; Yang, Fang; Li, Hongru; Tian, Ailing; Asundi, Anand
2017-01-20
A linear programming phase unwrapping method in dual-wavelength digital holography is proposed and verified experimentally. The proposed method uses the square of height difference as a convergence standard and theoretically gives the boundary condition in a searching process. A simulation was performed by unwrapping step structures at different levels of Gaussian noise. As a result, our method is capable of recovering the discontinuities accurately. It is robust and straightforward. In the experiment, a microelectromechanical systems sample and a cylindrical lens were measured separately. The testing results were in good agreement with true values. Moreover, the proposed method is applicable not only in digital holography but also in other dual-wavelength interferometric techniques.
Microgrid Reliability Modeling and Battery Scheduling Using Stochastic Linear Programming
Energy Technology Data Exchange (ETDEWEB)
Cardoso, Goncalo; Stadler, Michael; Siddiqui, Afzal; Marnay, Chris; DeForest, Nicholas; Barbosa-Povoa, Ana; Ferrao, Paulo
2013-05-23
This paper describes the introduction of stochastic linear programming into Operations DER-CAM, a tool used to obtain optimal operating schedules for a given microgrid under local economic and environmental conditions. This application follows previous work on optimal scheduling of a lithium-iron-phosphate battery given the output uncertainty of a 1 MW molten carbonate fuel cell. Both are in the Santa Rita Jail microgrid, located in Dublin, California. This fuel cell has proven unreliable, partially justifying the consideration of storage options. Several stochastic DER-CAM runs are executed to compare different scenarios to values obtained by a deterministic approach. Results indicate that using a stochastic approach provides a conservative yet more lucrative battery schedule. Lower expected energy bills result, given fuel cell outages, in potential savings exceeding 6percent.
CONTRIBUTION OF A LINEAR PROGRAMMING VBA MODULE TO STUDENTS PEFORMANCE
Directory of Open Access Journals (Sweden)
KUČÍRKOVÁ Lenka
2010-12-01
Full Text Available This paper deals with the application of freeware modules as a teaching support of Operations Research methods at the Department of Systems Engineering, Czech university of Life Sciences (CULS Prague. In particular, we concentrated on a linear programming module and measured the impact on student performance. The motivation for this evaluation is based on a current development of a new module that focuses on Traveling Salesman Problem. First, we explain the current situation both worldwide and in the Czech Republic and the CULS Prague. Subsequently, we describe the content of students’ exams and statistical methods applied to the evaluation. Finally, we analyze and generalize the obtained results. The students exams have show a positive impact of the modules. Further, our analysis has proven that this impact is statistically significant. The findings motivate us to made new modules for other methods.
Local beam angle optimization with linear programming and gradient search
International Nuclear Information System (INIS)
Craft, David
2007-01-01
The optimization of beam angles in IMRT planning is still an open problem, with literature focusing on heuristic strategies and exhaustive searches on discrete angle grids. We show how a beam angle set can be locally refined in a continuous manner using gradient-based optimization in the beam angle space. The gradient is derived using linear programming duality theory. Applying this local search to 100 random initial angle sets of a phantom pancreatic case demonstrates the method, and highlights the many-local-minima aspect of the BAO problem. Due to this function structure, we recommend a search strategy of a thorough global search followed by local refinement at promising beam angle sets. Extensions to nonlinear IMRT formulations are discussed. (note)
Towards lexicographic multi-objective linear programming using grossone methodology
Cococcioni, Marco; Pappalardo, Massimo; Sergeyev, Yaroslav D.
2016-10-01
Lexicographic Multi-Objective Linear Programming (LMOLP) problems can be solved in two ways: preemptive and nonpreemptive. The preemptive approach requires the solution of a series of LP problems, with changing constraints (each time the next objective is added, a new constraint appears). The nonpreemptive approach is based on a scalarization of the multiple objectives into a single-objective linear function by a weighted combination of the given objectives. It requires the specification of a set of weights, which is not straightforward and can be time consuming. In this work we present both mathematical and software ingredients necessary to solve LMOLP problems using a recently introduced computational methodology (allowing one to work numerically with infinities and infinitesimals) based on the concept of grossone. The ultimate goal of such an attempt is an implementation of a simplex-like algorithm, able to solve the original LMOLP problem by solving only one single-objective problem and without the need to specify finite weights. The expected advantages are therefore obvious.
C-program LINOP for the evaluation of film dosemeters by linear optimization. User manual
International Nuclear Information System (INIS)
Kragh, P.
1995-11-01
Linear programming results in an optimal measuring value for film dosemeters. The Linop program was developed to be used for linear programming. The program permits the evaluation and control of film dosemeters and of all other multi-component dosemeters. This user manual for the Linop program contains the source program, a description of the program and installation and use instructions. The data sets with programs and examples are available upon request. (orig.) [de
Zhang, Lifu; Li, Chuxin; Zhong, Haizhe; Xu, Changwen; Lei, Dajun; Li, Ying; Fan, Dianyuan
2016-06-27
We have investigated the propagation dynamics of super-Gaussian optical beams in fractional Schrödinger equation. We have identified the difference between the propagation dynamics of super-Gaussian beams and that of Gaussian beams. We show that, the linear propagation dynamics of the super-Gaussian beams with order m > 1 undergo an initial compression phase before they split into two sub-beams. The sub-beams with saddle shape separate each other and their interval increases linearly with propagation distance. In the nonlinear regime, the super-Gaussian beams evolve to become a single soliton, breathing soliton or soliton pair depending on the order of super-Gaussian beams, nonlinearity, as well as the Lévy index. In two dimensions, the linear evolution of super-Gaussian beams is similar to that for one dimension case, but the initial compression of the input super-Gaussian beams and the diffraction of the splitting beams are much stronger than that for one dimension case. While the nonlinear propagation of the super-Gaussian beams becomes much more unstable compared with that for the case of one dimension. Our results show the nonlinear effects can be tuned by varying the Lévy index in the fractional Schrödinger equation for a fixed input power.
Lachhwani, Kailash; Poonia, Mahaveer Prasad
2012-08-01
In this paper, we show a procedure for solving multilevel fractional programming problems in a large hierarchical decentralized organization using fuzzy goal programming approach. In the proposed method, the tolerance membership functions for the fuzzily described numerator and denominator part of the objective functions of all levels as well as the control vectors of the higher level decision makers are respectively defined by determining individual optimal solutions of each of the level decision makers. A possible relaxation of the higher level decision is considered for avoiding decision deadlock due to the conflicting nature of objective functions. Then, fuzzy goal programming approach is used for achieving the highest degree of each of the membership goal by minimizing negative deviational variables. We also provide sensitivity analysis with variation of tolerance values on decision vectors to show how the solution is sensitive to the change of tolerance values with the help of a numerical example.
Split diversity in constrained conservation prioritization using integer linear programming.
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.
A linear programming approach for placement of applicants to academic programs
Kassa, Biniyam Asmare
2013-01-01
This paper reports a linear programming approach for placement of applicants to study programs developed and implemented at the college of Business & Economics, Bahir Dar University, Bahir Dar, Ethiopia. The approach is estimated to significantly streamline the placement decision process at the college by reducing required man hour as well as the time it takes to announce placement decisions. Compared to the previous manual system where only one or two placement criteria were considered, the ...
DEFF Research Database (Denmark)
Le, T.H.A.; Pham, D. T.; Canh, Nam Nguyen
2010-01-01
Both the efficient and weakly efficient sets of an affine fractional vector optimization problem, in general, are neither convex nor given explicitly. Optimization problems over one of these sets are thus nonconvex. We propose two methods for optimizing a real-valued function over the efficient...... and weakly efficient sets of an affine fractional vector optimization problem. The first method is a local one. By using a regularization function, we reformulate the problem into a standard smooth mathematical programming problem that allows applying available methods for smooth programming. In case...... the objective function is linear, we have investigated a global algorithm based upon a branch-and-bound procedure. The algorithm uses Lagrangian bound coupling with a simplicial bisection in the criteria space. Preliminary computational results show that the global algorithm is promising....
An overview of solution methods for multi-objective mixed integer linear programming programs
DEFF Research Database (Denmark)
Andersen, Kim Allan; Stidsen, Thomas Riis
Multiple objective mixed integer linear programming (MOMIP) problems are notoriously hard to solve to optimality, i.e. finding the complete set of non-dominated solutions. We will give an overview of existing methods. Among those are interactive methods, the two phases method and enumeration...... methods. In particular we will discuss the existing branch and bound approaches for solving multiple objective integer programming problems. Despite the fact that branch and bound methods has been applied successfully to integer programming problems with one criterion only a few attempts has been made...
Approximate labeling via graph cuts based on linear programming.
Komodakis, Nikos; Tziritas, Georgios
2007-08-01
A new framework is presented for both understanding and developing graph-cut-based combinatorial algorithms suitable for the approximate optimization of a very wide class of Markov Random Fields (MRFs) that are frequently encountered in computer vision. The proposed framework utilizes tools from the duality theory of linear programming in order to provide an alternative and more general view of state-of-the-art techniques like the \\alpha-expansion algorithm, which is included merely as a special case. Moreover, contrary to \\alpha-expansion, the derived algorithms generate solutions with guaranteed optimality properties for a much wider class of problems, for example, even for MRFs with nonmetric potentials. In addition, they are capable of providing per-instance suboptimality bounds in all occasions, including discrete MRFs with an arbitrary potential function. These bounds prove to be very tight in practice (that is, very close to 1), which means that the resulting solutions are almost optimal. Our algorithms' effectiveness is demonstrated by presenting experimental results on a variety of low-level vision tasks, such as stereo matching, image restoration, image completion, and optical flow estimation, as well as on synthetic problems.
Flow discharge prediction in compound channels using linear genetic programming
Azamathulla, H. Md.; Zahiri, A.
2012-08-01
SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.
Periodic inventory system in cafeteria using linear programming
Usop, Mohd Fais; Ishak, Ruzana; Hamdan, Ahmad Ridhuan
2017-11-01
Inventory management is an important factor in running a business. It plays a big role of managing the stock in cafeteria. If the inventories are failed to be managed wisely, it will affect the profit of the cafeteria. Therefore, the purpose of this study is to find the solution of the inventory management in cafeteria. Most of the cafeteria in Malaysia did not manage their stock well. Therefore, this study is to propose a database system of inventory management and to develop the inventory model in cafeteria management. In this study, new database system to improve the management of the stock in a weekly basis will be provided using Linear Programming Model to get the optimal range of the inventory needed for selected categories. Data that were collected by using the Periodic Inventory System at the end of the week within three months period being analyzed by using the Food Stock-take Database. The inventory model was developed from the collected data according to the category of the inventory in the cafeteria. Results showed the effectiveness of using the Periodic Inventory System and will be very helpful to the cafeteria management in organizing the inventory. Moreover, the findings in this study can reduce the cost of operation and increased the profit.
Learning oncogenetic networks by reducing to mixed integer linear programming.
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.
Near-Regular Structure Discovery Using Linear Programming
Huang, Qixing
2014-06-02
Near-regular structures are common in manmade and natural objects. Algorithmic detection of such regularity greatly facilitates our understanding of shape structures, leads to compact encoding of input geometries, and enables efficient generation and manipulation of complex patterns on both acquired and synthesized objects. Such regularity manifests itself both in the repetition of certain geometric elements, as well as in the structured arrangement of the elements. We cast the regularity detection problem as an optimization and efficiently solve it using linear programming techniques. Our optimization has a discrete aspect, that is, the connectivity relationships among the elements, as well as a continuous aspect, namely the locations of the elements of interest. Both these aspects are captured by our near-regular structure extraction framework, which alternates between discrete and continuous optimizations. We demonstrate the effectiveness of our framework on a variety of problems including near-regular structure extraction, structure-preserving pattern manipulation, and markerless correspondence detection. Robustness results with respect to geometric and topological noise are presented on synthesized, real-world, and also benchmark datasets. © 2014 ACM.
Maximum likelihood pedigree reconstruction using integer linear programming.
Cussens, James; Bartlett, Mark; Jones, Elinor M; Sheehan, Nuala A
2013-01-01
Large population biobanks of unrelated individuals have been highly successful in detecting common genetic variants affecting diseases of public health concern. However, they lack the statistical power to detect more modest gene-gene and gene-environment interaction effects or the effects of rare variants for which related individuals are ideally required. In reality, most large population studies will undoubtedly contain sets of undeclared relatives, or pedigrees. Although a crude measure of relatedness might sometimes suffice, having a good estimate of the true pedigree would be much more informative if this could be obtained efficiently. Relatives are more likely to share longer haplotypes around disease susceptibility loci and are hence biologically more informative for rare variants than unrelated cases and controls. Distant relatives are arguably more useful for detecting variants with small effects because they are less likely to share masking environmental effects. Moreover, the identification of relatives enables appropriate adjustments of statistical analyses that typically assume unrelatedness. We propose to exploit an integer linear programming optimisation approach to pedigree learning, which is adapted to find valid pedigrees by imposing appropriate constraints. Our method is not restricted to small pedigrees and is guaranteed to return a maximum likelihood pedigree. With additional constraints, we can also search for multiple high-probability pedigrees and thus account for the inherent uncertainty in any particular pedigree reconstruction. The true pedigree is found very quickly by comparison with other methods when all individuals are observed. Extensions to more complex problems seem feasible. © 2012 Wiley Periodicals, Inc.
Discovery of Boolean metabolic networks: integer linear programming based approach.
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 ".
Storage and distribution/Linear programming for storage operations
Energy Technology Data Exchange (ETDEWEB)
Coleman, D
1978-07-15
The techniques of linear programing to solve storage problems as applied in a tank farm tie-in with refinery throughput operation include: (1) the time-phased model which works on storage and refinery operations input parameters, e.g., production, distribution, cracking, etc., and is capable of representing product stockpiling in slack periods to meet future peak demands, and investigating alternative strategies such as exchange deals and purchase and leasing of additional storage, and (2) the Monte Carlo simulation method, which inputs parameters, e.g., arrival of crude products at refinery, tankage size, likely demand for products, etc., as probability distributions rather than single values, and is capable of showing the average utilization of facilities, potential bottlenecks, investment required to achieve an increase in utilization, and to enable the user to predict total investment, cash flow, and profit emanating from the original financing decision. The increasing use of computer techniques to solve refinery and storage problems is attributed to potential savings resulting from more effective planning, reduced computer costs, ease of access and more usable software. Diagrams.
Mixed integer linear programming for maximum-parsimony phylogeny inference.
Sridhar, Srinath; Lam, Fumei; Blelloch, Guy E; Ravi, R; Schwartz, Russell
2008-01-01
Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new advances in phylogeny inference will be required if we are to be able to continue to make effective use of the rapidly growing stores of variation data now being gathered. In this paper, we present two integer linear programming (ILP) formulations to find the most parsimonious phylogenetic tree from a set of binary variation data. One method uses a flow-based formulation that can produce exponential numbers of variables and constraints in the worst case. The method has, however, proven extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods, solving several large mtDNA and Y-chromosome instances within a few seconds and giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality. An alternative formulation establishes that the problem can be solved with a polynomial-sized ILP. We further present a web server developed based on the exponential-sized ILP that performs fast maximum parsimony inferences and serves as a front end to a database of precomputed phylogenies spanning the human genome.
Fitting boxes to Manhattan scenes using linear integer programming
Li, Minglei
2016-02-19
We propose an approach for automatic generation of building models by assembling a set of boxes using a Manhattan-world assumption. The method first aligns the point cloud with a per-building local coordinate system, and then fits axis-aligned planes to the point cloud through an iterative regularization process. The refined planes partition the space of the data into a series of compact cubic cells (candidate boxes) spanning the entire 3D space of the input data. We then choose to approximate the target building by the assembly of a subset of these candidate boxes using a binary linear programming formulation. The objective function is designed to maximize the point cloud coverage and the compactness of the final model. Finally, all selected boxes are merged into a lightweight polygonal mesh model, which is suitable for interactive visualization of large scale urban scenes. Experimental results and a comparison with state-of-the-art methods demonstrate the effectiveness of the proposed framework.
Chen, Ruoying; Zhang, Zhiwang; Wu, Di; Zhang, Peng; Zhang, Xinyang; Wang, Yong; Shi, Yong
2011-01-21
Protein-protein interactions are fundamentally important in many biological processes and it is in pressing need to understand the principles of protein-protein interactions. Mutagenesis studies have found that only a small fraction of surface residues, known as hot spots, are responsible for the physical binding in protein complexes. However, revealing hot spots by mutagenesis experiments are usually time consuming and expensive. In order to complement the experimental efforts, we propose a new computational approach in this paper to predict hot spots. Our method, Rough Set-based Multiple Criteria Linear Programming (RS-MCLP), integrates rough sets theory and multiple criteria linear programming to choose dominant features and computationally predict hot spots. Our approach is benchmarked by a dataset of 904 alanine-mutated residues and the results show that our RS-MCLP method performs better than other methods, e.g., MCLP, Decision Tree, Bayes Net, and the existing HotSprint database. In addition, we reveal several biological insights based on our analysis. We find that four features (the change of accessible surface area, percentage of the change of accessible surface area, size of a residue, and atomic contacts) are critical in predicting hot spots. Furthermore, we find that three residues (Tyr, Trp, and Phe) are abundant in hot spots through analyzing the distribution of amino acids. Copyright © 2010 Elsevier Ltd. All rights reserved.
Mixed integer (0-1) fractional programming for decision support in paper production industry
Claassen, G.D.H.
2014-01-01
This paper presents an effective and efficient method for solving a special class of mixed integer fractional programming (FP) problems. We take a classical reformulation approach for continuous FP as a starting point and extend it for solving a more general class of mixed integer (0–1) fractional
Li, Meng; Gu, Xian-Ming; Huang, Chengming; Fei, Mingfa; Zhang, Guoyu
2018-04-01
In this paper, a fast linearized conservative finite element method is studied for solving the strongly coupled nonlinear fractional Schrödinger equations. We prove that the scheme preserves both the mass and energy, which are defined by virtue of some recursion relationships. Using the Sobolev inequalities and then employing the mathematical induction, the discrete scheme is proved to be unconditionally convergent in the sense of L2-norm and H α / 2-norm, which means that there are no any constraints on the grid ratios. Then, the prior bound of the discrete solution in L2-norm and L∞-norm are also obtained. Moreover, we propose an iterative algorithm, by which the coefficient matrix is independent of the time level, and thus it leads to Toeplitz-like linear systems that can be efficiently solved by Krylov subspace solvers with circulant preconditioners. This method can reduce the memory requirement of the proposed linearized finite element scheme from O (M2) to O (M) and the computational complexity from O (M3) to O (Mlog M) in each iterative step, where M is the number of grid nodes. Finally, numerical results are carried out to verify the correction of the theoretical analysis, simulate the collision of two solitary waves, and show the utility of the fast numerical solution techniques.
Pilkey, W. D.; Chen, Y. H.
1974-01-01
An indirect synthesis method is used in the efficient optimal design of multi-degree of freedom, multi-design element, nonlinear, transient systems. A limiting performance analysis which requires linear programming for a kinematically linear system is presented. The system is selected using system identification methods such that the designed system responds as closely as possible to the limiting performance. The efficiency is a result of the method avoiding the repetitive systems analyses accompanying other numerical optimization methods.
NP-Hardness of optimizing the sum of Rational Linear Functions over an Asymptotic-Linear-Program
Chermakani, Deepak Ponvel
2012-01-01
We convert, within polynomial-time and sequential processing, an NP-Complete Problem into a real-variable problem of minimizing a sum of Rational Linear Functions constrained by an Asymptotic-Linear-Program. The coefficients and constants in the real-variable problem are 0, 1, -1, K, or -K, where K is the time parameter that tends to positive infinity. The number of variables, constraints, and rational linear functions in the objective, of the real-variable problem is bounded by a polynomial ...
Linear programming model can explain respiration of fermentation products
Möller, Philip; Liu, Xiaochen; Schuster, Stefan
2018-01-01
Many differentiated cells rely primarily on mitochondrial oxidative phosphorylation for generating energy in the form of ATP needed for cellular metabolism. In contrast most tumor cells instead rely on aerobic glycolysis leading to lactate to about the same extent as on respiration. Warburg found that cancer cells to support oxidative phosphorylation, tend to ferment glucose or other energy source into lactate even in the presence of sufficient oxygen, which is an inefficient way to generate ATP. This effect also occurs in striated muscle cells, activated lymphocytes and microglia, endothelial cells and several mammalian cell types, a phenomenon termed the “Warburg effect”. The effect is paradoxical at first glance because the ATP production rate of aerobic glycolysis is much slower than that of respiration and the energy demands are better to be met by pure oxidative phosphorylation. We tackle this question by building a minimal model including three combined reactions. The new aspect in extension to earlier models is that we take into account the possible uptake and oxidation of the fermentation products. We examine the case where the cell can allocate protein on several enzymes in a varying distribution and model this by a linear programming problem in which the objective is to maximize the ATP production rate under different combinations of constraints on enzymes. Depending on the cost of reactions and limitation of the substrates, this leads to pure respiration, pure fermentation, and a mixture of respiration and fermentation. The model predicts that fermentation products are only oxidized when glucose is scarce or its uptake is severely limited. PMID:29415045
Optimizing Biorefinery Design and Operations via Linear Programming Models
Energy Technology Data Exchange (ETDEWEB)
Talmadge, Michael; Batan, Liaw; Lamers, Patrick; Hartley, Damon; Biddy, Mary; Tao, Ling; Tan, Eric
2017-03-28
The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LP models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for
Linear programming model can explain respiration of fermentation products.
Möller, Philip; Liu, Xiaochen; Schuster, Stefan; Boley, Daniel
2018-01-01
Many differentiated cells rely primarily on mitochondrial oxidative phosphorylation for generating energy in the form of ATP needed for cellular metabolism. In contrast most tumor cells instead rely on aerobic glycolysis leading to lactate to about the same extent as on respiration. Warburg found that cancer cells to support oxidative phosphorylation, tend to ferment glucose or other energy source into lactate even in the presence of sufficient oxygen, which is an inefficient way to generate ATP. This effect also occurs in striated muscle cells, activated lymphocytes and microglia, endothelial cells and several mammalian cell types, a phenomenon termed the "Warburg effect". The effect is paradoxical at first glance because the ATP production rate of aerobic glycolysis is much slower than that of respiration and the energy demands are better to be met by pure oxidative phosphorylation. We tackle this question by building a minimal model including three combined reactions. The new aspect in extension to earlier models is that we take into account the possible uptake and oxidation of the fermentation products. We examine the case where the cell can allocate protein on several enzymes in a varying distribution and model this by a linear programming problem in which the objective is to maximize the ATP production rate under different combinations of constraints on enzymes. Depending on the cost of reactions and limitation of the substrates, this leads to pure respiration, pure fermentation, and a mixture of respiration and fermentation. The model predicts that fermentation products are only oxidized when glucose is scarce or its uptake is severely limited.
Very Low-Cost Nutritious Diet Plans Designed by Linear Programming.
Foytik, Jerry
1981-01-01
Provides procedural details of Linear Programing, developed by the U.S. Department of Agriculture to devise a dietary guide for consumers that minimizes food costs without sacrificing nutritional quality. Compares Linear Programming with the Thrifty Food Plan, which has been a basis for allocating coupons under the Food Stamp Program. (CS)
Designing fractional factorial split-plot experiments using integer programming
DEFF Research Database (Denmark)
Capehart, Shay R.; Keha, Ahmet; Kulahci, Murat
2011-01-01
factorial (FF) design, with the restricted randomisation structure to account for the whole plots and subplots. We discuss the formulation of FFSP designs using integer programming (IP) to achieve various design criteria. We specifically look at the maximum number of clear two-factor interactions...
Wilson, Peter J; Williams, Janet R; Smee, Robert I
2014-09-01
Nelson's syndrome is a unique clinical phenomenon of growth of a pituitary adenoma following bilateral adrenalectomies for the control of Cushing's disease. Primary management is surgical, with limited effective medical therapies available. We report our own institution's series of this pathology managed with radiation: prior to 1990, 12 patients were managed with conventional radiotherapy, and between 1990 and 2007, five patients underwent stereotactic radiosurgery (SRS) and two patients fractionated stereotactic radiotherapy (FSRT), both using the linear accelerator (LINAC). Tumour control was equivocal, with two of the five SRS patients having a reduction in tumour volume, one patient remaining unchanged, and two patients having an increase in volume. In the FSRT group, one patient had a decrease in tumour volume whilst the other had an increase in volume. Treatment related morbidity was low. Nelson's syndrome is a challenging clinical scenario, with a highly variable response to radiation in our series. Copyright © 2014 Elsevier Ltd. All rights reserved.
Wilson, P J; Williams, J R; Smee, R I
2014-01-01
Cushing's disease is hypercortisolaemia secondary to an adrenocorticotrophic hormone secreting pituitary adenoma. Primary management is almost always surgical, with limited effective medical interventions available. Adjuvant therapy in the form of radiation is gaining popularity, with the bulk of the literature related to the Gamma Knife. We present the results from our own institution using the linear accelerator (LINAC) since 1990. Thirty-six patients who underwent stereotactic radiosurgery (SRS), one patient who underwent fractionated stereotactic radiotherapy (FSRT) and for the purposes of comparison, 13 patients who had undergone conventional radiotherapy prior to 1990, were included in the analysis. Serum cortisol levels improved in nine of 36 (25%) SRS patients and 24 hour urinary free cortisol levels improved in 13 of 36 patients (36.1%). Tumour volume control was excellent in the SRS group with deterioration in only one patient (3%). The patient who underwent FSRT had a highly aggressive tumour refractory to radiation. Published by Elsevier Ltd.
SECPOP90: Sector population, land fraction, and economic estimation program
Energy Technology Data Exchange (ETDEWEB)
Humphreys, S.L.; Rollstin, J.A.; Ridgely, J.N.
1997-09-01
In 1973 Mr. W. Athey of the Environmental Protection Agency wrote a computer program called SECPOP which calculated population estimates. Since that time, two things have changed which suggested the need for updating the original program - more recent population censuses and the widespread use of personal computers (PCs). The revised computer program uses the 1990 and 1992 Population Census information and runs on current PCs as {open_quotes}SECPOP90.{close_quotes} SECPOP90 consists of two parts: site and regional. The site provides population and economic data estimates for any location within the continental United States. Siting analysis is relatively fast running. The regional portion assesses site availability for different siting policy decisions; i.e., the impact of available sites given specific population density criteria within the continental United States. Regional analysis is slow. This report compares the SECPOP90 population estimates and the nuclear power reactor licensee-provided information. Although the source, and therefore the accuracy, of the licensee information is unknown, this comparison suggests SECPOP90 makes reasonable estimates. Given the total uncertainty in any current calculation of severe accidents, including the potential offsite consequences, the uncertainty within SECPOP90 population estimates is expected to be insignificant. 12 refs., 55 figs., 7 tabs.
SECPOP90: Sector population, land fraction, and economic estimation program
International Nuclear Information System (INIS)
Humphreys, S.L.; Rollstin, J.A.; Ridgely, J.N.
1997-09-01
In 1973 Mr. W. Athey of the Environmental Protection Agency wrote a computer program called SECPOP which calculated population estimates. Since that time, two things have changed which suggested the need for updating the original program - more recent population censuses and the widespread use of personal computers (PCs). The revised computer program uses the 1990 and 1992 Population Census information and runs on current PCs as open-quotes SECPOP90.close quotes SECPOP90 consists of two parts: site and regional. The site provides population and economic data estimates for any location within the continental United States. Siting analysis is relatively fast running. The regional portion assesses site availability for different siting policy decisions; i.e., the impact of available sites given specific population density criteria within the continental United States. Regional analysis is slow. This report compares the SECPOP90 population estimates and the nuclear power reactor licensee-provided information. Although the source, and therefore the accuracy, of the licensee information is unknown, this comparison suggests SECPOP90 makes reasonable estimates. Given the total uncertainty in any current calculation of severe accidents, including the potential offsite consequences, the uncertainty within SECPOP90 population estimates is expected to be insignificant. 12 refs., 55 figs., 7 tabs
Frost, Susan A.; Bodson, Marc; Acosta, Diana M.
2009-01-01
The Next Generation (NextGen) transport aircraft configurations being investigated as part of the NASA Aeronautics Subsonic Fixed Wing Project have more control surfaces, or control effectors, than existing transport aircraft configurations. Conventional flight control is achieved through two symmetric elevators, two antisymmetric ailerons, and a rudder. The five effectors, reduced to three command variables, produce moments along the three main axes of the aircraft and enable the pilot to control the attitude and flight path of the aircraft. The NextGen aircraft will have additional redundant control effectors to control the three moments, creating a situation where the aircraft is over-actuated and where a simple relationship does not exist anymore between the required effector deflections and the desired moments. NextGen flight controllers will incorporate control allocation algorithms to determine the optimal effector commands and attain the desired moments, taking into account the effector limits. Approaches to solving the problem using linear programming and quadratic programming algorithms have been proposed and tested. It is of great interest to understand their relative advantages and disadvantages and how design parameters may affect their properties. In this paper, we investigate the sensitivity of the effector commands with respect to the desired moments and show on some examples that the solutions provided using the l2 norm of quadratic programming are less sensitive than those using the l1 norm of linear programming.
Financial Planning with Fractional Goals
Goedhart, Marc; Spronk, Jaap
1995-01-01
textabstractWhen solving financial planning problems with multiple goals by means of multiple objective programming, the presence of fractional goals leads to technical difficulties. In this paper we present a straightforward interactive approach for solving such linear fractional programs with multiple goal variables. The approach is illustrated by means of an example in financial planning.
International Nuclear Information System (INIS)
Bayati, Mohsen; Borgs, Christian; Chayes, Jennifer; Zecchina, Riccardo
2008-01-01
We consider the general problem of finding the minimum weight b-matching on arbitrary graphs. We prove that, whenever the linear programing relaxation of the problem has no fractional solutions, then the cavity or belief propagation equations converge to the correct solution both for synchronous and asynchronous updating. (letter)
Fleming, P.
1985-01-01
A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a non-linear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer-aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer.
Sensitivity analysis of linear programming problem through a recurrent neural network
Das, Raja
2017-11-01
In this paper we study the recurrent neural network for solving linear programming problems. To achieve optimality in accuracy and also in computational effort, an algorithm is presented. We investigate the sensitivity analysis of linear programming problem through the neural network. A detailed example is also presented to demonstrate the performance of the recurrent neural network.
Schmitt, M. A.; And Others
1994-01-01
Compares traditional manure application planning techniques calculated to meet agronomic nutrient needs on a field-by-field basis with plans developed using computer-assisted linear programming optimization methods. Linear programming provided the most economical and environmentally sound manure application strategy. (Contains 15 references.) (MDH)
Fundamental solution of the problem of linear programming and method of its determination
Petrunin, S. V.
1978-01-01
The idea of a fundamental solution to a problem in linear programming is introduced. A method of determining the fundamental solution and of applying this method to the solution of a problem in linear programming is proposed. Numerical examples are cited.
DEFF Research Database (Denmark)
Ren, Jingzheng; Dong, Liang; Sun, Lu
2015-01-01
in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed...
The essential multiobjectivity of linear programming | Stewart | ORiON
African Journals Online (AJOL)
It is argued that any non-trivial real world problems involve multiple objectives. The simplistic approach of combining objectives in linear form can generate highly misleading and biased results, and is poor operational research practice. Such biases are illustrated by means of a simple example, and it is demonstrated that ...
International Nuclear Information System (INIS)
Cullen, D.E.
1979-01-01
Program LINEAR converts evaluated cross sections in the ENDF/B format into a tabular form that is subject to linear-linear interpolation in energy and cross section. The code also thins tables of cross sections already in that form (i.e., removes points not needed for linear interpolability). The main advantage of the code is that it allows subsequent codes to consider only linear-linear data. A listing of the source deck is available on request
Effective radiological safety program for electron linear accelerators
International Nuclear Information System (INIS)
Swanson, W.P.
1980-10-01
An outline is presented of some of the main elements of an electron accelerator radiological safety program. The discussion includes types of accelerator facilities, types of radiations to be anticipated, activity induced in components, air and water, and production of toxic gases. Concepts of radiation shielding design are briefly discussed and organizational aspects are considered as an integral part of the overall safety program
Portfolio optimization by using linear programing models based on genetic algorithm
Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.
2018-01-01
In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.
Zhao, Yingfeng; Liu, Sanyang
2016-01-01
We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.
Mixed-Integer Conic Linear Programming: Challenges and Perspectives
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
Rui, Yichao; Murphy, Daniel V; Wang, Xiaoli; Hoyle, Frances C
2016-10-18
Rebuilding 'lost' soil carbon (C) is a priority in mitigating climate change and underpinning key soil functions that support ecosystem services. Microorganisms determine if fresh C input is converted into stable soil organic matter (SOM) or lost as CO 2 . Here we quantified if microbial biomass and respiration responded positively to addition of light fraction organic matter (LFOM, representing recent inputs of plant residue) in an infertile semi-arid agricultural soil. Field trial soil with different historical plant residue inputs [soil C content: control (tilled) = 9.6 t C ha -1 versus tilled + plant residue treatment (tilled + OM) = 18.0 t C ha -1 ] were incubated in the laboratory with a gradient of LFOM equivalent to 0 to 3.8 t C ha -1 (0 to 500% LFOM). Microbial biomass C significantly declined under increased rates of LFOM addition while microbial respiration increased linearly, leading to a decrease in the microbial C use efficiency. We hypothesise this was due to insufficient nutrients to form new microbial biomass as LFOM input increased the ratio of C to nitrogen, phosphorus and sulphur of soil. Increased CO 2 efflux but constrained microbial growth in response to LFOM input demonstrated the difficulty for C storage in this environment.
International Nuclear Information System (INIS)
Zavaljevski, N.
1985-01-01
Proposed optimization procedure is fast due to application of linear programming. Non-linear constraints which demand iterative application of linear programming are slowing down the calculation. Linearization can be done by different procedures starting from simple empirical rules for fuel in-core management to complicated general perturbation theory with higher order of corrections. A mathematical model was formulated for optimization of improved fuel cycle. A detailed algorithm for determining minimum of fresh fuel at the beginning of each fuel cycle is shown and the problem is linearized by first order perturbation theory and it is optimized by linear programming. Numerical illustration of the proposed method was done for the experimental reactor mostly for saving computer time
A linear programming approach for placement of applicants to academic programs.
Kassa, Biniyam Asmare
2013-01-01
This paper reports a linear programming approach for placement of applicants to study programs developed and implemented at the college of Business & Economics, Bahir Dar University, Bahir Dar, Ethiopia. The approach is estimated to significantly streamline the placement decision process at the college by reducing required man hour as well as the time it takes to announce placement decisions. Compared to the previous manual system where only one or two placement criteria were considered, the new approach allows the college's management to easily incorporate additional placement criteria, if needed. Comparison of our approach against manually constructed placement decisions based on actual data for the 2012/13 academic year suggested that about 93 percent of the placements from our model concur with the actual placement decisions. For the remaining 7 percent of placements, however, the actual placements made by the manual system display inconsistencies of decisions judged against the very criteria intended to guide placement decisions by the college's program management office. Overall, the new approach proves to be a significant improvement over the manual system in terms of efficiency of the placement process and the quality of placement decisions.
Bruhn, Peter; Geyer-Schulz, Andreas
2002-01-01
In this paper, we introduce genetic programming over context-free languages with linear constraints for combinatorial optimization, apply this method to several variants of the multidimensional knapsack problem, and discuss its performance relative to Michalewicz's genetic algorithm with penalty functions. With respect to Michalewicz's approach, we demonstrate that genetic programming over context-free languages with linear constraints improves convergence. A final result is that genetic programming over context-free languages with linear constraints is ideally suited to modeling complementarities between items in a knapsack problem: The more complementarities in the problem, the stronger the performance in comparison to its competitors.
International Nuclear Information System (INIS)
Hutchinson, W.
1983-04-01
The report takes the form of a user guide to a computer program using linear programming techniques to aid the assignment and scheduling of radioactive wastes for disposal to sea. The program is aimed at the identification of 'optimum' amounts of each waste stream for disposal to sea without violating specific constraints values and/or fairness parameters. (author)
Wilson, Peter J; Williams, Janet Rosemary; Smee, Robert Ian
2015-06-01
Primary management of prolactinomas is usually medical, with surgery a secondary option where necessary. This study is a review of a single centre's experience with focused radiotherapy where benefit was not gained by medical or surgical approaches. Radiotherapy as an alternative and adjuvant treatment for prolactinomas has been performed at our institution with the linear accelerator since 1990. We present a retrospective review of 13 patients managed with stereotactic radiosurgery (SRS) and 5 managed with fractionated stereotactic radiotherapy (FSRT), as well as 5 managed with conventional radiotherapy, at the Prince of Wales Hospital. Patients with a histopathologically diagnosed prolactinoma were eligible. Those patients who had a confirmed pathological diagnosis of prolactinoma following surgical intervention, a prolactin level elevated above 500 μg/L, or a prolactin level persistently elevated above 200 μg/L with exclusion of other causes were represented in this review. At the end of documented follow-up (SRS median 6 years, FSRT median 2 years), no SRS patients showed an increase in tumour volume. After FSRT, 1 patient showed an increase in size, 2 showed a decrease in size and 2 patients showed no change. Prolactin levels trended towards improvement after SRS and FSRT, but no patients achieved the remission level of <20 μg/L. Seven of 13 patients in the SRS group achieved a level of <500 μg/L, whereas no patients reached this target after FSRT. A reduction in prolactin level is frequent after SRS and FSRT for prolactinomas; however, true biochemical remission is uncommon. Tumour volume control in this series was excellent, but this may be related to the natural history of the disease. Morbidity and mortality after stereotactic radiation were very low in this series. © 2014 The Royal Australian and New Zealand College of Radiologists.
Van-Quynh, Alexandra; Blanchart, Philippe; Battu, Serge; Clédat, Dominique; Cardot, Philippe
2006-03-03
Sedimentation field flow fractionation was used to obtain purified fractions from a polydispersed zirconia colloidal suspension in the potential purpose of optical material hybrid coating. The zirconia particle size ranged from 50/70 nm to 1000 nm. It exhibited a log-Gaussian particle size distribution (in mass or volume) and a 115% polydispersity index (P.I.). Time dependent eluted fractions of the original zirconia colloidal suspension were collected. The particle size distribution of each fraction was determined with scanning electron microscopy and Coulter sub-micron particle sizer (CSPS). These orthogonal techniques generated similar data. From fraction average elution times and granulometry measurements, it was shown that zirconia colloids are eluted according to the Brownian elution mode. The four collected fractions have a Gaussian like distribution and respective average size and polydispersity index of 153 nm (P.I. = 34.7%); 188 nm (P.I. = 27.9%); 228 nm (P.I. = 22.6%), and 276 nm (P.I. = 22.3%). These data demonstrate the strong size selectivity of SdFFF operated with programmed field of exponential profile for sorting particles in the sub-micron range. Using this technique, the analytical production of zirconia of given average size and reduced polydispersity is possible.
adapta~k>n -11 of the surrogate memods for linear programming ...
African Journals Online (AJOL)
2005-08-02
Aug 2, 2005 ... inequality problem is made uj~ of the primal and dual optimal solutions for the given primal ... KEYWORDS: Linear Programming, Duality Theory, Surrogate Methods. ..... replaces x and the process IS repeated with the new x.
Development of demand functions and their inclusion in linear programming forecasting models
International Nuclear Information System (INIS)
Chamberlin, J.H.
1976-05-01
The purpose of the paper is to present a method for including demand directly within a linear programming model, and to use this method to analyze the effect of the Liquid Metal Fast Breeder Reactor upon the nuclear energy system
An introduction to fuzzy linear programming problems theory, methods and applications
Kaur, Jagdeep
2016-01-01
The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.
Fuzzy Multi Objective Linear Programming Problem with Imprecise Aspiration Level and Parameters
Directory of Open Access Journals (Sweden)
Zahra Shahraki
2015-07-01
Full Text Available This paper considers the multi-objective linear programming problems with fuzzygoal for each of the objective functions and constraints. Most existing works deal withlinear membership functions for fuzzy goals. In this paper, exponential membershipfunction is used.
International Nuclear Information System (INIS)
Ureba, A.; Palma, B. A.; Leal, A.
2011-01-01
Develop a more efficient method of optimization in relation to time, based on linear programming designed to implement a multi objective penalty function which also permits a simultaneous solution integrated boost situations considering two white volumes simultaneously.
Energy Technology Data Exchange (ETDEWEB)
Hong, Linda X.; Garg, Madhur; Lasala, Patrick; Kim, Mimi; Mah, Dennis; Chen, Chin-Cheng; Yaparpalvi, Ravindra; Mynampati, Dinesh; Kuo, Hsiang-Chi; Guha, Chandan; Kalnicki, Shalom [Department of Radiation Oncology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, New York 10461 (United States); Department of Neurosurgery, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, New York 10461 (United States); Department of Epidemiology and Population Health, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, New York 10461 (United States); Department of Radiation Oncology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, New York 10461 (United States)
2011-03-15
Purpose: Sharp dose fall off outside a tumor is essential for high dose single fraction stereotactic radiosurgery (SRS) plans. This study explores the relationship among tumor dose inhomogeneity, conformity, and dose fall off in normal tissues for micromultileaf collimator (mMLC) linear accelerator (LINAC) based cranial SRS plans. Methods: Between January 2007 and July 2009, 65 patients with single cranial lesions were treated with LINAC-based SRS. Among them, tumors had maximum diameters {<=}20 mm: 31; between 20 and 30 mm: 21; and >30 mm: 13. All patients were treated with 6 MV photons on a Trilogy linear accelerator (Varian Medical Systems, Palo Alto, CA) with a tertiary m3 high-resolution mMLC (Brainlab, Feldkirchen, Germany), using either noncoplanar conformal fixed fields or dynamic conformal arcs. The authors also created retrospective study plans with identical beam arrangement as the treated plan but with different tumor dose inhomogeneity by varying the beam margins around the planning target volume (PTV). All retrospective study plans were normalized so that the minimum PTV dose was the prescription dose (PD). Isocenter dose, mean PTV dose, RTOG conformity index (CI), RTOG homogeneity index (HI), dose gradient index R{sub 50}-R{sub 100} (defined as the difference between equivalent sphere radius of 50% isodose volume and prescription isodose volume), and normal tissue volume (as a ratio to PTV volume) receiving 50% prescription dose (NTV{sub 50}) were calculated. Results: HI was inversely related to the beam margins around the PTV. CI had a ''V'' shaped relationship with HI, reaching a minimum when HI was approximately 1.3. Isocenter dose and mean PTV dose (as percentage of PD) increased linearly with HI. R{sub 50}-R{sub 100} and NTV{sub 50} initially declined with HI and then reached a plateau when HI was approximately 1.3. These trends also held when tumors were grouped according to their maximum diameters. The smallest tumor group
Portfolio selection problem: a comparison of fuzzy goal programming and linear physical programming
Directory of Open Access Journals (Sweden)
Fusun Kucukbay
2016-04-01
Full Text Available Investors have limited budget and they try to maximize their return with minimum risk. Therefore this study aims to deal with the portfolio selection problem. In the study two criteria are considered which are expected return, and risk. In this respect, linear physical programming (LPP technique is applied on Bist 100 stocks to be able to find out the optimum portfolio. The analysis covers the period April 2009- March 2015. This period is divided into two; April 2009-March 2014 and April 2014 – March 2015. April 2009-March 2014 period is used as data to find an optimal solution. April 2014-March 2015 period is used to test the real performance of portfolios. The performance of the obtained portfolio is compared with that obtained from fuzzy goal programming (FGP. Then the performances of both method, LPP and FGP are compared with BIST 100 in terms of their Sharpe Indexes. The findings reveal that LPP for portfolio selection problem is a good alternative to FGP.
Arc-Search Infeasible Interior-Point Algorithm for Linear Programming
Yang, Yaguang
2014-01-01
Mehrotra's algorithm has been the most successful infeasible interior-point algorithm for linear programming since 1990. Most popular interior-point software packages for linear programming are based on Mehrotra's algorithm. This paper proposes an alternative algorithm, arc-search infeasible interior-point algorithm. We will demonstrate, by testing Netlib problems and comparing the test results obtained by arc-search infeasible interior-point algorithm and Mehrotra's algorithm, that the propo...
Diet models with linear goal programming: impact of achievement functions.
Gerdessen, J C; de Vries, J H M
2015-11-01
Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints. Results derived from GP models are usually very sensitive to the type of achievement function that is chosen.This paper aims to provide a methodological insight into several achievement functions. It describes the extended GP (EGP) achievement function, which enables the decision maker to use either a MinSum achievement function (which minimizes the sum of the unwanted deviations) or a MinMax achievement function (which minimizes the largest unwanted deviation), or a compromise between both. An additional advantage of EGP models is that from one set of data and weights multiple solutions can be obtained. We use small numerical examples to illustrate the 'mechanics' of achievement functions. Then, the EGP achievement function is demonstrated on a diet problem with 144 foods, 19 nutrients and several types of palatability constraints, in which the nutritional constraints are modeled with fuzzy sets. Choice of achievement function affects the results of diet models. MinSum achievement functions can give rise to solutions that are sensitive to weight changes, and that pile all unwanted deviations on a limited number of nutritional constraints. MinMax achievement functions spread the unwanted deviations as evenly as possible, but may create many (small) deviations. EGP comprises both types of achievement functions, as well as compromises between them. It can thus, from one data set, find a range of solutions with various properties.
Multi-Objective Fuzzy Linear Programming In Agricultural Production Planning
Directory of Open Access Journals (Sweden)
H.M.I.U. Herath
2015-08-01
Full Text Available Abstract Modern agriculture is characterized by a series of conflicting optimization criteria that obstruct the decision-making process in the planning of agricultural production. Such criteria are usually net profit total cost total production etc. At the same time the decision making process in the agricultural production planning is often conducted with data that accidentally occur in nature or that are fuzzy not deterministic. Such data are the yields of various crops the prices of products and raw materials demand for the product the available quantities of production factors such as water labor etc. In this paper a fuzzy multi-criteria mathematical programming model is presented. This model is applied in a region of 10 districts in Sri Lanka where paddy is cultivated under irrigated and rain fed water in the two main seasons called Yala and Maha and the optimal production plan is achieved. This study was undertaken to find out the optimal allocation of land for paddy to get a better yield while satisfying the two conflicting objectives profit maximizing and cost minimizing subjected to the utilizing of water constraint and the demand constraint. Only the availability of land constraint is considered as a crisp in nature while objectives and other constraints are treated as fuzzy. It is observed that the MOFLP is an effective method to handle more than a single objective occurs in an uncertain vague environment.
Stamova, Ivanka; Stamov, Gani
2017-12-01
In this paper, we propose a fractional-order neural network system with time-varying delays and reaction-diffusion terms. We first develop a new Mittag-Leffler synchronization strategy for the controlled nodes via impulsive controllers. Using the fractional Lyapunov method sufficient conditions are given. We also study the global Mittag-Leffler synchronization of two identical fractional impulsive reaction-diffusion neural networks using linear controllers, which was an open problem even for integer-order models. Since the Mittag-Leffler stability notion is a generalization of the exponential stability concept for fractional-order systems, our results extend and improve the exponential impulsive control theory of neural network system with time-varying delays and reaction-diffusion terms to the fractional-order case. The fractional-order derivatives allow us to model the long-term memory in the neural networks, and thus the present research provides with a conceptually straightforward mathematical representation of rather complex processes. Illustrative examples are presented to show the validity of the obtained results. We show that by means of appropriate impulsive controllers we can realize the stability goal and to control the qualitative behavior of the states. An image encryption scheme is extended using fractional derivatives. Copyright © 2017 Elsevier Ltd. All rights reserved.
FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management.
Li, Pu; Chen, Bing
2011-04-01
Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk. Copyright © 2010 Elsevier Ltd. All rights reserved.
Study and program implementation of transient curves' piecewise linearization
International Nuclear Information System (INIS)
Shi Yang; Zu Hongbiao
2014-01-01
Background: Transient curves are essential for the stress analysis of related equipment in nuclear power plant (NPP). The actually operating data or the design transient data of a NPP usually consist of a large number of data points with very short time intervals. To simplify the analysis, transient curves are generally piecewise linearized in advance. Up to now, the piecewise linearization of transient curves is accomplished manually, Purpose: The aim is to develop a method for the piecewise linearization of transient curves, and to implement it by programming. Methods: First of all, the fitting line of a number of data points was obtained by the least square method. The segment of the fitting line is set while the accumulation error of linearization exceeds the preset limit with the increasing number of points. Then the linearization of subsequent data points was begun from the last point of the preceding curve segment to get the next segment in the same way, and continue until the final data point involved. Finally, averaging of junction points is taken for the segment connection. Results: A computer program named PLTC (Piecewise Linearization for Transient Curves) was implemented and verified by the linearization of the standard sine curve and typical transient curves of a NPP. Conclusion: The method and the PLTC program can be well used to the piecewise linearization of transient curves, with improving efficiency and precision. (authors)
A Nutritional Analysis of the Food Basket in BIH: A Linear Programming Approach
Directory of Open Access Journals (Sweden)
Arnaut-Berilo Almira
2017-04-01
Full Text Available This paper presents linear and goal programming optimization models for determining and analyzing the food basket in Bosnia and Herzegovina (BiH in terms of adequate nutritional needs according to World Health Organization (WHO standards and World Bank (WB recommendations. A linear programming (LP model and goal linear programming model (GLP are adequate since price and nutrient contents are linearly related to food weight. The LP model provides information about the minimal value and the structure of the food basket for an average person in BiH based on nutrient needs. GLP models are designed to give us information on minimal deviations from nutrient needs if the budget is fixed. Based on these results, poverty analysis can be performed. The data used for the models consisted of 158 food items from the general consumption of the population of BiH according to COICOP classifications, with average prices in 2015 for these products.
The Computer Program LIAR for Beam Dynamics Calculations in Linear Accelerators
International Nuclear Information System (INIS)
Assmann, R.W.; Adolphsen, C.; Bane, K.; Raubenheimer, T.O.; Siemann, R.H.; Thompson, K.
2011-01-01
Linear accelerators are the central components of the proposed next generation of linear colliders. They need to provide acceleration of up to 750 GeV per beam while maintaining very small normalized emittances. Standard simulation programs, mainly developed for storage rings, do not meet the specific requirements for high energy linear accelerators. We present a new program LIAR ('LInear Accelerator Research code') that includes wakefield effects, a 6D coupled beam description, specific optimization algorithms and other advanced features. Its modular structure allows to use and to extend it easily for different purposes. The program is available for UNIX workstations and Windows PC's. It can be applied to a broad range of accelerators. We present examples of simulations for SLC and NLC.
Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing.
Yang, Changju; Kim, Hyongsuk
2016-08-19
A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model.
Directory of Open Access Journals (Sweden)
Ram Verma
2016-02-01
Full Text Available This paper deals with mainly establishing numerous sets of generalized second order paramertic sufficient optimality conditions for a semiinfinite discrete minmax fractional programming problem, while the results on semiinfinite discrete minmax fractional programming problem achieved based on some partitioning schemes under various types of generalized second order univexity assumptions.
Micosoft Excel Sensitivity Analysis for Linear and Stochastic Program Feed Formulation
Sensitivity analysis is a part of mathematical programming solutions and is used in making nutritional and economic decisions for a given feed formulation problem. The terms, shadow price and reduced cost, are familiar linear program (LP) terms to feed formulators. Because of the nonlinear nature of...
International Workshop on “Generalized Concavity, Fractional Programming and Economic Applications”
Castagnoli, Erio; Martein, Laura; Mazzoleni, Piera; Schaible, Siegfried
1990-01-01
Generalizations of convex functions have been used in a variety of fields such as economics. business administration. engineering. statistics and applied sciences.· In 1949 de Finetti introduced one of the fundamental of generalized convex functions characterized by convex level sets which are now known as quasiconvex functions. Since then numerous types of generalized convex functions have been defined in accordance with the need of particular applications.· In each case such functions preserve soine of the valuable properties of a convex function. In addition to generalized convex functions this volume deals with fractional programs. These are constrained optimization problems which in the objective function involve one or several ratios. Such functions are often generalized convex. Fractional programs arise in management science. economics and numerical mathematics for example. In order to promote the circulation and development of research in this field. an international workshop on "Generalized Concavi...
International program on linear electric motors. CIGGT report No. 92-1
Energy Technology Data Exchange (ETDEWEB)
Dawson, G.E.; Eastham, A.R.; Parker, J.H.
1992-12-31
The International Program for Linear Electric Motors (LEM) was begun in April 1989 to communicate and coordinate activities with centers of expertise in Germany, Canada, and Japan; to provide for the assessment and support of the planning of technological developments and for dissemination of information to researchers, service operators, and policy makers; and to ensure that full advantage can be taken if opportunities for technology transfer occur. This report documents the work done under the program, including standardizing linear induction motor (LIM) design characteristics; test procedures and measurement methods; rating; database for design data; criteria for evaluation of designs; computer programs for modelling performance; and a design study for an agreed application.
Object matching using a locally affine invariant and linear programming techniques.
Li, Hongsheng; Huang, Xiaolei; He, Lei
2013-02-01
In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm.
Development and adjustment of programs for solving systems of linear equations
International Nuclear Information System (INIS)
Fujimura, Toichiro
1978-03-01
Programs for solving the systems of linear equations have been adjusted and developed in expanding the scientific subroutine library SSL. The principal programs adjusted are based on the congruent method, method of product form of the inverse, orthogonal method, Crout's method for sparse system, and acceleration of iterative methods. The programs developed are based on the escalator method, direct parallel residue method and block tridiagonal method for band system. Described are usage of the programs developed and their future improvement. FORTRAN lists with simple examples in tests of the programs are also given. (auth.)
Directory of Open Access Journals (Sweden)
Animesh Biswas
2016-04-01
Full Text Available This paper deals with fuzzy goal programming approach to solve fuzzy linear bilevel integer programming problems with fuzzy probabilistic constraints following Pareto distribution and Frechet distribution. In the proposed approach a new chance constrained programming methodology is developed from the view point of managing those probabilistic constraints in a hybrid fuzzy environment. A method of defuzzification of fuzzy numbers using ?-cut has been adopted to reduce the problem into a linear bilevel integer programming problem. The individual optimal value of the objective of each DM is found in isolation to construct the fuzzy membership goals. Finally, fuzzy goal programming approach is used to achieve maximum degree of each of the membership goals by minimizing under deviational variables in the decision making environment. To demonstrate the efficiency of the proposed approach, a numerical example is provided.
DESIGN OF EDUCATIONAL PROBLEMS ON LINEAR PROGRAMMING USING SYSTEMS OF COMPUTER MATHEMATICS
Directory of Open Access Journals (Sweden)
Volodymyr M. Mykhalevych
2013-11-01
Full Text Available From a perspective of the theory of educational problems a problem of substitution in the conditions of ICT use of one discipline by an educational problem of another discipline is represented. Through the example of mathematical problems of linear programming it is showed that a student’s method of operation in the course of an educational problem solving is determinant in the identification of an educational problem in relation to a specific discipline: linear programming, informatics, mathematical modeling, methods of optimization, automatic control theory, calculus etc. It is substantiated the necessity of linear programming educational problems renovation with the purpose of making students free of bulky similar arithmetic calculations and notes which often becomes a barrier to a deeper understanding of key ideas taken as a basis of algorithms used by them.
Accommodation of practical constraints by a linear programming jet select. [for Space Shuttle
Bergmann, E.; Weiler, P.
1983-01-01
An experimental spacecraft control system will be incorporated into the Space Shuttle flight software and exercised during a forthcoming mission to evaluate its performance and handling qualities. The control system incorporates a 'phase space' control law to generate rate change requests and a linear programming jet select to compute jet firings. Posed as a linear programming problem, jet selection must represent the rate change request as a linear combination of jet acceleration vectors where the coefficients are the jet firing times, while minimizing the fuel expended in satisfying that request. This problem is solved in real time using a revised Simplex algorithm. In order to implement the jet selection algorithm in the Shuttle flight control computer, it was modified to accommodate certain practical features of the Shuttle such as limited computer throughput, lengthy firing times, and a large number of control jets. To the authors' knowledge, this is the first such application of linear programming. It was made possible by careful consideration of the jet selection problem in terms of the properties of linear programming and the Simplex algorithm. These modifications to the jet select algorithm may by useful for the design of reaction controlled spacecraft.
A computer program for two-particle generalized coefficients of fractional parentage
Deveikis, A.; Juodagalvis, A.
2008-10-01
We present a FORTRAN90 program GCFP for the calculation of the generalized coefficients of fractional parentage (generalized CFPs or GCFP). The approach is based on the observation that the multi-shell CFPs can be expressed in terms of single-shell CFPs, while the latter can be readily calculated employing a simple enumeration scheme of antisymmetric A-particle states and an efficient method of construction of the idempotent matrix eigenvectors. The program provides fast calculation of GCFPs for a given particle number and produces results possessing numerical uncertainties below the desired tolerance. A single j-shell is defined by four quantum numbers, (e,l,j,t). A supplemental C++ program parGCFP allows calculation to be done in batches and/or in parallel. Program summaryProgram title:GCFP, parGCFP Catalogue identifier: AEBI_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBI_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.: 17 199 No. of bytes in distributed program, including test data, etc.: 88 658 Distribution format: tar.gz Programming language: FORTRAN 77/90 ( GCFP), C++ ( parGCFP) Computer: Any computer with suitable compilers. The program GCFP requires a FORTRAN 77/90 compiler. The auxiliary program parGCFP requires GNU-C++ compatible compiler, while its parallel version additionally requires MPI-1 standard libraries Operating system: Linux (Ubuntu, Scientific) (all programs), also checked on Windows XP ( GCFP, serial version of parGCFP) RAM: The memory demand depends on the computation and output mode. If this mode is not 4, the program GCFP demands the following amounts of memory on a computer with Linux operating system. It requires around 2 MB of RAM for the A=12 system at E⩽2. Computation of the A=50 particle system requires around 60 MB of
Method for solving fully fuzzy linear programming problems using deviation degree measure
Institute of Scientific and Technical Information of China (English)
Haifang Cheng; Weilai Huang; Jianhu Cai
2013-01-01
A new ful y fuzzy linear programming (FFLP) prob-lem with fuzzy equality constraints is discussed. Using deviation degree measures, the FFLP problem is transformed into a crispδ-parametric linear programming (LP) problem. Giving the value of deviation degree in each constraint, the δ-fuzzy optimal so-lution of the FFLP problem can be obtained by solving this LP problem. An algorithm is also proposed to find a balance-fuzzy optimal solution between two goals in conflict: to improve the va-lues of the objective function and to decrease the values of the deviation degrees. A numerical example is solved to il ustrate the proposed method.
A novel recurrent neural network with finite-time convergence for linear programming.
Liu, Qingshan; Cao, Jinde; Chen, Guanrong
2010-11-01
In this letter, a novel recurrent neural network based on the gradient method is proposed for solving linear programming problems. Finite-time convergence of the proposed neural network is proved by using the Lyapunov method. Compared with the existing neural networks for linear programming, the proposed neural network is globally convergent to exact optimal solutions in finite time, which is remarkable and rare in the literature of neural networks for optimization. Some numerical examples are given to show the effectiveness and excellent performance of the new recurrent neural network.
Fault detection and initial state verification by linear programming for a class of Petri nets
Rachell, Traxon; Meyer, David G.
1992-01-01
The authors present an algorithmic approach to determining when the marking of a LSMG (live safe marked graph) or a LSFC (live safe free choice) net is in the set of live safe markings M. Hence, once the marking of a net is determined to be in M, then if at some time thereafter the marking of this net is determined not to be in M, this indicates a fault. It is shown how linear programming can be used to determine if m is an element of M. The worst-case computational complexity of each algorithm is bounded by the number of linear programs necessary to compute.
BEAMPATH: a program library for beam dynamics simulation in linear accelerators
International Nuclear Information System (INIS)
Batygin, Y.K.
1992-01-01
A structured programming technique was used to develop software for space charge dominated beams investigation in linear accelerators. The method includes hierarchical program design using program independent modules and a flexible combination of modules to provide a most effective version of structure for every specific case of simulation. A modular program BEAMPATH was developed for 2D and 3D particle-in-cell simulation of beam dynamics in a structure containing RF gaps, radio-frequency quadrupoles (RFQ), multipole lenses, waveguides, bending magnets and solenoids. (author) 5 refs.; 2 figs
International Nuclear Information System (INIS)
Reibel, R.R.; Barber, Z.W.; Fischer, J.A.; Tian, M.; Babbitt, W.R.
2004-01-01
Linear sideband chirped (LSC) programming is introduced as a means of configuring spatial-spectral holographic gratings for optical coherent transient processors. Similar to linear frequency chirped programming, LSC programming allows the use of broadband integrated electro-optic phase modulators to produce chirps instead of using elaborate broadband chirped lasers. This approach has several advantages including the ability to use a stabilized laser for the optical carrier as well as stable, reproducible chirped optical signals when the modulator is driven digitally. Using LSC programming, we experimentally demonstrate broadband true-time delay as a proof of principle for the optical control of phased array radars. Here both cw phase modulated and binary phase shift keyed probe signals are true-time delayed with bandwidths of 1 GHz and delay resolutions better than 60 ps
Directory of Open Access Journals (Sweden)
Chandra Nagasuma R
2009-02-01
Full Text Available Abstract Background A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN from transcript profiling data. Results The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting problem and solved finally by formulating a Linear Program (LP. A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known
A novel approach based on preference-based index for interval bilevel linear programming problem
Aihong Ren; Yuping Wang; Xingsi Xue
2017-01-01
This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrain...
Energy Technology Data Exchange (ETDEWEB)
Castillo, J.A.; Ramirez, J.R.; Alonso, G. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)]. e-mail: jacm@nuclear.inin.mx
2003-07-01
The linear reactivity model allows the multicycle analysis in pressurized water reactors in a simple and quick way. In the case of the Boiling water reactors the void fraction it varies axially from 0% of voids in the inferior part of the fuel assemblies until approximately 70% of voids to the exit of the same ones. Due to this it is very important the determination of the average void fraction during different stages of the reactor operation to predict the burnt one appropriately of the same ones to inclination of the pattern of linear reactivity. In this work a pursuit is made of the profile of power for different steps of burnt of a typical operation cycle of a Boiling water reactor. Starting from these profiles it builds an algorithm that allows to determine the voids profile and this way to obtain the average value of the same one. The results are compared against those reported by the CM-PRESTO code that uses another method to carry out this calculation. Finally, the range in which is the average value of the void fraction during a typical cycle is determined and an estimate of the impact that it would have the use of this value in the prediction of the reactivity produced by the fuel assemblies is made. (Author)
The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.
Pang, Haotian; Liu, Han; Vanderbei, Robert
2014-02-01
We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method called CLIME (Constrained L 1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems.
Mass Optimization of Battery/Supercapacitors Hybrid Systems Based on a Linear Programming Approach
Fleury, Benoit; Labbe, Julien
2014-08-01
The objective of this paper is to show that, on a specific launcher-type mission profile, a 40% gain of mass is expected using a battery/supercapacitors active hybridization instead of a single battery solution. This result is based on the use of a linear programming optimization approach to perform the mass optimization of the hybrid power supply solution.
Optimal local dimming for LED-backlit LCD displays via linear programming
DEFF Research Database (Denmark)
Shu, Xiao; Wu, Xiaolin; Forchhammer, Søren
2012-01-01
and the attenuations of LCD pixels. The objective is to minimize the distortion in luminance reproduction due to the leakage of LCD and the coarse granularity of the LED lights. The optimization problem is formulated as one of linear programming, and both exact and approximate algorithms are proposed. Simulation...
DEFF Research Database (Denmark)
Hernández, Adriana Carolina Luna; Aldana, Nelson Leonardo Diaz; Graells, Moises
2017-01-01
-side strategy, defined as a general mixed-integer linear programming by taking into account two stages for proper charging of the storage units. This model is considered as a deterministic problem that aims to minimize operating costs and promote self-consumption based on 24-hour ahead forecast data...
Linear Programming Approaches for Power Savings in Software-defined Networks
Moghaddam, F.A.; Grosso, P.
2016-01-01
Software-defined networks have been proposed as a viable solution to decrease the power consumption of the networking component in data center networks. Still the question remains on which scheduling algorithms are most suited to achieve this goal. We propose 4 different linear programming
Velazquez-Marti, B.; Annevelink, E.
2009-01-01
Much bio-energy can be obtained from wood pruning operations in forests and fruit orchards. Several spatial studies have been carried out for biomass surveys, and many linear programming models have been developed to model the logistics of bio-energy chains. These models can assist in determining
Discounted semi-Markov decision processes : linear programming and policy iteration
Wessels, J.; van Nunen, J.A.E.E.
1975-01-01
For semi-Markov decision processes with discounted rewards we derive the well known results regarding the structure of optimal strategies (nonrandomized, stationary Markov strategies) and the standard algorithms (linear programming, policy iteration). Our analysis is completely based on a primal
Fuzzy chance constrained linear programming model for scrap charge optimization in steel production
DEFF Research Database (Denmark)
Rong, Aiying; Lahdelma, Risto
2008-01-01
the uncertainty based on fuzzy set theory and constrain the failure risk based on a possibility measure. Consequently, the scrap charge optimization problem is modeled as a fuzzy chance constrained linear programming problem. Since the constraints of the model mainly address the specification of the product...
Visual, Algebraic and Mixed Strategies in Visually Presented Linear Programming Problems.
Shama, Gilli; Dreyfus, Tommy
1994-01-01
Identified and classified solution strategies of (n=49) 10th-grade students who were presented with linear programming problems in a predominantly visual setting in the form of a computerized game. Visual strategies were developed more frequently than either algebraic or mixed strategies. Appendix includes questionnaires. (Contains 11 references.)…
Discounted semi-Markov decision processes : linear programming and policy iteration
Wessels, J.; van Nunen, J.A.E.E.
1974-01-01
For semi-Markov decision processes with discounted rewards we derive the well known results regarding the structure of optimal strategies (nonrandomized, stationary Markov strategies) and the standard algorithms (linear programming, policy iteration). Our analysis is completely based on a primal
Eric J. Gustafson; L. Jay Roberts; Larry A. Leefers
2006-01-01
Forest management planners require analytical tools to assess the effects of alternative strategies on the sometimes disparate benefits from forests such as timber production and wildlife habitat. We assessed the spatial patterns of alternative management strategies by linking two models that were developed for different purposes. We used a linear programming model (...
Nutrient density score of typical Indonesian foods and dietary formulation using linear programming.
Jati, Ignasius Radix A P; Vadivel, Vellingiri; Nöhr, Donatus; Biesalski, Hans Konrad
2012-12-01
The present research aimed to analyse the nutrient density (ND), nutrient adequacy score (NAS) and energy density (ED) of Indonesian foods and to formulate a balanced diet using linear programming. Data on typical Indonesian diets were obtained from the Indonesian Socio-Economic Survey 2008. ND was investigated for 122 Indonesian foods. NAS was calculated for single nutrients such as Fe, Zn and vitamin A. Correlation analysis was performed between ND and ED, as well as between monthly expenditure class and food consumption pattern in Indonesia. Linear programming calculations were performed using the software POM-QM for Windows version 3. Republic of Indonesia, 2008. Public households (n 68 800). Vegetables had the highest ND of the food groups, followed by animal-based foods, fruits and staple foods. Based on NAS, the top ten food items for each food group were identified. Most of the staple foods had high ED and contributed towards daily energy fulfillment, followed by animal-based foods, vegetables and fruits. Commodities with high ND tended to have low ED. Linear programming could be used to formulate a balanced diet. In contrast to staple foods, purchases of fruit, vegetables and animal-based foods increased with the rise of monthly expenditure. People should select food items based on ND and NAS to alleviate micronutrient deficiencies in Indonesia. Dietary formulation calculated using linear programming to achieve RDA levels for micronutrients could be recommended for different age groups of the Indonesian population.
Huitzing, Hiddo A.
2004-01-01
This article shows how set covering with item sampling (SCIS) methods can be used in the analysis and preanalysis of linear programming models for test assembly (LPTA). LPTA models can construct tests, fulfilling a set of constraints set by the test assembler. Sometimes, no solution to the LPTA model exists. The model is then said to be…
An Interactive Method to Solve Infeasibility in Linear Programming Test Assembling Models
Huitzing, Hiddo A.
2004-01-01
In optimal assembly of tests from item banks, linear programming (LP) models have proved to be very useful. Assembly by hand has become nearly impossible, but these LP techniques are able to find the best solutions, given the demands and needs of the test to be assembled and the specifics of the item bank from which it is assembled. However,…
Secret Message Decryption: Group Consulting Projects Using Matrices and Linear Programming
Gurski, Katharine F.
2009-01-01
We describe two short group projects for finite mathematics students that incorporate matrices and linear programming into fictional consulting requests presented as a letter to the students. The students are required to use mathematics to decrypt secret messages in one project involving matrix multiplication and inversion. The second project…
Research and evaluation of the effectiveness of e-learning in the case of linear programming
Directory of Open Access Journals (Sweden)
Ljiljana Miletić
2016-04-01
Full Text Available The paper evaluates the effectiveness of the e-learning approach to linear programming. The goal was to investigate how proper use of information and communication technologies (ICT and interactive learning helps to improve high school students’ understanding, learning and retention of advanced non-curriculum material. The hypothesis was that ICT and e-learning is helpful in teaching linear programming methods. In the first phase of the research, a module of lessons for linear programming (LP was created using the software package Loomen Moodle and other interactive software packages such as Geogebra. In the second phase, the LP module was taught as a short course to two groups of high school students. These two groups of students were second-grade students in a Croatian high school. In Class 1, the module was taught using ICT and e-learning, while the module was taught using classical methods in Class 2. The action research methodology was an integral part in delivering the course to both student groups. The sample student groups were carefully selected to ensure that differences in background knowledge and learning potential were statistically negligible. Relevant data was collected while delivering the course. Statistical analysis of the collected data showed that the student group using the e-learning method produced better results than the group using a classical learning method. These findings support previous results on the effectiveness of e-learning, and also establish a specific approach to e-learning in linear programming.
Korman, Jonathan; McCann, Robert J.; Seis, Christian
2013-01-01
A new approach to linear programming duality is proposed which relies on quadratic penalization, so that the relation between solutions to the penalized primal and dual problems becomes affine. This yields a new proof of Levin's duality theorem for capacity-constrained optimal transport as an infinite-dimensional application.
The effect of workload constraints in linear programming models for production planning
Jansen, M.M.; Kok, de A.G.; Adan, I.J.B.F.
2011-01-01
Linear programming (LP) models for production planning incorporate a model of the manufacturing system that is necessarily deterministic. Although these deterministic models are the current state-of-the-art, it should be recognized that they are used in an environment that is inherently stochastic.
A linear programming model of diet choice of free-living beavers
Nolet, BA; VanderVeer, PJ; Evers, EGJ; Ottenheim, MM
1995-01-01
Linear programming has been remarkably successful in predicting the diet choice of generalist herbivores. We used this technique to test the diet choice of free-living beavers (Castor fiber) in the Biesbosch (The Netherlands) under different Foraging goals, i.e. maximization of intake of energy,
Mukherjee, Kanchan Kumar; Kumar, Narendra; Tripathi, Manjul; Oinam, Arun S; Ahuja, Chirag K; Dhandapani, Sivashanmugam; Kapoor, Rakesh; Ghoshal, Sushmita; Kaur, Rupinder; Bhatt, Sandeep
2017-01-01
To evaluate the feasibility, safety and efficacy of dose fractionated gamma knife radiosurgery (DFGKRS) on a daily schedule beyond the linear quadratic (LQ) model, for large volume arteriovenous malformations (AVMs). Between 2012-16, 14 patients of large AVMs (median volume 26.5 cc) unsuitable for surgery or embolization were treated in 2-3 of DFGKRS sessions. The Leksell G frame was kept in situ during the whole procedure. 86% (n = 12) patients had radiologic evidence of bleed, and 43% (n = 6) had presented with a history of seizures. 57% (n = 8) patients received a daily treatment for 3 days and 43% (n = 6) were on an alternate day (2 fractions) regimen. The marginal dose was split into 2 or 3 fractions of the ideal prescription dose of a single fraction of 23-25 Gy. The median follow up period was 35.6 months (8-57 months). In the three-fraction scheme, the marginal dose ranged from 8.9-11.5 Gy, while in the two-fraction scheme, the marginal dose ranged from 11.3-15 Gy at 50% per fraction. Headache (43%, n = 6) was the most common early postoperative complication, which was controlled with short course steroids. Follow up evaluation of at least three years was achieved in seven patients, who have shown complete nidus obliteration in 43% patients while the obliteration has been in the range of 50-99% in rest of the patients. Overall, there was a 67.8% reduction in the AVM volume at 3 years. Nidus obliteration at 3 years showed a significant rank order correlation with the cumulative prescription dose (p 0.95, P value 0.01), with attainment of near-total (more than 95%) obliteration rates beyond 29 Gy of the cumulative prescription dose. No patient receiving a cumulative prescription dose of less than 31 Gy had any severe adverse reaction. In co-variate adjusted ordinal regression, only the cumulative prescription dose had a significant correlation with common terminology criteria for adverse events (CTCAE) severity (P value 0.04), independent of age, AVM volume
Acoustic programming in step-split-flow lateral-transport thin fractionation.
Ratier, Claire; Hoyos, Mauricio
2010-02-15
We propose a new separation scheme for micrometer-sized particles combining acoustic forces and gravitational field in split-flow lateral-transport thin (SPLITT)-like fractionation channels. Acoustic forces are generated by ultrasonic standing waves set up in the channel thickness. We report on the separation of latex particles of two different sizes in a preliminary experiment using this proposed hydrodynamic acoustic sorter, HAS. Total binary separation of 5 and 10 microm diameter particles has been achieved. Numerical simulations of trajectories of particles flowing through a step-SPLITT under the conditions which combine acoustic standing waves and gravity show a very good agreement with the experiment. Calculations in order to compare separations obtained by the acoustic programming s-SPLITT fractionation and the conventional SPLITT fractionation show that the improvement in separation time is around 1 order of magnitude and could still be improved; this is the major finding of this work. This separation technique can be extended to biomimetic particles and blood cells.
Cooke, C. H.
1975-01-01
STICAP (Stiff Circuit Analysis Program) is a FORTRAN 4 computer program written for the CDC-6400-6600 computer series and SCOPE 3.0 operating system. It provides the circuit analyst a tool for automatically computing the transient responses and frequency responses of large linear time invariant networks, both stiff and nonstiff (algorithms and numerical integration techniques are described). The circuit description and user's program input language is engineer-oriented, making simple the task of using the program. Engineering theories underlying STICAP are examined. A user's manual is included which explains user interaction with the program and gives results of typical circuit design applications. Also, the program structure from a systems programmer's viewpoint is depicted and flow charts and other software documentation are given.
Dyehouse, Melissa; Bennett, Deborah; Harbor, Jon; Childress, Amy; Dark, Melissa
2009-01-01
Logic models are based on linear relationships between program resources, activities, and outcomes, and have been used widely to support both program development and evaluation. While useful in describing some programs, the linear nature of the logic model makes it difficult to capture the complex relationships within larger, multifaceted…
Fractional Consumption of Liquid Hydrogen and Liquid Oxygen During the Space Shuttle Program
Partridge, Jonathan K.
2011-01-01
The Space Shuttle uses the propellants, liquid hydrogen and liquid oxygen, to meet part of the propulsion requirements from ground to orbit. The Kennedy Space Center procured over 25 million kilograms of liquid hydrogen and over 250 million kilograms of liquid oxygen during the 3D-year Space Shuttle Program. Because of the cryogenic nature of the propellants, approximately 55% of the total purchased liquid hydrogen and 30% of the total purchased liquid oxygen were used in the Space Shuttle Main Engines. The balance of the propellants were vaporized during operations for various purposes. This paper dissects the total consumption of liqUid hydrogen and liqUid oxygen and determines the fraction attributable to each of the various processing and launch operations that occurred during the entire Space Shuttle Program at the Kennedy Space Center.
International Nuclear Information System (INIS)
Martin, P.; Zamudio-Cristi, J.
1982-01-01
A method is described to obtain fractional approximations for linear first order differential equations with polynomial coefficients. This approximation can give good accuracy in a large region of the complex variable plane that may include all the real axis. The parameters of the approximation are solutions of algebraic equations obtained through the coefficients of the highest and lowest power of the variable after the sustitution of the fractional approximation in the differential equation. The method is more general than the asymptotical Pade method, and it is not required to determine the power series or asymptotical expansion. A simple approximation for the exponential integral is found, which give three exact digits for most of the real values of the variable. Approximations of higher accuracy and of the same degree than other authors are also obtained. (Author) [pt
International Nuclear Information System (INIS)
Alsmiller, R.G. Jr.; Alsmiller, F.S.; Lewis, T.A.
1986-05-01
In a series of previous papers, calculated results obtained using a one-dimensional ballistic model were presented to aid in the design of a prebuncher for the Oak Ridge Electron Linear Accelerator. As part of this work, a model was developed to provide limits on the fraction of an incident current pulse that would be accelerated by the existing accelerator. In this paper experimental data on this fraction are presented and the validity of the model developed previously is tested by comparing calculated and experimental data. Part of the experimental data is used to fix the physical parameters in the model and then good agreement between the calculated results and the rest of the experimental data is obtained
International Nuclear Information System (INIS)
Kovacic, Ivana
2009-01-01
An analytical approach to determine the approximate solution for the periodic motion of non-conservative oscillators with a fractional-order restoring force and slowly varying parameters is presented. The solution has the form of the first-order differential equation for the amplitude and phase of motion. The method used is based on the combination of the Krylov-Bogoliubov method with Hamilton's variational principle with the uncommutative rule for the variation of velocity. The conservative systems with slowly varying parameters are also considered. The corresponding adiabatic invariant is obtained. Two examples are given to illustrate derived theoretical results.
International Nuclear Information System (INIS)
Aref'ev, A.V.; Blokhov, M.V.; Gerasimov, V.F.
1981-01-01
A program of physical investigations and the corresponding requirements to accelerated beam parameters are discussed in brief. The state and working capacity of separate units and the accelerator as a whole for the 8-year operating period are analyzed. The aim and principal program points of linear electron accelerator modernization are defined. The program of accelerator modernization assumes: electron beam energy increase up to 100-120 MeV; mounting of three additional accelerating sections; clystron efficiency increase; development of a highly reliable modulator; stabilized power supply sources; a system of synchronous start-up; a focusing system; a beam separation system and etc [ru
Linear programming models and methods of matrix games with payoffs of triangular fuzzy numbers
Li, Deng-Feng
2016-01-01
This book addresses two-person zero-sum finite games in which the payoffs in any situation are expressed with fuzzy numbers. The purpose of this book is to develop a suite of effective and efficient linear programming models and methods for solving matrix games with payoffs in fuzzy numbers. Divided into six chapters, it discusses the concepts of solutions of matrix games with payoffs of intervals, along with their linear programming models and methods. Furthermore, it is directly relevant to the research field of matrix games under uncertain economic management. The book offers a valuable resource for readers involved in theoretical research and practical applications from a range of different fields including game theory, operational research, management science, fuzzy mathematical programming, fuzzy mathematics, industrial engineering, business and social economics. .
User's Guide to the Weighted-Multiple-Linear Regression Program (WREG version 1.0)
Eng, Ken; Chen, Yin-Yu; Kiang, Julie.E.
2009-01-01
Streamflow is not measured at every location in a stream network. Yet hydrologists, State and local agencies, and the general public still seek to know streamflow characteristics, such as mean annual flow or flood flows with different exceedance probabilities, at ungaged basins. The goals of this guide are to introduce and familiarize the user with the weighted multiple-linear regression (WREG) program, and to also provide the theoretical background for program features. The program is intended to be used to develop a regional estimation equation for streamflow characteristics that can be applied at an ungaged basin, or to improve the corresponding estimate at continuous-record streamflow gages with short records. The regional estimation equation results from a multiple-linear regression that relates the observable basin characteristics, such as drainage area, to streamflow characteristics.
Simic, Vladimir; Dimitrijevic, Branka
2015-02-01
An interval linear programming approach is used to formulate and comprehensively test a model for optimal long-term planning of vehicle recycling in the Republic of Serbia. The proposed model is applied to a numerical case study: a 4-year planning horizon (2013-2016) is considered, three legislative cases and three scrap metal price trends are analysed, availability of final destinations for sorted waste flows is explored. Potential and applicability of the developed model are fully illustrated. Detailed insights on profitability and eco-efficiency of the projected contemporary equipped vehicle recycling factory are presented. The influences of the ordinance on the management of end-of-life vehicles in the Republic of Serbia on the vehicle hulks procuring, sorting generated material fractions, sorted waste allocation and sorted metals allocation decisions are thoroughly examined. The validity of the waste management strategy for the period 2010-2019 is tested. The formulated model can create optimal plans for procuring vehicle hulks, sorting generated material fractions, allocating sorted waste flows and allocating sorted metals. Obtained results are valuable for supporting the construction and/or modernisation process of a vehicle recycling system in the Republic of Serbia. © The Author(s) 2015.
Guo, Sangang
2017-09-01
There are two stages in solving security-constrained unit commitment problems (SCUC) within Lagrangian framework: one is to obtain feasible units’ states (UC), the other is power economic dispatch (ED) for each unit. The accurate solution of ED is more important for enhancing the efficiency of the solution to SCUC for the fixed feasible units’ statues. Two novel methods named after Convex Combinatorial Coefficient Method and Power Increment Method respectively based on linear programming problem for solving ED are proposed by the piecewise linear approximation to the nonlinear convex fuel cost functions. Numerical testing results show that the methods are effective and efficient.
International Nuclear Information System (INIS)
Wennberg, Berit M.; Baumann, Pia; Gagliardi, Giovanna
2011-01-01
Background. In SBRT of lung tumours no established relationship between dose-volume parameters and the incidence of lung toxicity is found. The aim of this study is to compare the LQ model and the universal survival curve (USC) to calculate biologically equivalent doses in SBRT to see if this will improve knowledge on this relationship. Material and methods. Toxicity data on radiation pneumonitis grade 2 or more (RP2+) from 57 patients were used, 10.5% were diagnosed with RP2+. The lung DVHs were corrected for fractionation (LQ and USC) and analysed with the Lyman- Kutcher-Burman (LKB) model. In the LQ-correction α/β = 3 Gy was used and the USC parameters used were: α/β = 3 Gy, D 0 = 1.0 Gy, n = 10, α 0.206 Gy-1 and d T = 5.8 Gy. In order to understand the relative contribution of different dose levels to the calculated NTCP the concept of fractional NTCP was used. This might give an insight to the questions of whether 'high doses to small volumes' or 'low doses to large volumes' are most important for lung toxicity. Results and Discussion. NTCP analysis with the LKB-model using parameters m = 0.4, D50 = 30 Gy resulted for the volume dependence parameter (n) with LQ correction n = 0.87 and with USC correction n = 0.71. Using parameters m = 0.3, D 50 = 20 Gy n = 0.93 with LQ correction and n 0.83 with USC correction. In SBRT of lung tumours, NTCP modelling of lung toxicity comparing models (LQ,USC) for fractionation correction, shows that low dose contribute less and high dose more to the NTCP when using the USC-model. Comparing NTCP modelling of SBRT data and data from breast cancer, lung cancer and whole lung irradiation implies that the response of the lung is treatment specific. More data are however needed in order to have a more reliable modelling
Plocková, J; Chmelík, J
2001-05-25
Gravitational field-flow fractionation (GFFF) utilizes the Earth's gravitational field as an external force that causes the settlement of particles towards the channel accumulation wall. Hydrodynamic lift forces oppose this action by elevating particles away from the channel accumulation wall. These two counteracting forces enable modulation of the resulting force field acting on particles in GFFF. In this work, force-field programming based on modulating the magnitude of hydrodynamic lift forces was implemented via changes of flow-rate, which was accomplished by a programmable pump. Several flow-rate gradients (step gradients, linear gradients, parabolic, and combined gradients) were tested and evaluated as tools for optimization of the separation of a silica gel particle mixture. The influence of increasing amount of sample injected on the peak resolution under flow-rate gradient conditions was also investigated. This is the first time that flow-rate gradients have been implemented for programming of the resulting force field acting on particles in GFFF.
Stability of multi-objective bi-level linear programming problems under fuzziness
Directory of Open Access Journals (Sweden)
Abo-Sinna Mahmoud A.
2013-01-01
Full Text Available This paper deals with multi-objective bi-level linear programming problems under fuzzy environment. In the proposed method, tentative solutions are obtained and evaluated by using the partial information on preference of the decision-makers at each level. The existing results concerning the qualitative analysis of some basic notions in parametric linear programming problems are reformulated to study the stability of multi-objective bi-level linear programming problems. An algorithm for obtaining any subset of the parametric space, which has the same corresponding Pareto optimal solution, is presented. Also, this paper established the model for the supply-demand interaction in the age of electronic commerce (EC. First of all, the study uses the individual objectives of both parties as the foundation of the supply-demand interaction. Subsequently, it divides the interaction, in the age of electronic commerce, into the following two classifications: (i Market transactions, with the primary focus on the supply demand relationship in the marketplace; and (ii Information service, with the primary focus on the provider and the user of information service. By applying the bi-level programming technique of interaction process, the study will develop an analytical process to explain how supply-demand interaction achieves a compromise or why the process fails. Finally, a numerical example of information service is provided for the sake of illustration.
A computer program for two-particle intrinsic coefficients of fractional parentage
Deveikis, A.
2012-06-01
A Fortran 90 program CESOS for the calculation of the two-particle intrinsic coefficients of fractional parentage for several j-shells with isospin and an arbitrary number of oscillator quanta (CESOs) is presented. The implemented procedure for CESOs calculation consistently follows the principles of antisymmetry and translational invariance. The approach is based on a simple enumeration scheme for antisymmetric many-particle states, efficient algorithms for calculation of the coefficients of fractional parentage for j-shells with isospin, and construction of the subspace of the center-of-mass Hamiltonian eigenvectors corresponding to the minimal eigenvalue equal to 3/2 (in ℏω). The program provides fast calculation of CESOs for a given particle number and produces results possessing small numerical uncertainties. The introduced CESOs may be used for calculation of expectation values of two-particle nuclear shell-model operators within the isospin formalism. Program summaryProgram title: CESOS Catalogue identifier: AELT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AELT_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.: 10 932 No. of bytes in distributed program, including test data, etc.: 61 023 Distribution format: tar.gz Programming language: Fortran 90 Computer: Any computer with a Fortran 90 compiler Operating system: Windows XP, Linux RAM: The memory demand depends on the number of particles A and the excitation energy of the system E. Computation of the A=6 particle system with the total angular momentum J=0 and the total isospin T=1 requires around 4 kB of RAM at E=0,˜3 MB at E=3, and ˜172 MB at E=5. Classification: 17.18 Nature of problem: The code CESOS generates a list of two-particle intrinsic coefficients of fractional parentage for several
Directory of Open Access Journals (Sweden)
Sifeu Takougang Kingni
2017-01-01
Full Text Available A linear resistive-capacitive-inductance shunted junction (LRCLSJ model obtained by replacing the nonlinear piecewise resistance of a nonlinear resistive-capacitive-inductance shunted junction (NRCLSJ model by a linear resistance is analyzed in this paper. The LRCLSJ model has two or no equilibrium points depending on the dc bias current. For a suitable choice of the parameters, the LRCLSJ model without equilibrium point can exhibit regular and fast spiking, intrinsic and periodic bursting, and periodic and chaotic behaviors. We show that the LRCLSJ model displays similar dynamical behaviors as the NRCLSJ model. Moreover the coexistence between periodic and chaotic attractors is found in the LRCLSJ model for specific parameters. The lowest order of the commensurate form of the no equilibrium LRCLSJ model to exhibit chaotic behavior is found to be 2.934. Moreover, adaptive finite-time synchronization with parameter estimation is applied to achieve synchronization of unidirectional coupled identical fractional-order form of chaotic no equilibrium LRCLSJ models. Finally, a cryptographic encryption scheme with the help of the finite-time synchronization of fractional-order chaotic no equilibrium LRCLSJ models is illustrated through a numerical example, showing that a high level security device can be produced using this system.
The use of linear programming in optimization of HDR implant dose distributions
International Nuclear Information System (INIS)
Jozsef, Gabor; Streeter, Oscar E.; Astrahan, Melvin A.
2003-01-01
The introduction of high dose rate brachytherapy enabled optimization of dose distributions to be used on a routine basis. The objective of optimization is to homogenize the dose distribution within the implant while simultaneously satisfying dose constraints on certain points. This is accomplished by varying the time the source dwells at different locations. As the dose at any point is a linear function of the dwell times, a linear programming approach seems to be a natural choice. The dose constraints are inherently linear inequalities. Homogeneity requirements are linearized by minimizing the maximum deviation of the doses at points inside the implant from a prescribed dose. The revised simplex method was applied for the solution of this linear programming problem. In the homogenization process the possible source locations were chosen as optimization points. To avoid the problem of the singular value of the dose at a source location from the source itself we define the 'self-contribution' as the dose at a small distance from the source. The effect of varying this distance is discussed. Test cases were optimized for planar, biplanar and cylindrical implants. A semi-irregular, fan-like implant with diverging needles was also investigated. Mean central dose calculation based on 3D Delaunay-triangulation of the source locations was used to evaluate the dose distributions. The optimization method resulted in homogeneous distributions (for brachytherapy). Additional dose constraints--when applied--were satisfied. The method is flexible enough to include other linear constraints such as the inclusion of the centroids of the Delaunay-triangulation for homogenization, or limiting the maximum allowable dwell time
Directory of Open Access Journals (Sweden)
S. Alonso-Quesada
2010-01-01
Full Text Available This paper presents a strategy for designing a robust discrete-time adaptive controller for stabilizing linear time-invariant (LTI continuous-time dynamic systems. Such systems may be unstable and noninversely stable in the worst case. A reduced-order model is considered to design the adaptive controller. The control design is based on the discretization of the system with the use of a multirate sampling device with fast-sampled control signal. A suitable on-line adaptation of the multirate gains guarantees the stability of the inverse of the discretized estimated model, which is used to parameterize the adaptive controller. A dead zone is included in the parameters estimation algorithm for robustness purposes under the presence of unmodeled dynamics in the controlled dynamic system. The adaptive controller guarantees the boundedness of the system measured signal for all time. Some examples illustrate the efficacy of this control strategy.
Linear programming to build food-based dietary guidelines: Romanian food baskets
DEFF Research Database (Denmark)
Parlesak, Alexandr; Robertson, Aileen; Hondru, Gabriela
approach using linear programming methodology to design national dietary recommendations which aim to prevent both NCDs and micronutrient deficiencies and still be affordable by low income groups. This new approach is applied within the context of food availability in Romania in 2014. Eating the same food...... every day is unrealistic and too monotonous to be maintained, so this novel approach is used to select a wide range of diverse foods that can be recommended for a period of up to, for example, one month. The following are the key findings of this report. • The simplest version of the Romanian food.......65 lei (~€ 4.46) for a day. • Key nutrients, primarily vitamin D, calcium, potassium and iron, were found to control the overall price. • The least expensive basket (one day’s rations) is monotonous and the linear programming approach is used to select a wide range of foods that can be recommended...
International Nuclear Information System (INIS)
Shimizu, Yoshiaki
1981-01-01
A mathematical procedure is proposed to make a radioactive waste management plan comprehensively. Since such planning is relevant to some different goals in management, decision making has to be formulated as a multiobjective optimization problem. A mathematical programming method was introduced to make a decision through an interactive manner which enables us to assess the preference of decision maker step by step among the conflicting objectives. The reference system taken as an example is the radioactive waste management system at the Research Reactor Institute of Kyoto University (KUR). Its linear model was built based on the experience in the actual management at KUR. The best-compromise model was then formulated as a multiobjective linear programming by the aid of the computational analysis through a conventional optimization. It was shown from the numerical results that the proposed approach could provide some useful informations to make an actual management plan. (author)
Mixed integer linear programming model for dynamic supplier selection problem considering discounts
Directory of Open Access Journals (Sweden)
Adi Wicaksono Purnawan
2018-01-01
Full Text Available Supplier selection is one of the most important elements in supply chain management. This function involves evaluation of many factors such as, material costs, transportation costs, quality, delays, supplier capacity, storage capacity and others. Each of these factors varies with time, therefore, supplier identified for one period is not necessarily be same for the next period to supply the same product. So, mixed integer linear programming (MILP was developed to overcome the dynamic supplier selection problem (DSSP. In this paper, a mixed integer linear programming model is built to solve the lot-sizing problem with multiple suppliers, multiple periods, multiple products and quantity discounts. The buyer has to make a decision for some products which will be supplied by some suppliers for some periods cosidering by discount. To validate the MILP model with randomly generated data. The model is solved by Lingo 16.
Visualizing measurement for 3D smooth density distributions by means of linear programming
International Nuclear Information System (INIS)
Tayama, Norio; Yang, Xue-dong
1994-01-01
This paper is concerned with a theoretical possibility of a new visualizing measurement method based on an optimum 3D reconstruction from a few selected projections. A theory of optimum 3D reconstruction by a linear programming is discussed, utilizing a few projections for sampled 3D smooth-density-distribution model which satisfies the condition of the 3D sampling theorem. First by use of the sampling theorem, it is shown that we can set up simultaneous simple equations which corresponds to the case of the parallel beams. Then we solve the simultaneous simple equations by means of linear programming algorithm, and we can get an optimum 3D density distribution images with minimum error in the reconstruction. The results of computer simulation with the algorithm are presented. (author)
Ren, Jingzheng; Dong, Liang; Sun, Lu; Goodsite, Michael Evan; Tan, Shiyu; Dong, Lichun
2015-01-01
The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties. Copyright © 2015 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Romeijn, H Edwin; Ahuja, Ravindra K; Dempsey, James F; Kumar, Arvind; Li, Jonathan G
2003-01-01
We present a novel linear programming (LP) based approach for efficiently solving the intensity modulated radiation therapy (IMRT) fluence-map optimization (FMO) problem to global optimality. Our model overcomes the apparent limitations of a linear-programming approach by approximating any convex objective function by a piecewise linear convex function. This approach allows us to retain the flexibility offered by general convex objective functions, while allowing us to formulate the FMO problem as a LP problem. In addition, a novel type of partial-volume constraint that bounds the tail averages of the differential dose-volume histograms of structures is imposed while retaining linearity as an alternative approach to improve dose homogeneity in the target volumes, and to attempt to spare as many critical structures as possible. The goal of this work is to develop a very rapid global optimization approach that finds high quality dose distributions. Implementation of this model has demonstrated excellent results. We found globally optimal solutions for eight 7-beam head-and-neck cases in less than 3 min of computational time on a single processor personal computer without the use of partial-volume constraints. Adding such constraints increased the running times by a factor of 2-3, but improved the sparing of critical structures. All cases demonstrated excellent target coverage (>95%), target homogeneity (<10% overdosing and <7% underdosing) and organ sparing using at least one of the two models
Directory of Open Access Journals (Sweden)
Weihua Jin
2013-01-01
Full Text Available This paper proposes a genetic-algorithms-based approach as an all-purpose problem-solving method for operation programming problems under uncertainty. The proposed method was applied for management of a municipal solid waste treatment system. Compared to the traditional interactive binary analysis, this approach has fewer limitations and is able to reduce the complexity in solving the inexact linear programming problems and inexact quadratic programming problems. The implementation of this approach was performed using the Genetic Algorithm Solver of MATLAB (trademark of MathWorks. The paper explains the genetic-algorithms-based method and presents details on the computation procedures for each type of inexact operation programming problems. A comparison of the results generated by the proposed method based on genetic algorithms with those produced by the traditional interactive binary analysis method is also presented.
DEFF Research Database (Denmark)
Cetin, Bilge Kartal; Prasad, Neeli R.; Prasad, Ramjee
2011-01-01
In wireless sensor networks, one of the key challenge is to achieve minimum energy consumption in order to maximize network lifetime. In fact, lifetime depends on many parameters: the topology of the sensor network, the data aggregation regime in the network, the channel access schemes, the routing...... protocols, and the energy model for transmission. In this paper, we tackle the routing challenge for maximum lifetime of the sensor network. We introduce a novel linear programming approach to the maximum lifetime routing problem. To the best of our knowledge, this is the first mathematical programming...
Mixed Integer Linear Programming model for Crude Palm Oil Supply Chain Planning
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 new neural network model for solving random interval linear programming problems.
Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza
2017-05-01
This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique. Copyright © 2017 Elsevier Ltd. All rights reserved.
CiOpt: a program for optimization of the frequency response of linear circuits
Miró Sans, Joan Maria; Palà Schönwälder, Pere
1991-01-01
An interactive personal-computer program for optimizing the frequency response of linear lumped circuits (CiOpt) is presented. CiOpt has proved to be an efficient tool in improving designs where the inclusion of more accurate device models distorts the desired frequency response, as well as in device modeling. The outputs of CiOpt are the element values which best match the obtained and the desired frequency response. The optimization algorithms used (the Fletcher-Powell and Newton's methods,...
Roslee Rajikan; Nurul Izza Ahmad Zaidi; Siti Masitah Elias; Suzana Shahar; Zahara Abd Manaf; Noor Aini Md Yusoff
2017-01-01
Differences in socioeconomic profile may influences healthy food choices, particularly among individuals with low socioeconomic status. Thus, high-energy dense foods become the preferences compared to high nutritional content foods due to their cheaper price. The present study aims to develop healthy and palatable diet at the minimum cost based on Malaysian Dietary Guidelines 2010 and Recommended Nutrient Intake 2005 via linear programming. A total of 96 female adults from low socioeconomic f...
A linear programming approach to characterizing norm bounded uncertainty from experimental data
Scheid, R. E.; Bayard, D. S.; Yam, Y.
1991-01-01
The linear programming spectral overbounding and factorization (LPSOF) algorithm, an algorithm for finding a minimum phase transfer function of specified order whose magnitude tightly overbounds a specified nonparametric function of frequency, is introduced. This method has direct application to transforming nonparametric uncertainty bounds (available from system identification experiments) into parametric representations required for modern robust control design software (i.e., a minimum-phase transfer function multiplied by a norm-bounded perturbation).
A Unique Technique to get Kaprekar Iteration in Linear Programming Problem
Sumathi, P.; Preethy, V.
2018-04-01
This paper explores about a frivolous number popularly known as Kaprekar constant and Kaprekar numbers. A large number of courses and the different classroom capacities with difference in study periods make the assignment between classrooms and courses complicated. An approach of getting the minimum value of number of iterations to reach the Kaprekar constant for four digit numbers and maximum value is also obtained through linear programming techniques.
Stress-constrained truss topology optimization problems that can be solved by linear programming
DEFF Research Database (Denmark)
Stolpe, Mathias; Svanberg, Krister
2004-01-01
We consider the problem of simultaneously selecting the material and determining the area of each bar in a truss structure in such a way that the cost of the structure is minimized subject to stress constraints under a single load condition. We show that such problems can be solved by linear...... programming to give the global optimum, and that two different materials are always sufficient in an optimal structure....
Fuzzy solution of the linear programming problem with interval coefficients in the constraints
Dorota Kuchta
2005-01-01
A fuzzy concept of solving the linear programming problem with interval coefficients is proposed. For each optimism level of the decision maker (where the optimism concerns the certainty that no errors have been committed in the estimation of the interval coefficients and the belief that optimistic realisations of the interval coefficients will occur) another interval solution of the problem will be generated and the decision maker will be able to choose the final solution having a complete v...
An Improved Search Approach for Solving Non-Convex Mixed-Integer Non Linear Programming Problems
Sitopu, Joni Wilson; Mawengkang, Herman; Syafitri Lubis, Riri
2018-01-01
The nonlinear mathematical programming problem addressed in this paper has a structure characterized by a subset of variables restricted to assume discrete values, which are linear and separable from the continuous variables. The strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method, has been developed. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points. Successful implementation of these algorithms was achieved on various test problems.
A Mixed Integer Linear Programming Model for the North Atlantic Aircraft Trajectory Planning
Sbihi , Mohammed; Rodionova , Olga; Delahaye , Daniel; Mongeau , Marcel
2015-01-01
International audience; This paper discusses the trajectory planning problem for ights in the North Atlantic oceanic airspace (NAT). We develop a mathematical optimization framework in view of better utilizing available capacity by re-routing aircraft. The model is constructed by discretizing the problem parameters. A Mixed integer linear program (MILP) is proposed. Based on the MILP a heuristic to solve real-size instances is also introduced
Learning Bayesian network structure: towards the essential graph by integer linear programming tools
Czech Academy of Sciences Publication Activity Database
Studený, Milan; Haws, D.
2014-01-01
Roč. 55, č. 4 (2014), s. 1043-1071 ISSN 0888-613X R&D Projects: GA ČR GA13-20012S Institutional support: RVO:67985556 Keywords : learning Bayesian network structure * integer linear programming * characteristic imset * essential graph Subject RIV: BA - General Mathematics Impact factor: 2.451, year: 2014 http://library.utia.cas.cz/separaty/2014/MTR/studeny-0427002.pdf
APPLYING ROBUST RANKING METHOD IN TWO PHASE FUZZY OPTIMIZATION LINEAR PROGRAMMING PROBLEMS (FOLPP
Directory of Open Access Journals (Sweden)
Monalisha Pattnaik
2014-12-01
Full Text Available Background: This paper explores the solutions to the fuzzy optimization linear program problems (FOLPP where some parameters are fuzzy numbers. In practice, there are many problems in which all decision parameters are fuzzy numbers, and such problems are usually solved by either probabilistic programming or multi-objective programming methods. Methods: In this paper, using the concept of comparison of fuzzy numbers, a very effective method is introduced for solving these problems. This paper extends linear programming based problem in fuzzy environment. With the problem assumptions, the optimal solution can still be theoretically solved using the two phase simplex based method in fuzzy environment. To handle the fuzzy decision variables can be initially generated and then solved and improved sequentially using the fuzzy decision approach by introducing robust ranking technique. Results and conclusions: The model is illustrated with an application and a post optimal analysis approach is obtained. The proposed procedure was programmed with MATLAB (R2009a version software for plotting the four dimensional slice diagram to the application. Finally, numerical example is presented to illustrate the effectiveness of the theoretical results, and to gain additional managerial insights.
The Linear Programming to evaluate the performance of Oral Health in Primary Care.
Colussi, Claudia Flemming; Calvo, Maria Cristina Marino; Freitas, Sergio Fernando Torres de
2013-01-01
To show the use of Linear Programming to evaluate the performance of Oral Health in Primary Care. This study used data from 19 municipalities of Santa Catarina city that participated of the state evaluation in 2009 and have more than 50,000 habitants. A total of 40 indicators were evaluated, calculated using the Microsoft Excel 2007, and converted to the interval [0, 1] in ascending order (one indicating the best situation and zero indicating the worst situation). Applying the Linear Programming technique municipalities were assessed and compared among them according to performance curve named "quality estimated frontier". Municipalities included in the frontier were classified as excellent. Indicators were gathered, and became synthetic indicators. The majority of municipalities not included in the quality frontier (values different of 1.0) had lower values than 0.5, indicating poor performance. The model applied to the municipalities of Santa Catarina city assessed municipal management and local priorities rather than the goals imposed by pre-defined parameters. In the final analysis three municipalities were included in the "perceived quality frontier". The Linear Programming technique allowed to identify gaps that must be addressed by city managers to enhance actions taken. It also enabled to observe each municipal performance and compare results among similar municipalities.
Schipper, R.A.; Stoorvogel, J.J.; Jansen, D.M.
1995-01-01
The paper deals with linear programming as a tool for land use analysis at the sub-regional level. A linear programming model of a case study area, the Neguev settlement in the Atlantic zone of Costa Rica, is presented. The matrix of the model includes five submatrices each encompassing a different
International Nuclear Information System (INIS)
Sergienko, I.V.; Golodnikov, A.N.
1984-01-01
This article applies the methods of decompositions, which are used to solve continuous linear problems, to integer and partially integer problems. The fall-vector method is used to solve the obtained coordinate problems. An algorithm of the fall-vector is described. The Kornai-Liptak decomposition principle is used to reduce the integer linear programming problem to integer linear programming problems of a smaller dimension and to a discrete coordinate problem with simple constraints
Barber, Duncan Henry
benchmark calculation demonstrates the improvement in agreement of the total inventory of those chemical elements included in the RMC fuel model to an ORIGEN-S calculation. ORIGEN-S is the Oak Ridge isotope generation and depletion computer program. The Gibbs energy minimizer requires a chemical database containing coefficients from which the Gibbs energy of pure compounds, gas and liquid mixtures, and solid solutions can be calculated. The RMC model of irradiated uranium dioxide fuel has been converted into the required format. The Gibbs energy minimizer has been incorporated into a new model of fission-product vaporization from the fuel surface. Calculated release fractions using the new code have been compared to results calculated with SOURCE IST 2.0P11 and to results of tests used in the validation of SOURCE 2.0. The new code shows improvements in agreement with experimental releases for a number of nuclides. Of particular significance is the better agreement between experimental and calculated release fractions for 140La. The improved agreement reflects the inclusion in the RMC model of the solubility of lanthanum (III) oxide (La2O3) in the fuel matrix. Calculated lanthanide release fractions from earlier computer programs were a challenge to environmental qualification analysis of equipment for some accident scenarios. The new prototype computer program would alleviate this concern. Keywords: Nuclear Engineering; Material Science; Thermodynamics; Radioactive Material, Gibbs Energy Minimization, Actinide Generation and Depletion, FissionProduct Generation and Depletion.
IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS
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.
Energy Technology Data Exchange (ETDEWEB)
Ellis, J H; McBean, E A; Farquhar, G J
1985-01-01
A Linear Programming model is presented for development of acid rain abatement strategies in eastern North America. For a system comprised of 235 large controllable point sources and 83 uncontrolled area sources, it determines the least-cost method of reducing SO/sub 2/ emissions to satisfy maximum wet sulfur deposition limits at 20 sensitive receptor locations. In this paper, the purely deterministic model is extended to a probabilistic form by incorporating the effects of meteorologic variability on the long-range pollutant transport processes. These processes are represented by source-receptor-specific transfer coefficients. Experiments for quantifying the spatial variability of transfer coefficients showed their distributions to be approximately lognormal with logarithmic standard deviations consistently about unity. Three methods of incorporating second-moment random variable uncertainty into the deterministic LP framework are described: Two-Stage Programming Under Uncertainty, Chance-Constrained Programming and Stochastic Linear Programming. A composite CCP-SLP model is developed which embodies the two-dimensional characteristics of transfer coefficient uncertainty. Two probabilistic formulations are described involving complete colinearity and complete noncolinearity for the transfer coefficient covariance-correlation structure. The completely colinear and noncolinear formulations are considered extreme bounds in a meteorologic sense and yield abatement strategies of largely didactic value. Such strategies can be characterized as having excessive costs and undesirable deposition results in the completely colinear case and absence of a clearly defined system risk level (other than expected-value) in the noncolinear formulation.
Optimal placement of capacitors in a radial network using conic and mixed integer linear programming
Energy Technology Data Exchange (ETDEWEB)
Jabr, R.A. [Electrical, Computer and Communication Engineering Department, Notre Dame University, P.O. Box: 72, Zouk Mikhael, Zouk Mosbeh (Lebanon)
2008-06-15
This paper considers the problem of optimally placing fixed and switched type capacitors in a radial distribution network. The aim of this problem is to minimize the costs associated with capacitor banks, peak power, and energy losses whilst satisfying a pre-specified set of physical and technical constraints. The proposed solution is obtained using a two-phase approach. In phase-I, the problem is formulated as a conic program in which all nodes are candidates for placement of capacitor banks whose sizes are considered as continuous variables. A global solution of the phase-I problem is obtained using an interior-point based conic programming solver. Phase-II seeks a practical optimal solution by considering capacitor sizes as discrete variables. The problem in this phase is formulated as a mixed integer linear program based on minimizing the L1-norm of deviations from the phase-I state variable values. The solution to the phase-II problem is obtained using a mixed integer linear programming solver. The proposed method is validated via extensive comparisons with previously published results. (author)
Automated design and optimization of flexible booster autopilots via linear programming, volume 1
Hauser, F. D.
1972-01-01
A nonlinear programming technique was developed for the automated design and optimization of autopilots for large flexible launch vehicles. This technique, which resulted in the COEBRA program, uses the iterative application of linear programming. The method deals directly with the three main requirements of booster autopilot design: to provide (1) good response to guidance commands; (2) response to external disturbances (e.g. wind) to minimize structural bending moment loads and trajectory dispersions; and (3) stability with specified tolerances on the vehicle and flight control system parameters. The method is applicable to very high order systems (30th and greater per flight condition). Examples are provided that demonstrate the successful application of the employed algorithm to the design of autopilots for both single and multiple flight conditions.
Directory of Open Access Journals (Sweden)
Hideki Katagiri
2017-10-01
Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.
Energy Technology Data Exchange (ETDEWEB)
Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia
1997-12-01
This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs.
Wavelet-linear genetic programming: A new approach for modeling monthly streamflow
Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur
2017-06-01
The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.
International Nuclear Information System (INIS)
Piacentino, A.; Cardona, F.
2008-01-01
The optimization of synthesis, design and operation in trigeneration systems for building applications is a quite complex task, due to the high number of decision variables, the presence of irregular heat, cooling and electric load profiles and the variable electricity price. Consequently, computer-aided techniques are usually adopted to achieve the optimal solution, based either on iterative techniques, linear or non-linear programming or evolutionary search. Large efforts have been made in improving algorithm efficiency, which have resulted in an increasingly rapid convergence to the optimal solution and in reduced calculation time; robust algorithm have also been formulated, assuming stochastic behaviour for energy loads and prices. This paper is based on the assumption that margins for improvements in the optimization of trigeneration systems still exist, which require an in-depth understanding of plant's energetic behaviour. Robustness in the optimization of trigeneration systems has more to do with a 'correct and comprehensive' than with an 'efficient' modelling, being larger efforts required to energy specialists rather than to experts in efficient algorithms. With reference to a mixed integer linear programming model implemented in MatLab for a trigeneration system including a pressurized (medium temperature) heat storage, the relevant contribute of thermoeconomics and energo-environmental analysis in the phase of mathematical modelling and code testing are shown
A versatile program for the calculation of linear accelerator room shielding.
Hassan, Zeinab El-Taher; Farag, Nehad M; Elshemey, Wael M
2018-03-22
This work aims at designing a computer program to calculate the necessary amount of shielding for a given or proposed linear accelerator room design in radiotherapy. The program (Shield Calculation in Radiotherapy, SCR) has been developed using Microsoft Visual Basic. It applies the treatment room shielding calculations of NCRP report no. 151 to calculate proper shielding thicknesses for a given linear accelerator treatment room design. The program is composed of six main user-friendly interfaces. The first enables the user to upload their choice of treatment room design and to measure the distances required for shielding calculations. The second interface enables the user to calculate the primary barrier thickness in case of three-dimensional conventional radiotherapy (3D-CRT), intensity modulated radiotherapy (IMRT) and total body irradiation (TBI). The third interface calculates the required secondary barrier thickness due to both scattered and leakage radiation. The fourth and fifth interfaces provide a means to calculate the photon dose equivalent for low and high energy radiation, respectively, in door and maze areas. The sixth interface enables the user to calculate the skyshine radiation for photons and neutrons. The SCR program has been successfully validated, precisely reproducing all of the calculated examples presented in NCRP report no. 151 in a simple and fast manner. Moreover, it easily performed the same calculations for a test design that was also calculated manually, and produced the same results. The program includes a new and important feature that is the ability to calculate required treatment room thickness in case of IMRT and TBI. It is characterised by simplicity, precision, data saving, printing and retrieval, in addition to providing a means for uploading and testing any proposed treatment room shielding design. The SCR program provides comprehensive, simple, fast and accurate room shielding calculations in radiotherapy.
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.
Optimization of production planning in Czech agricultural co-operative via linear programming
Directory of Open Access Journals (Sweden)
Jitka Janová
2009-01-01
Full Text Available The production planning is one of the key managerial decisions in agricultural business, which must be done periodically every year. Correct decision must cover the agriculture demands of planting the crops such as crop rotation restrictions or water resource scarcity, while the decision maker aims to plan the crop design in most profitable way in sense of maximizing the total profit from the crop yield. This decision problem represents the optimization of crop design and can be treated by the methods of linear programming which begun to be extensively used in agriculture production planning in USA during 50’s. There is ongoing research of mathematical programming applications in agriculture worldwide, but the results are not easily transferable to other localities due to the specific local restrictions in each country. In Czech Republic the farmers use for production planning mainly their expert knowledge and past experience. However, the mathematical programming approach enables find the true optimal solution of the problem, which especially in the problems with a great number of constraints is not easy to find intuitively. One of the possible barriers for using the general decision support systems (which are based on mathematical programming methods for agriculture production planning in Czech Republic is its expensiveness. The small farmer can not afford to buy the expensive software or to employ a mathematical programming specialist. The aim of this paper is to present a user friendly linear programming model of the typical agricultural production planning problem in Czech Republic which can be solved via software tools commonly available in any farm (e.g. EXCEL. The linear programming model covering the restrictions on total costs, crop rotation, thresholds for the total area sowed by particular crops, total amount of manure and the need of feed crops is developed. The model is applied in real-world problem of Czech agriculture
Solutions to estimation problems for scalar hamilton-jacobi equations using linear programming
Claudel, Christian G.; Chamoin, Timothee; Bayen, Alexandre M.
2014-01-01
This brief presents new convex formulations for solving estimation problems in systems modeled by scalar Hamilton-Jacobi (HJ) equations. Using a semi-analytic formula, we show that the constraints resulting from a HJ equation are convex, and can be written as a set of linear inequalities. We use this fact to pose various (and seemingly unrelated) estimation problems related to traffic flow-engineering as a set of linear programs. In particular, we solve data assimilation and data reconciliation problems for estimating the state of a system when the model and measurement constraints are incompatible. We also solve traffic estimation problems, such as travel time estimation or density estimation. For all these problems, a numerical implementation is performed using experimental data from the Mobile Century experiment. In the context of reproducible research, the code and data used to compute the results presented in this brief have been posted online and are accessible to regenerate the results. © 2013 IEEE.
LPmerge: an R package for merging genetic maps by linear programming.
Endelman, Jeffrey B; Plomion, Christophe
2014-06-01
Consensus genetic maps constructed from multiple populations are an important resource for both basic and applied research, including genome-wide association analysis, genome sequence assembly and studies of evolution. The LPmerge software uses linear programming to efficiently minimize the mean absolute error between the consensus map and the linkage maps from each population. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts. LPmerge is on CRAN at http://cran.r-project.org/web/packages/LPmerge. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
A primal-dual exterior point algorithm for linear programming problems
Directory of Open Access Journals (Sweden)
Samaras Nikolaos
2009-01-01
Full Text Available The aim of this paper is to present a new simplex type algorithm for the Linear Programming Problem. The Primal - Dual method is a Simplex - type pivoting algorithm that generates two paths in order to converge to the optimal solution. The first path is primal feasible while the second one is dual feasible for the original problem. Specifically, we use a three-phase-implementation. The first two phases construct the required primal and dual feasible solutions, using the Primal Simplex algorithm. Finally, in the third phase the Primal - Dual algorithm is applied. Moreover, a computational study has been carried out, using randomly generated sparse optimal linear problems, to compare its computational efficiency with the Primal Simplex algorithm and also with MATLAB's Interior Point Method implementation. The algorithm appears to be very promising since it clearly shows its superiority to the Primal Simplex algorithm as well as its robustness over the IPM algorithm.
Katz, Josh M; Winter, Carl K; Buttrey, Samuel E; Fadel, James G
2012-03-01
Western and guideline based diets were compared to determine if dietary improvements resulting from following dietary guidelines reduce acrylamide intake. Acrylamide forms in heat treated foods and is a human neurotoxin and animal carcinogen. Acrylamide intake from the Western diet was estimated with probabilistic techniques using teenage (13-19 years) National Health and Nutrition Examination Survey (NHANES) food consumption estimates combined with FDA data on the levels of acrylamide in a large number of foods. Guideline based diets were derived from NHANES data using linear programming techniques to comport to recommendations from the Dietary Guidelines for Americans, 2005. Whereas the guideline based diets were more properly balanced and rich in consumption of fruits, vegetables, and other dietary components than the Western diets, acrylamide intake (mean±SE) was significantly greater (Plinear programming and results demonstrate that linear programming techniques can be used to model specific diets for the assessment of toxicological and nutritional dietary components. Copyright Â© 2011 Elsevier Ltd. All rights reserved.
Oktem, Figen S; Ozaktas, Haldun M
2010-08-01
Linear canonical transforms (LCTs) form a three-parameter family of integral transforms with wide application in optics. We show that LCT domains correspond to scaled fractional Fourier domains and thus to scaled oblique axes in the space-frequency plane. This allows LCT domains to be labeled and ordered by the corresponding fractional order parameter and provides insight into the evolution of light through an optical system modeled by LCTs. If a set of signals is highly confined to finite intervals in two arbitrary LCT domains, the space-frequency (phase space) support is a parallelogram. The number of degrees of freedom of this set of signals is given by the area of this parallelogram, which is equal to the bicanonical width product but usually smaller than the conventional space-bandwidth product. The bicanonical width product, which is a generalization of the space-bandwidth product, can provide a tighter measure of the actual number of degrees of freedom, and allows us to represent and process signals with fewer samples.
International Nuclear Information System (INIS)
Assmann, R.; Adolphsen, C.; Bane, K.; Raubenheimer, T.O.; Siemann, R.; Thompson, K.
1996-09-01
Linear accelerators are the central components of the proposed next generation of linear colliders. They need to provide acceleration of up to 750 GeV per beam while maintaining very small normalized emittances. Standard simulation programs, mainly developed for storage rings, do not meet the specific requirements for high energy linear accelerators. The authors present a new program LIAR (LInear Accelerator Research code) that includes wakefield effects, a 4D coupled beam description, specific optimization algorithms and other advanced features. Its modular structure allows to use and to extend it easily for different purposes. They present examples of simulations for SLC and NLC
Frega, Romeo; Lanfranco, Jose Guerra; De Greve, Sam; Bernardini, Sara; Geniez, Perrine; Grede, Nils; Bloem, Martin; de Pee, Saskia
2012-09-01
Linear programming has been used for analyzing children's complementary feeding diets, for optimizing nutrient adequacy of dietary recommendations for a population, and for estimating the economic value of fortified foods. To describe and apply a linear programming tool ("Cost of the Diet") with data from Mozambique to determine what could be cost-effective fortification strategies. Based on locally assessed average household dietary needs, seasonal market prices of available food products, and food composition data, the tool estimates the lowest-cost diet that meets almost all nutrient needs. The results were compared with expenditure data from Mozambique to establish the affordability of this diet by quintiles of the population. Three different applications were illustrated: identifying likely "limiting nutrients," comparing cost effectiveness of different fortification interventions at the household level, and assessing economic access to nutritious foods. The analysis identified iron, vitamin B2, and pantothenic acid as "limiting nutrients." Under the Mozambique conditions, vegetable oil was estimated as a more cost-efficient vehicle for vitamin A fortification than sugar; maize flour may also be an effective vehicle to provide other constraining micronutrients. Multiple micronutrient fortification of maize flour could reduce the cost of the "lowest-cost nutritious diet" by 18%, but even this diet can be afforded by only 20% of the Mozambican population. Within the context of fortification, linear programming can be a useful tool for identifying likely nutrient inadequacies, for comparing fortification options in terms of cost effectiveness, and for illustrating the potential benefit of fortification for improving household access to a nutritious diet.
INFORMATION SECURITY RISKS OPTIMIZATION IN CLOUDY SERVICES ON THE BASIS OF LINEAR PROGRAMMING
Directory of Open Access Journals (Sweden)
I. A. Zikratov
2013-01-01
Full Text Available The paper discusses theoretical aspects of secure cloud services creation for information processing of various confidentiality degrees. A new approach to the reasoning of information security composition in distributed computing structures is suggested, presenting the problem of risk assessment as an extreme problem of decisionmaking. Linear programming method application is proved to minimize the risk of information security for given performance security in compliance with the economic balance for the maintenance of security facilities and cost of services. An example is given to illustrate the obtained theoretical results.
An improved multiple linear regression and data analysis computer program package
Sidik, S. M.
1972-01-01
NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.
Reactor Network Synthesis Using Coupled Genetic Algorithm with the Quasi-linear Programming Method
Soltani, H.; Shafiei, S.; Edraki, J.
2016-01-01
This research is an attempt to develop a new procedure for the synthesis of reactor networks (RNs) using a genetic algorithm (GA) coupled with the quasi-linear programming (LP) method. The GA is used to produce structural configuration, whereas continuous variables are handled using a quasi-LP formulation for finding the best objective function. Quasi-LP consists of LP together with a search loop to find the best reactor conversions (xi), as well as split and recycle ratios (yi). Quasi-LP rep...
International Nuclear Information System (INIS)
Sun Wei; Huang, Guo H.; Lv Ying; Li Gongchen
2012-01-01
Highlights: ► Inexact piecewise-linearization-based fuzzy flexible programming is proposed. ► It’s the first application to waste management under multiple complexities. ► It tackles nonlinear economies-of-scale effects in interval-parameter constraints. ► It estimates costs more accurately than the linear-regression-based model. ► 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 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
Fleming, P.
1983-01-01
A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a nonlinear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer. One concerns helicopter longitudinal dynamics and the other the flight dynamics of an aerodynamically unstable aircraft.
Directory of Open Access Journals (Sweden)
Darunee Hunwisai
2017-01-01
Full Text Available In this work, we considered two-person zero-sum games with fuzzy payoffs and matrix games with payoffs of trapezoidal intuitionistic fuzzy numbers (TrIFNs. The concepts of TrIFNs and their arithmetic operations were used. The cut-set based method for matrix game with payoffs of TrIFNs was also considered. Compute the interval-type value of any alfa-constrategies by simplex method for linear programming. The proposed method is illustrated with a numerical example.
International Nuclear Information System (INIS)
Kato, K.; Ihara, S.
1993-01-01
Hydrogen is expected to be an important energy carrier, especially in the frame of global warming problem solution. The purpose of this study is to examine the condition of market penetration of hydrogen technologies in reducing CO 2 emissions. A multi-time-period linear programming model (MARKAL, Market Allocation)) is used to explore technology options and cost for meeting the energy demands while reducing CO 2 emissions from energy systems. The results show that hydrogen technologies become economical when CO 2 emissions are stringently constrained. 9 figs., 2 refs
The evaluation of multi-element personal dosemeters using the linear programming method
International Nuclear Information System (INIS)
Kragh, P.; Ambrosi, P.; Boehm, J.; Hilgers, G.
1996-01-01
Multi-element dosemeters are frequently used in individual monitoring. Each element can be regarded as an individual dosemeter with its own individual dose measurement value. In general, the individual dose values of one dosemeter vary according to the exposure conditions, i. e. the energy and angle of incidence of the radiation. The (final) dose measurement value of the personal dosemeter is calculated from the individual dose values by means of an evaluation algorithm. The best possible dose value, i.e. that of the smallest systematic (type B) uncertainty if the exposure conditions are changed in the dosemeter's rated range of use, is obtained by the method of linear programming. (author)
Energy Technology Data Exchange (ETDEWEB)
Dufour, F., E-mail: dufour@math.u-bordeaux1.fr [Institut de Mathématiques de Bordeaux, INRIA Bordeaux Sud Ouest, Team: CQFD, and IMB (France); Prieto-Rumeau, T., E-mail: tprieto@ccia.uned.es [UNED, Department of Statistics and Operations Research (Spain)
2016-08-15
We consider a discrete-time constrained discounted Markov decision process (MDP) with Borel state and action spaces, compact action sets, and lower semi-continuous cost functions. We introduce a set of hypotheses related to a positive weight function which allow us to consider cost functions that might not be bounded below by a constant, and which imply the solvability of the linear programming formulation of the constrained MDP. In particular, we establish the existence of a constrained optimal stationary policy. Our results are illustrated with an application to a fishery management problem.
Directory of Open Access Journals (Sweden)
Sukhpreet Kaur Sidhu
2014-01-01
Full Text Available The drawbacks of the existing methods to obtain the fuzzy optimal solution of such linear programming problems, in which coefficients of the constraints are represented by real numbers and all the other parameters as well as variables are represented by symmetric trapezoidal fuzzy numbers, are pointed out, and to resolve these drawbacks, a new method (named as Mehar method is proposed for the same linear programming problems. Also, with the help of proposed Mehar method, a new method, much easy as compared to the existing methods, is proposed to deal with the sensitivity analysis of the same type of linear programming problems.
DEFF Research Database (Denmark)
Parlesak, A.; Tetens, Inge; Dejgård Jensen, Jørgen
2016-01-01
programming. The FBs were defined using five different constraints: cultural acceptability (CA), or dietary guidelines (DG), or nutrient recommendations (N), or cultural acceptability and nutrient recommendations (CAN), or dietary guidelines and nutrient recommendations (DGN). The variety and number of foods...... in each of the resulting five baskets was increased through limiting the relative share of individual foods. The one-day version of N contained only 12 foods at the minimum cost of DKK 27 (€ 3.6). The CA, DG, and DGN were about twice of this and the CAN cost ~DKK 81 (€ 10.8). The baskets with the greater...... variety of foods contained from 70 (CAN) to 134 (DGN) foods and cost between DKK 60 (€ 8.1, N) and DKK 125 (€ 16.8, DGN). Ensuring that the food baskets cover both dietary guidelines and nutrient recommendations doubled the cost while cultural acceptability (CAN) tripled it. Use of linear programming...
Consideration in selecting crops for the human-rated life support system: a Linear Programming model
Wheeler, E. F.; Kossowski, J.; Goto, E.; Langhans, R. W.; White, G.; Albright, L. D.; Wilcox, D.; Henninger, D. L. (Principal Investigator)
1996-01-01
A Linear Programming model has been constructed which aids in selecting appropriate crops for CELSS (Controlled Environment Life Support System) food production. A team of Controlled Environment Agriculture (CEA) faculty, staff, graduate students and invited experts representing more than a dozen disciplines, provided a wide range of expertise in developing the model and the crop production program. The model incorporates nutritional content and controlled-environment based production yields of carefully chosen crops into a framework where a crop mix can be constructed to suit the astronauts' needs. The crew's nutritional requirements can be adequately satisfied with only a few crops (assuming vitamin mineral supplements are provided) but this will not be satisfactory from a culinary standpoint. This model is flexible enough that taste and variety driven food choices can be built into the model.
International Nuclear Information System (INIS)
Saminadayar, L.
2001-01-01
20 years ago fractional charges were imagined to explain values of conductivity in some materials. Recent experiments have proved the existence of charges whose value is the third of the electron charge. This article presents the experimental facts that have led theorists to predict the existence of fractional charges from the motion of quasi-particles in a linear chain of poly-acetylene to the quantum Hall effect. According to the latest theories, fractional charges are neither bosons nor fermions but anyons, they are submitted to an exclusive principle that is less stringent than that for fermions. (A.C.)
Averaging and Linear Programming in Some Singularly Perturbed Problems of Optimal Control
Energy Technology Data Exchange (ETDEWEB)
Gaitsgory, Vladimir, E-mail: vladimir.gaitsgory@mq.edu.au [Macquarie University, Department of Mathematics (Australia); Rossomakhine, Sergey, E-mail: serguei.rossomakhine@flinders.edu.au [Flinders University, Flinders Mathematical Sciences Laboratory, School of Computer Science, Engineering and Mathematics (Australia)
2015-04-15
The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite time horizon. We mostly focus on problems with time discounting criteria but a possibility of the extension of results to periodic optimization problems is discussed as well. Our consideration is based on earlier results on averaging of SP control systems and on linear programming formulations of optimal control problems. The idea that we exploit is to first asymptotically approximate a given problem of optimal control of the SP system by a certain averaged optimal control problem, then reformulate this averaged problem as an infinite-dimensional linear programming (LP) problem, and then approximate the latter by semi-infinite LP problems. We show that the optimal solution of these semi-infinite LP problems and their duals (that can be found with the help of a modification of an available LP software) allow one to construct near optimal controls of the SP system. We demonstrate the construction with two numerical examples.
Energy Technology Data Exchange (ETDEWEB)
Djukanovic, M.; Babic, B.; Milosevic, B. [Electrical Engineering Inst. Nikola Tesla, Belgrade (Yugoslavia); Sobajic, D.J. [EPRI, Palo Alto, CA (United States). Power System Control; Pao, Y.H. [Case Western Reserve Univ., Cleveland, OH (United States)]|[AI WARE, Inc., Cleveland, OH (United States)
1996-05-01
In this paper the blending/transloading facilities are modeled using an interactive fuzzy linear programming (FLP), in order to allow the decision-maker to solve the problem of uncertainty of input information within the fuel scheduling optimization. An interactive decision-making process is formulated in which decision-maker can learn to recognize good solutions by considering all possibilities of fuzziness. The application of the fuzzy formulation is accompanied by a careful examination of the definition of fuzziness, appropriateness of the membership function and interpretation of results. The proposed concept provides a decision support system with integration-oriented features, whereby the decision-maker can learn to recognize the relative importance of factors in the specific domain of optimal fuel scheduling (OFS) problem. The formulation of a fuzzy linear programming problem to obtain a reasonable nonfuzzy solution under consideration of the ambiguity of parameters, represented by fuzzy numbers, is introduced. An additional advantage of the FLP formulation is its ability to deal with multi-objective problems.
Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri
2016-01-01
This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.
Li, Yanning
2013-10-01
This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.
International Nuclear Information System (INIS)
Shimizu, Yoshiaki
1988-01-01
Due to the simplicity and effectiveness, linear program has been popular in the actual optimization in various fields. In the previous study, the uncertainty involved in the model at the different stage of optimization was dealt with by post-optimizing analysis. But it often becomes insufficient to make a decision how to deal with an uncertain system especially suffering large parameter deviation. Recently in the field of processing systems, it is desired to obtain a flexible solution which can present the counterplan to a deviating system from a practical viewpoint. The scope of this preliminary note presents how to apply a methodology development to obtain the flexible solution of a linear program. For this purpose, a simple example associated with nuclear reactor decommissioning is shown. The problem to maximize a system performance given as an objective function under the constraint of the static behavior of the system is considered, and the flexible solution is determined. In Japan, the decommissioning of commercial nuclear power plants will being in near future, and the study using the retired research reactor JPDR is in progress. The planning of decontamination and the reuse of wastes is taken as the example. (Kako, I.)
Li, Yanning; Canepa, Edward S.; Claudel, Christian G.
2013-01-01
This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.
A novel approach based on preference-based index for interval bilevel linear programming problem.
Ren, Aihong; Wang, Yuping; Xue, Xingsi
2017-01-01
This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation [Formula: see text]. Furthermore, the concept of a preference δ -optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.
A novel approach based on preference-based index for interval bilevel linear programming problem
Directory of Open Access Journals (Sweden)
Aihong Ren
2017-05-01
Full Text Available Abstract This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation ⪯ m w $\\preceq_{mw}$ . Furthermore, the concept of a preference δ-optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.
DEFF Research Database (Denmark)
Escudero, Laureano F.; Monge, Juan Francisco; Morales, Dolores Romero
2015-01-01
In this paper we consider multiperiod mixed 0–1 linear programming models under uncertainty. We propose a risk averse strategy using stochastic dominance constraints (SDC) induced by mixed-integer linear recourse as the risk measure. The SDC strategy extends the existing literature to the multist...
Nakhanu, Shikuku Beatrice; Musasia, Amadalo Maurice
2015-01-01
The topic Linear Programming is included in the compulsory Kenyan secondary school mathematics curriculum at form four. The topic provides skills for determining best outcomes in a given mathematical model involving some linear relationship. This technique has found application in business, economics as well as various engineering fields. Yet many…
Heart failure with preserved ejection fraction in women : The dutch queen of hearts program
den Ruijter, H.; Pasterkamp, G.; Rutten, F. H.; Lam, C. S P; Chi, C.; Tan, K. H.; van Zonneveld, A. J.; Spaanderman, M.; de Kleijn, D. P V
2015-01-01
Heart failure (HF) poses a heavy burden on patients, their families and society. The syndrome of HF comes in two types: with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF). The latter is on the increase and predominantly present in women, especially the older ones. There
Aihong Ren
2016-01-01
This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solut...
Fractional Programming for Communication Systems—Part II: Uplink Scheduling via Matching
Shen, Kaiming; Yu, Wei
2018-05-01
This two-part paper develops novel methodologies for using fractional programming (FP) techniques to design and optimize communication systems. Part I of this paper proposes a new quadratic transform for FP and treats its application for continuous optimization problems. In this Part II of the paper, we study discrete problems, such as those involving user scheduling, which are considerably more difficult to solve. Unlike the continuous problems, discrete or mixed discrete-continuous problems normally cannot be recast as convex problems. In contrast to the common heuristic of relaxing the discrete variables, this work reformulates the original problem in an FP form amenable to distributed combinatorial optimization. The paper illustrates this methodology by tackling the important and challenging problem of uplink coordinated multi-cell user scheduling in wireless cellular systems. Uplink scheduling is more challenging than downlink scheduling, because uplink user scheduling decisions significantly affect the interference pattern in nearby cells. Further, the discrete scheduling variable needs to be optimized jointly with continuous variables such as transmit power levels and beamformers. The main idea of the proposed FP approach is to decouple the interaction among the interfering links, thereby permitting a distributed and joint optimization of the discrete and continuous variables with provable convergence. The paper shows that the well-known weighted minimum mean-square-error (WMMSE) algorithm can also be derived from a particular use of FP; but our proposed FP-based method significantly outperforms WMMSE when discrete user scheduling variables are involved, both in term of run-time efficiency and optimizing results.
International Nuclear Information System (INIS)
Fernandes, Marco A.R.; Fernandes, David M.; Florentino, Helenice O.
2010-01-01
The work detaches the importance of the use of mathematical tools and computer systems for optimization of the planning in radiotherapy, seeking to the distribution of dose of appropriate radiation in the white volume that provides an ideal therapeutic rate between the tumor cells and the adjacent healthy tissues, extolled in the radiotherapy protocols. Examples of target volumes mathematically modeled are analyzed with the technique of linear programming, comparing the obtained results using the Simplex algorithm with those using the algorithm of Interior Points. The System Genesis II was used for obtaining of the isodose curves for the outline and geometry of fields idealized in the computer simulations, considering the parameters of a 10 MV photons beams. Both programming methods (Simplex and Interior Points) they resulted in a distribution of integral dose in the tumor volume and allow the adaptation of the dose in the critical organs inside of the restriction limits extolled. The choice of an or other method should take into account the facility and the need of limiting the programming time. The isodose curves, obtained with the Genesis II System, illustrate that the adjacent healthy tissues to the tumor receives larger doses than those reached in the computer simulations. More coincident values can be obtained altering the weights and some factors of minimization of the objective function. The prohibitive costs of the computer planning systems, at present available for radiotherapy, it motivates the researches to look for the implementation of simpler and so effective methods for optimization of the treatment plan. (author)
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Frison, Gianluca; Skajaa, Anders
2015-01-01
We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear...... system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that 1) the proposed algorithm...
Young, Katherine C.; Sobieszczanski-Sobieski, Jaroslaw
1988-01-01
This project has two objectives. The first is to determine whether linear programming techniques can improve performance when handling design optimization problems with a large number of design variables and constraints relative to the feasible directions algorithm. The second purpose is to determine whether using the Kreisselmeier-Steinhauser (KS) function to replace the constraints with one constraint will reduce the cost of total optimization. Comparisons are made using solutions obtained with linear and non-linear methods. The results indicate that there is no cost saving using the linear method or in using the KS function to replace constraints.
Czech Academy of Sciences Publication Activity Database
Plocková, Jana; Chmelík, Josef
2001-01-01
Roč. 918, č. 2 (2001), s. 361-370 ISSN 0021-9673 R&D Projects: GA AV ČR IAA4031805 Institutional research plan: CEZ:AV0Z4031919 Keywords : field-flow fractionation * field programming * flow-rate gradients Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 2.793, year: 2001
Czech Academy of Sciences Publication Activity Database
Plocková, Jana; Matulík, František; Chmelík, Josef
2002-01-01
Roč. 955, č. 1 (2002), s. 95-103 ISSN 0021-9673 R&D Projects: GA AV ČR IAA4031805 Institutional research plan: CEZ:AV0Z4031919 Keywords : gravitational field-flow fractionation * field programming * hydrodynamic lift forces Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 3.098, year: 2002
Ghadie, Mohamed A; Japkowicz, Nathalie; Perkins, Theodore J
2015-08-15
Stem cell differentiation is largely guided by master transcriptional regulators, but it also depends on the expression of other types of genes, such as cell cycle genes, signaling genes, metabolic genes, trafficking genes, etc. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can group cell types based on gene expression, but they do so without knowledge of the differentiation hierarchy. Hierarchical clustering can organize cell types into a tree, but in general this tree is different from the differentiation hierarchy itself. Given the differentiation hierarchy and gene expression data at each node, we construct a weighted Euclidean distance metric such that the minimum spanning tree with respect to that metric is precisely the given differentiation hierarchy. We provide a set of linear constraints that are provably sufficient for the desired construction and a linear programming approach to identify sparse sets of weights, effectively identifying genes that are most relevant for discriminating different parts of the tree. We apply our method to microarray gene expression data describing 38 cell types in the hematopoiesis hierarchy, constructing a weighted Euclidean metric that uses just 175 genes. However, we find that there are many alternative sets of weights that satisfy the linear constraints. Thus, in the style of random-forest training, we also construct metrics based on random subsets of the genes and compare them to the metric of 175 genes. We then report on the selected genes and their biological functions. Our approach offers a new way to identify genes that may have important roles in stem cell differentiation. tperkins@ohri.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
International Nuclear Information System (INIS)
De Donato, O.; Parisi, M.A.
1977-01-01
When loads increase proportionally beyond the elastic limit in the presence of elastic-plastic piecewise-linear constitutive laws, the problem of finding the whole evolution of the plastic strain and displacements of structures was recently shown to be amenable to a parametric linear complementary problem (PLCP) in which the parameter is represented by the load factor, the matrix is symmetric positive definite or at least semi-definite (for perfect plasticity) and the variables with a direct mechanical meaning are the plastic multipliers. With reference to plane trusses and frames with elastic-plastic linear work-hardening material behaviour numerical solutions were also fairly efficiently obtained using a recent mathematical programming algorithm (due to R.W. Cottle) which is able to provide the whole deformation history of the structure and, at the same time to rule out local unloadings along the given proportional loading process by means of 'a priori' checks carried out before each pivotal step of the procedure. Hence it becomes possible to use the holonomic (reversible, path-independent) constitutive laws in finite terms and to benefit by all the relevant numerical and computational advantages despite the non-holonomic nature of plastic behaviour. In the present paper the method of solution is re-examined in view to overcome an important drawback of the algorithm deriving from the size of PLCP fully populated matrix when structural problems with large number of variables are considered and, consequently, the updating, the storing or, generally, the handling of the current tableau may become prohibitive. (Auth.)
Linear programming optimization of nuclear energy strategy with sodium-cooled fast reactors
International Nuclear Information System (INIS)
Lee, Je Whan; Jeong, Yong Hoon; Chang, Yoon Il; Chang, Soon Heung
2011-01-01
Nuclear power has become an essential part of electricity generation to meet the continuous growth of electricity demand. A Sodium-cooled Fast Reactor (SFR) was developed to extend uranium resource utilization under a growing nuclear energy scenario while concomitantly providing a nuclear waste management solution. Key questions in this scenario are when to introduce SFRs and how many reactors should be introduced. In this study, a methodology using Linear Programming is employed in order to quantify an optimized growth pattern of a nuclear energy system comprising light water reactors and SFRs. The optimization involves tradeoffs between SFR capital cost premiums and the total system U3O8 price premiums. Optimum nuclear growth patterns for several scenarios are presented, as well as sensitivity analyses of important input parameters
A linear goal programming model for urban energy-economy-environment interaction
Energy Technology Data Exchange (ETDEWEB)
Kambo, N.S.; Handa, B.R. (Indian Inst. of Tech., New Delhi (India). Dept. of Mathematics); Bose, R.K. (Tata Energy Research Inst., New Delhi (India))
1991-01-01
This paper provides a comprehensive and systematic analysis of energy and pollution problems interconnected with the economic structure, by using a multi-objective sectoral end-use model for addressing regional energy policy issues. The multi-objective model proposed for the study is a 'linear goal programming (LGP)' technique of analysing a 'reference energy system (RES)' in a framework within which alternative policies and technical strategies may be evaluated. The model so developed has further been tested for the city of Delhi (India) for the period 1985 - 86, and a scenario analysis has been carried out by assuming different policy options. (orig./BWJ).
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
Energy Technology Data Exchange (ETDEWEB)
Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)
2015-01-15
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Highlights of the SLD Physics Program at the SLAC Linear Collider
International Nuclear Information System (INIS)
Willocq, Stephane
2001-01-01
Starting in 1989, and continuing through the 1990s, high-energy physics witnessed a flowering of precision measurements in general and tests of the standard model in particular, led by e + e - collider experiments operating at the Z 0 resonance. Key contributions to this work came from the SLD collaboration at the SLAC Linear Collider. By exploiting the unique capabilities of this pioneering accelerator and the SLD detector, including a polarized electron beam, exceptionally small beam dimensions, and a CCD pixel vertex detector, SLD produced a broad array of electroweak, heavy-flavor, and QCD measurements. Many of these results are one of a kind or represent the world's standard in precision. This article reviews the highlights of the SLD physics program, with an eye toward associated advances in experimental technique, and the contribution of these measurements to our dramatically improved present understanding of the standard model and its possible extensions
Decomposition and (importance) sampling techniques for multi-stage stochastic linear programs
Energy Technology Data Exchange (ETDEWEB)
Infanger, G.
1993-11-01
The difficulty of solving large-scale multi-stage stochastic linear programs arises from the sheer number of scenarios associated with numerous stochastic parameters. The number of scenarios grows exponentially with the number of stages and problems get easily out of hand even for very moderate numbers of stochastic parameters per stage. Our method combines dual (Benders) decomposition with Monte Carlo sampling techniques. We employ importance sampling to efficiently obtain accurate estimates of both expected future costs and gradients and right-hand sides of cuts. The method enables us to solve practical large-scale problems with many stages and numerous stochastic parameters per stage. We discuss the theory of sharing and adjusting cuts between different scenarios in a stage. We derive probabilistic lower and upper bounds, where we use importance path sampling for the upper bound estimation. Initial numerical results turned out to be promising.
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
International Nuclear Information System (INIS)
Hirata, Yoshito; Aihara, Kazuyuki; Suzuki, Hideyuki; Shiro, Masanori; Takahashi, Nozomu; Mas, Paloma
2015-01-01
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data
Impulsive Control for Continuous-Time Markov Decision Processes: A Linear Programming Approach
Energy Technology Data Exchange (ETDEWEB)
Dufour, F., E-mail: dufour@math.u-bordeaux1.fr [Bordeaux INP, IMB, UMR CNRS 5251 (France); Piunovskiy, A. B., E-mail: piunov@liv.ac.uk [University of Liverpool, Department of Mathematical Sciences (United Kingdom)
2016-08-15
In this paper, we investigate an optimization problem for continuous-time Markov decision processes with both impulsive and continuous controls. We consider the so-called constrained problem where the objective of the controller is to minimize a total expected discounted optimality criterion associated with a cost rate function while keeping other performance criteria of the same form, but associated with different cost rate functions, below some given bounds. Our model allows multiple impulses at the same time moment. The main objective of this work is to study the associated linear program defined on a space of measures including the occupation measures of the controlled process and to provide sufficient conditions to ensure the existence of an optimal control.
A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems.
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.
Xia, Bisheng; Qian, Xin; Yao, Hong
2017-11-01
Although the risk-explicit interval linear programming (REILP) model has solved the problem of having interval solutions, it has an equity problem, which can lead to unbalanced allocation between different decision variables. Therefore, an improved REILP model is proposed. This model adds an equity objective function and three constraint conditions to overcome this equity problem. In this case, pollution reduction is in proportion to pollutant load, which supports balanced development between different regional economies. The model is used to solve the problem of pollution load allocation in a small transboundary watershed. Compared with the REILP original model result, our model achieves equity between the upstream and downstream pollutant loads; it also overcomes the problem of greatest pollution reduction, where sources are nearest to the control section. The model provides a better solution to the problem of pollution load allocation than previous versions.
Approximating high-dimensional dynamics by barycentric coordinates with linear programming.
Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma
2015-01-01
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
A minimax technique for time-domain design of preset digital equalizers using linear programming
Vaughn, G. L.; Houts, R. C.
1975-01-01
A linear programming technique is presented for the design of a preset finite-impulse response (FIR) digital filter to equalize the intersymbol interference (ISI) present in a baseband channel with known impulse response. A minimax technique is used which minimizes the maximum absolute error between the actual received waveform and a specified raised-cosine waveform. Transversal and frequency-sampling FIR digital filters are compared as to the accuracy of the approximation, the resultant ISI and the transmitted energy required. The transversal designs typically have slightly better waveform accuracy for a given distortion; however, the frequency-sampling equalizer uses fewer multipliers and requires less transmitted energy. A restricted transversal design is shown to use the least number of multipliers at the cost of a significant increase in energy and loss of waveform accuracy at the receiver.
Highlights of the SLD Physics Program at the SLAC Linear Collider
Energy Technology Data Exchange (ETDEWEB)
Willocq, Stephane
2001-09-07
Starting in 1989, and continuing through the 1990s, high-energy physics witnessed a flowering of precision measurements in general and tests of the standard model in particular, led by e{sup +}e{sup -} collider experiments operating at the Z{sup 0} resonance. Key contributions to this work came from the SLD collaboration at the SLAC Linear Collider. By exploiting the unique capabilities of this pioneering accelerator and the SLD detector, including a polarized electron beam, exceptionally small beam dimensions, and a CCD pixel vertex detector, SLD produced a broad array of electroweak, heavy-flavor, and QCD measurements. Many of these results are one of a kind or represent the world's standard in precision. This article reviews the highlights of the SLD physics program, with an eye toward associated advances in experimental technique, and the contribution of these measurements to our dramatically improved present understanding of the standard model and its possible extensions.
Zenis, F. M.; Supian, S.; Lesmana, E.
2018-03-01
Land is one of the most important assets for farmers in Sumedang Regency. Therefore, agricultural land should be used optimally. This study aims to obtain the optimal land use composition in order to obtain maximum income. The optimization method used in this research is Linear Programming Models. Based on the results of the analysis, the composition of land use for rice area of 135.314 hectares, corn area of 11.798 hectares, soy area of 2.290 hectares, and peanuts of 2.818 hectares with the value of farmers income of IDR 2.682.020.000.000,-/year. The results of this analysis can be used as a consideration in decisions making about cropping patterns by farmers.
Directory of Open Access Journals (Sweden)
Tumpal Sihombing
2013-01-01
Full Text Available The world is entering the era of recession when the trend is bearish and market is not so favorable. The capital markets in every major country were experiencing great amount of loss and people suffered in their investment. The Jakarta Composite Index (JCI has shown a great downturn for the past one year but the trend bearish year of the JCI. Therefore, rational investors should consider restructuring their portfolio to set bigger proportion in bonds and cash instead of stocks. Investors can apply modern portfolio theory by Harry Markowitz to find the optimum asset allocation for their portfolio. Higher return is always associated with higher risk. This study shows investors how to find out the lowest risk of a portfolio investment by providing them with several structures of portfolio weighting. By this way, investor can compare and make the decision based on risk-return consideration and opportunity cost as well. Keywords: Modern portfolio theory, Monte Carlo, linear programming
Optimisation of substrate blends in anaerobic co-digestion using adaptive linear programming.
García-Gen, Santiago; Rodríguez, Jorge; Lema, Juan M
2014-12-01
Anaerobic co-digestion of multiple substrates has the potential to enhance biogas productivity by making use of the complementary characteristics of different substrates. A blending strategy based on a linear programming optimisation method is proposed aiming at maximising COD conversion into methane, but simultaneously maintaining a digestate and biogas quality. The method incorporates experimental and heuristic information to define the objective function and the linear restrictions. The active constraints are continuously adapted (by relaxing the restriction boundaries) such that further optimisations in terms of methane productivity can be achieved. The feasibility of the blends calculated with this methodology was previously tested and accurately predicted with an ADM1-based co-digestion model. This was validated in a continuously operated pilot plant, treating for several months different mixtures of glycerine, gelatine and pig manure at organic loading rates from 1.50 to 4.93 gCOD/Ld and hydraulic retention times between 32 and 40 days at mesophilic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.
Linear programming: an alternative approach for developing formulations for emergency food products.
Sheibani, Ershad; Dabbagh Moghaddam, Arasb; Sharifan, Anousheh; Afshari, Zahra
2018-03-01
To minimize the mortality rates of individuals affected by disasters, providing high-quality food relief during the initial stages of an emergency is crucial. The goal of this study was to develop a formulation for a high-energy, nutrient-dense prototype using linear programming (LP) model as a novel method for developing formulations for food products. The model consisted of the objective function and the decision variables, which were the formulation costs and weights of the selected commodities, respectively. The LP constraints were the Institute of Medicine and the World Health Organization specifications of the content of nutrients in the product. Other constraints related to the product's sensory properties were also introduced to the model. Nonlinear constraints for energy ratios of nutrients were linearized to allow their use in the LP. Three focus group studies were conducted to evaluate the palatability and other aspects of the optimized formulation. New constraints were introduced to the LP model based on the focus group evaluations to improve the formulation. LP is an appropriate tool for designing formulations of food products to meet a set of nutritional requirements. This method is an excellent alternative to the traditional 'trial and error' method in designing formulations. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.
Baran, Richard; Northen, Trent R
2013-10-15
Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.
Directory of Open Access Journals (Sweden)
Maoyuan Feng
2014-01-01
Full Text Available This study proposes a mixed integer linear programming (MILP model to optimize the spillways scheduling for reservoir flood control. Unlike the conventional reservoir operation model, the proposed MILP model specifies the spillways status (including the number of spillways to be open and the degree of the spillway opened instead of reservoir release, since the release is actually controlled by using the spillway. The piecewise linear approximation is used to formulate the relationship between the reservoir storage and water release for a spillway, which should be open/closed with a status depicted by a binary variable. The control order and symmetry rules of spillways are described and incorporated into the constraints for meeting the practical demand. Thus, a MILP model is set up to minimize the maximum reservoir storage. The General Algebraic Modeling System (GAMS and IBM ILOG CPLEX Optimization Studio (CPLEX software are used to find the optimal solution for the proposed MILP model. The China’s Three Gorges Reservoir, whose spillways are of five types with the total number of 80, is selected as the case study. It is shown that the proposed model decreases the flood risk compared with the conventional operation and makes the operation more practical by specifying the spillways status directly.
Directory of Open Access Journals (Sweden)
Bo Zhang
2016-01-01
Full Text Available This paper presents a model for analyzing a five-phase fractional-slot permanent magnet tubular linear motor (FSPMTLM with the modified winding function approach (MWFA. MWFA is a fast modeling method and it gives deep insight into the calculations of the following parameters: air-gap magnetic field, inductances, flux linkages, and detent force, which are essential in modeling the motor. First, using a magnetic circuit model, the air-gap magnetic density is computed from stator magnetomotive force (MMF, flux barrier, and mover geometry. Second, the inductances, flux linkages, and detent force are analytically calculated using modified winding function and the air-gap magnetic density. Finally, a model has been established with the five-phase Park transformation and simulated. The calculations of detent force reveal that the end-effect force is the main component of the detent force. This is also proven by finite element analysis on the motor. The accuracy of the model is validated by comparing with the results obtained using semianalytical method (SAM and measurements to analyze the motor’s transient characteristics. In addition, the proposed method requires less computation time.
Directory of Open Access Journals (Sweden)
Guan Yu
Full Text Available Accurately identifying mild cognitive impairment (MCI individuals who will progress to Alzheimer's disease (AD is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI and fluorodeoxyglucose positron emission tomography (FDG-PET. However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI subjects and 226 stable MCI (sMCI subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images and also the single-task classification method (using only MRI or only subjects with both MRI and
PAPR reduction in FBMC using an ACE-based linear programming optimization
van der Neut, Nuan; Maharaj, Bodhaswar TJ; de Lange, Frederick; González, Gustavo J.; Gregorio, Fernando; Cousseau, Juan
2014-12-01
This paper presents four novel techniques for peak-to-average power ratio (PAPR) reduction in filter bank multicarrier (FBMC) modulation systems. The approach extends on current PAPR reduction active constellation extension (ACE) methods, as used in orthogonal frequency division multiplexing (OFDM), to an FBMC implementation as the main contribution. The four techniques introduced can be split up into two: linear programming optimization ACE-based techniques and smart gradient-project (SGP) ACE techniques. The linear programming (LP)-based techniques compensate for the symbol overlaps by utilizing a frame-based approach and provide a theoretical upper bound on achievable performance for the overlapping ACE techniques. The overlapping ACE techniques on the other hand can handle symbol by symbol processing. Furthermore, as a result of FBMC properties, the proposed techniques do not require side information transmission. The PAPR performance of the techniques is shown to match, or in some cases improve, on current PAPR techniques for FBMC. Initial analysis of the computational complexity of the SGP techniques indicates that the complexity issues with PAPR reduction in FBMC implementations can be addressed. The out-of-band interference introduced by the techniques is investigated. As a result, it is shown that the interference can be compensated for, whilst still maintaining decent PAPR performance. Additional results are also provided by means of a study of the PAPR reduction of the proposed techniques at a fixed clipping probability. The bit error rate (BER) degradation is investigated to ensure that the trade-off in terms of BER degradation is not too severe. As illustrated by exhaustive simulations, the SGP ACE-based technique proposed are ideal candidates for practical implementation in systems employing the low-complexity polyphase implementation of FBMC modulators. The methods are shown to offer significant PAPR reduction and increase the feasibility of FBMC as
Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang
2014-01-01
Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images
Parlesak, Alexandr; Tetens, Inge; Dejgård Jensen, Jørgen; Smed, Sinne; Gabrijelčič Blenkuš, Mojca; Rayner, Mike; Darmon, Nicole; Robertson, Aileen
2016-01-01
Food-Based Dietary Guidelines (FBDGs) are developed to promote healthier eating patterns, but increasing food prices may make healthy eating less affordable. The aim of this study was to design a range of cost-minimized nutritionally adequate health-promoting food baskets (FBs) that help prevent both micronutrient inadequacy and diet-related non-communicable diseases at lowest cost. Average prices for 312 foods were collected within the Greater Copenhagen area. The cost and nutrient content of five different cost-minimized FBs for a family of four were calculated per day using linear programming. The FBs were defined using five different constraints: cultural acceptability (CA), or dietary guidelines (DG), or nutrient recommendations (N), or cultural acceptability and nutrient recommendations (CAN), or dietary guidelines and nutrient recommendations (DGN). The variety and number of foods in each of the resulting five baskets was increased through limiting the relative share of individual foods. The one-day version of N contained only 12 foods at the minimum cost of DKK 27 (€ 3.6). The CA, DG, and DGN were about twice of this and the CAN cost ~DKK 81 (€ 10.8). The baskets with the greater variety of foods contained from 70 (CAN) to 134 (DGN) foods and cost between DKK 60 (€ 8.1, N) and DKK 125 (€ 16.8, DGN). Ensuring that the food baskets cover both dietary guidelines and nutrient recommendations doubled the cost while cultural acceptability (CAN) tripled it. Use of linear programming facilitates the generation of low-cost food baskets that are nutritionally adequate, health promoting, and culturally acceptable.
A linear programming algorithm to test for jamming in hard-sphere packings
International Nuclear Information System (INIS)
Donev, Aleksandar; Torquato, Salvatore.; Stillinger, Frank H.; Connelly, Robert
2004-01-01
Jamming in hard-particle packings has been the subject of considerable interest in recent years. In a paper by Torquato and Stillinger [J. Phys. Chem. B 105 (2001)], a classification scheme of jammed packings into hierarchical categories of locally, collectively and strictly jammed configurations has been proposed. They suggest that these jamming categories can be tested using numerical algorithms that analyze an equivalent contact network of the packing under applied displacements, but leave the design of such algorithms as a future task. In this work, we present a rigorous and practical algorithm to assess whether an ideal hard-sphere packing in two or three dimensions is jammed according to the aforementioned categories. The algorithm is based on linear programming and is applicable to regular as well as random packings of finite size with hard-wall and periodic boundary conditions. If the packing is not jammed, the algorithm yields representative multi-particle unjamming motions. Furthermore, we extend the jamming categories and the testing algorithm to packings with significant interparticle gaps. We describe in detail two variants of the proposed randomized linear programming approach to test for jamming in hard-sphere packings. The first algorithm treats ideal packings in which particles form perfect contacts. Another algorithm treats the case of jamming in packings with significant interparticle gaps. This extended algorithm allows one to explore more fully the nature of the feasible particle displacements. We have implemented the algorithms and applied them to ordered as well as random packings of circular disks and spheres with periodic boundary conditions. Some representative results for large disordered disk and sphere packings are given, but more robust and efficient implementations as well as further applications (e.g., non-spherical particles) are anticipated for the future
International Nuclear Information System (INIS)
Shaban Boloukat, Mohammad Hadi; Akbari Foroud, Asghar
2016-01-01
This paper represents a stochastic approach for long-term optimal resource expansion planning of a grid-connected microgrid (MG) containing different technologies as intermittent renewable energy resources, energy storage systems and thermal resources. Maximizing profit and reliability, along with minimizing investment and operation costs, are major objectives which have been considered in this model. Also, the impacts of intermittency and uncertainty in renewable energy resources were investigated. The interval linear programming (ILP) was applied for modelling inherent stochastic nature of the renewable energy resources. ILP presents some superiority in modelling of uncertainties in MG planning. The problem was formulated as a mixed-integer linear programming. It has been demonstrated previously that the benders decomposition (BD) served as an effective tool for solving such problems. BD divides the original problem into a master (investment) problem and operation and reliability subproblems. In this paper a multiperiod MG planning is presented, considering life time, maximum penetration limit of each technology, interest rate, capital recovery factor and investment fund. Real-time energy exchange with the utility is covered, with a consideration of variable tariffs at different load blocks. The presented approach can help MG planners to adopt best decision under various uncertainty levels based on their budgetary policies. - Highlights: • Considering uncertain nature of the renewable resources with applying ILP. • Considering the effect of intermittency of renewable in MG planning. • Multiobjective MG planning problem which covers cost, profit and reliability. • Multiperiod approach for MG planning considering life time and MPL of technologies. • Presenting real-time energy exchange with the utility considering variable tariffs.
Energy Technology Data Exchange (ETDEWEB)
Jana, C. [Indian Inst. of Social Welfare and Business Management, Kolkata (India); Chattopadhyay, R.N. [Indian Inst. of Technology, Kharagpur (India). Rural Development Centre
2004-09-01
Creating provisions for domestic lighting is important for rural development. Its significance in rural economy is unquestionable since some activities, like literacy, education and manufacture of craft items and other cottage products are largely dependent on domestic lighting facilities for their progress and prosperity. Thus, in rural energy planning, domestic lighting remains a key sector for allocation of investments. For rational allocation, decision makers need alternative strategies for identifying adequate and proper investment structure corresponding to appropriate sources and precise devices. The present study aims at designing a model of energy utilisation by developing a decision support frame for an optimised solution to the problem, taking into consideration four sources and six devices suitable for the study area, namely Narayangarh Block of Midnapore District in India. Since the data available from rural and unorganised sectors are often ill-defined and subjective in nature, many coefficients are fuzzy numbers, and hence several constraints appear to be fuzzy expressions. In this study, the energy allocation model is initiated with three separate objectives for optimisation, namely minimising the total cost, minimising the use of non-local sources of energy and maximising the overall efficiency of the system. Since each of the above objective-based solutions has relevance to the needs of the society and economy, it is necessary to build a model that makes a compromise among the three individual solutions. This multi-objective fuzzy linear programming (MOFLP) model, solved in a compromising decision support frame, seems to be a more rational alternative than single objective linear programming model in rural energy planning. (author)
Directory of Open Access Journals (Sweden)
m. s. osman
2017-09-01
Full Text Available In this paper, we consider fuzzy goal programming (FGP approach for solving multi-level multi-objective quadratic fractional programming (ML-MOQFP problem with fuzzy parameters in the constraints. Firstly, the concept of the ?-cut approach is applied to transform the set of fuzzy constraints into a common deterministic one. Then, the quadratic fractional objective functions in each level are transformed into quadratic objective functions based on a proposed transformation. Secondly, the FGP approach is utilized to obtain a compromise solution for the ML-MOQFP problem by minimizing the sum of the negative deviational variables. Finally, an illustrative numerical example is given to demonstrate the applicability and performance of the proposed approach.
Wei, Peng; Sridhar, Banavar; Chen, Neil Yi-Nan; Sun, Dengfent
2012-01-01
A class of strategies has been proposed to reduce contrail formation in the United States airspace. A 3D grid based on weather data and the cruising altitude level of aircraft is adjusted to avoid the persistent contrail potential area with the consideration to fuel-efficiency. In this paper, the authors introduce a contrail avoidance strategy on 3D grid by considering additional operationally feasible constraints from an air traffic controller's aspect. First, shifting too many aircraft to the same cruising level will make the miles-in-trail at this level smaller than the safety separation threshold. Furthermore, the high density of aircraft at one cruising level may exceed the workload for the traffic controller. Therefore, in our new model we restrict the number of total aircraft at each level. Second, the aircraft count variation for successive intervals cannot be too drastic since the workload to manage climbing/descending aircraft is much larger than managing cruising aircraft. The contrail reduction is formulated as an integer-programming problem and the problem is shown to have the property of total unimodularity. Solving the corresponding relaxed linear programming with the simplex method provides an optimal and integral solution to the problem. Simulation results are provided to illustrate the methodology.
European refining trends to 2030: The advent of multi-area linear programming
International Nuclear Information System (INIS)
Saint-Antonin, V.; Marion, P.
2011-01-01
The current high degree of uncertainty that pervades the global energy landscape is directly impacting on the oil industry, which is having to integrate growing mobility requirements in the context of energy transition due to the emergence of alternatives to petroleum fuels and restrictions on pollutant emissions. In this context, the study 'Raffinage 2030' (Refining 2030), carried out by IFPEN (the French Institute of Petroleum and New Energy Sources), is a prospective exercise for a better understanding of the balance between global supply and demand of petroleum products in order to shed light on the type and geographical location of necessary investments in refineries, as well as to assess the impact on these of the introduction of new fuels and more and more restrictions, such as environmental regulations. To this end, the refinery model used is one of linear programming, breaking the world down into nine geographical areas. This article introduces the programming model and its basic assumptions, before presenting the main lessons drawn om this study regarding the potential evolutions of the refining industry, in particular the European one, to face the market's long term trends. (authors)
Drag reduction of a car model by linear genetic programming control
Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien
2017-08-01
We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.
International Nuclear Information System (INIS)
Sadeghi, Mehdi; Mirshojaeian Hosseini, Hossein
2006-01-01
For many years, energy models have been used in developed or developing countries to satisfy different needs in energy planning. One of major problems against energy planning and consequently energy models is uncertainty, spread in different economic, political and legal dimensions of energy planning. Confronting uncertainty, energy planners have often used two well-known strategies. The first strategy is stochastic programming, in which energy system planners define different scenarios and apply an explicit probability of occurrence to each scenario. The second strategy is Minimax Regret strategy that minimizes regrets of different decisions made in energy planning. Although these strategies have been used extensively, they could not flexibly and effectively deal with the uncertainties caused by fuzziness. 'Fuzzy Linear Programming (FLP)' is a strategy that can take fuzziness into account. This paper tries to demonstrate the method of application of FLP for optimization of supply energy system in Iran, as a case study. The used FLP model comprises fuzzy coefficients for investment costs. Following the mentioned purpose, it is realized that FLP is an easy and flexible approach that can be a serious competitor for other confronting uncertainties approaches, i.e. stochastic and Minimax Regret strategies. (author)
Li, Yanning
2014-03-01
This article presents a new optimal control framework for transportation networks in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi (H-J) equation and the commonly used triangular fundamental diagram, we pose the problem of controlling the state of the system on a network link, in a finite horizon, as a Linear Program (LP). We then show that this framework can be extended to an arbitrary transportation network, resulting in an LP or a Quadratic Program. Unlike many previously investigated transportation network control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e., discontinuities in the state of the system). As it leverages the intrinsic properties of the H-J equation used to model the state of the system, it does not require any approximation, unlike classical methods that are based on discretizations of the model. The computational efficiency of the method is illustrated on a transportation network. © 2014 IEEE.
Takabe, Satoshi; Hukushima, Koji
2016-05-01
Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α-uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α=2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c=e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c=1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α≥3, minimum vertex covers on α-uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c=e/(α-1) where the replica symmetry is broken.
Application of mixed-integer linear programming in a car seats assembling process
Directory of Open Access Journals (Sweden)
Jorge Iván Perez Rave
2011-12-01
Full Text Available In this paper, a decision problem involving a car parts manufacturing company is modeled in order to prepare the company for an increase in demand. Mixed-integer linear programming was used with the following decision variables: creating a second shift, purchasing additional equipment, determining the required work force, and other alternatives involving new manners of work distribution that make it possible to separate certain operations from some workplaces and integrate them into others to minimize production costs. The model was solved using GAMS. The solution consisted of programming 19 workers under a configuration that merges two workplaces and separates some operations from some workplaces. The solution did not involve purchasing additional machinery or creating a second shift. As a result, the manufacturing paradigms that had been valid in the company for over 14 years were broken. This study allowed the company to increase its productivity and obtain significant savings. It also shows the benefits of joint work between academia and companies, and provides useful information for professors, students and engineers regarding production and continuous improvement.
Takabe, Satoshi; Hukushima, Koji
2016-05-01
Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α -uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α =2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c =e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c =1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α ≥3 , minimum vertex covers on α -uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c =e /(α -1 ) where the replica symmetry is broken.
Li, Yanning; Canepa, Edward S.; Claudel, Christian
2014-01-01
This article presents a new optimal control framework for transportation networks in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi (H-J) equation and the commonly used triangular fundamental diagram, we pose the problem of controlling the state of the system on a network link, in a finite horizon, as a Linear Program (LP). We then show that this framework can be extended to an arbitrary transportation network, resulting in an LP or a Quadratic Program. Unlike many previously investigated transportation network control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e., discontinuities in the state of the system). As it leverages the intrinsic properties of the H-J equation used to model the state of the system, it does not require any approximation, unlike classical methods that are based on discretizations of the model. The computational efficiency of the method is illustrated on a transportation network. © 2014 IEEE.
Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen
2018-01-01
With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weights of the remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP
Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen
2018-01-05
With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weights of the remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP
Simic, Vladimir
2015-01-01
End-of-life vehicles (ELVs) are vehicles that have reached the end of their useful lives and are no longer registered or licensed for use. The ELV recycling problem has become very serious in the last decade and more and more efforts are made in order to reduce the impact of ELVs on the environment. This paper proposes the fuzzy risk explicit interval linear programming model for ELV recycling planning in the EU. It has advantages in reflecting uncertainties presented in terms of intervals in the ELV recycling systems and fuzziness in decision makers' preferences. The formulated model has been applied to a numerical study in which different decision maker types and several ELV types under two EU ELV Directive legislative cases were examined. This study is conducted in order to examine the influences of the decision maker type, the α-cut level, the EU ELV Directive and the ELV type on decisions about vehicle hulks procuring, storing unprocessed hulks, sorting generated material fractions, allocating sorted waste flows and allocating sorted metals. Decision maker type can influence quantity of vehicle hulks kept in storages. The EU ELV Directive and decision maker type have no influence on which vehicle hulk type is kept in the storage. Vehicle hulk type, the EU ELV Directive and decision maker type do not influence the creation of metal allocation plans, since each isolated metal has its regular destination. The valid EU ELV Directive eco-efficiency quotas can be reached even when advanced thermal treatment plants are excluded from the ELV recycling process. The introduction of the stringent eco-efficiency quotas will significantly reduce the quantities of land-filled waste fractions regardless of the type of decision makers who will manage vehicle recycling system. In order to reach these stringent quotas, significant quantities of sorted waste need to be processed in advanced thermal treatment plants. Proposed model can serve as the support for the European
Aspect-object alignment with Integer Linear Programming in opinion mining.
Directory of Open Access Journals (Sweden)
Yanyan Zhao
Full Text Available Target extraction is an important task in opinion mining. In this task, a complete target consists of an aspect and its corresponding object. However, previous work has always simply regarded the aspect as the target itself and has ignored the important "object" element. Thus, these studies have addressed incomplete targets, which are of limited use for practical applications. This paper proposes a novel and important sentiment analysis task, termed aspect-object alignment, to solve the "object neglect" problem. The objective of this task is to obtain the correct corresponding object for each aspect. We design a two-step framework for this task. We first provide an aspect-object alignment classifier that incorporates three sets of features, namely, the basic, relational, and special target features. However, the objects that are assigned to aspects in a sentence often contradict each other and possess many complicated features that are difficult to incorporate into a classifier. To resolve these conflicts, we impose two types of constraints in the second step: intra-sentence constraints and inter-sentence constraints. These constraints are encoded as linear formulations, and Integer Linear Programming (ILP is used as an inference procedure to obtain a final global decision that is consistent with the constraints. Experiments on a corpus in the camera domain demonstrate that the three feature sets used in the aspect-object alignment classifier are effective in improving its performance. Moreover, the classifier with ILP inference performs better than the classifier without it, thereby illustrating that the two types of constraints that we impose are beneficial.
Aspect-object alignment with Integer Linear Programming in opinion mining.
Zhao, Yanyan; Qin, Bing; Liu, Ting; Yang, Wei
2015-01-01
Target extraction is an important task in opinion mining. In this task, a complete target consists of an aspect and its corresponding object. However, previous work has always simply regarded the aspect as the target itself and has ignored the important "object" element. Thus, these studies have addressed incomplete targets, which are of limited use for practical applications. This paper proposes a novel and important sentiment analysis task, termed aspect-object alignment, to solve the "object neglect" problem. The objective of this task is to obtain the correct corresponding object for each aspect. We design a two-step framework for this task. We first provide an aspect-object alignment classifier that incorporates three sets of features, namely, the basic, relational, and special target features. However, the objects that are assigned to aspects in a sentence often contradict each other and possess many complicated features that are difficult to incorporate into a classifier. To resolve these conflicts, we impose two types of constraints in the second step: intra-sentence constraints and inter-sentence constraints. These constraints are encoded as linear formulations, and Integer Linear Programming (ILP) is used as an inference procedure to obtain a final global decision that is consistent with the constraints. Experiments on a corpus in the camera domain demonstrate that the three feature sets used in the aspect-object alignment classifier are effective in improving its performance. Moreover, the classifier with ILP inference performs better than the classifier without it, thereby illustrating that the two types of constraints that we impose are beneficial.
A linear programming model for protein inference problem in shotgun proteomics.
Huang, Ting; He, Zengyou
2012-11-15
Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is an important issue in shotgun proteomics. The objective of protein inference is to find a subset of proteins that are truly present in the sample. Although many methods have been proposed for protein inference, several issues such as peptide degeneracy still remain unsolved. In this article, we present a linear programming model for protein inference. In this model, we use a transformation of the joint probability that each peptide/protein pair is present in the sample as the variable. Then, both the peptide probability and protein probability can be expressed as a formula in terms of the linear combination of these variables. Based on this simple fact, the protein inference problem is formulated as an optimization problem: minimize the number of proteins with non-zero probabilities under the constraint that the difference between the calculated peptide probability and the peptide probability generated from peptide identification algorithms should be less than some threshold. This model addresses the peptide degeneracy issue by forcing some joint probability variables involving degenerate peptides to be zero in a rigorous manner. The corresponding inference algorithm is named as ProteinLP. We test the performance of ProteinLP on six datasets. Experimental results show that our method is competitive with the state-of-the-art protein inference algorithms. The source code of our algorithm is available at: https://sourceforge.net/projects/prolp/. zyhe@dlut.edu.cn. Supplementary data are available at Bioinformatics Online.
Czech Academy of Sciences Publication Activity Database
Plocková, Jana; Chmelík, Josef
2006-01-01
Roč. 1118, č. 2 (2006), s. 253-260 ISSN 0021-9673 R&D Projects: GA MZe QD1005 Institutional research plan: CEZ:AV0Z40310501 Keywords : gravitational field flow fractionation * focusing elution mode * carrier liquid density Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 3.554, year: 2006
A linear programming model to optimize diets in environmental policy scenarios.
Moraes, L E; Wilen, J E; Robinson, P H; Fadel, J G
2012-03-01
The objective was to develop a linear programming model to formulate diets for dairy cattle when environmental policies are present and to examine effects of these policies on diet formulation and dairy cattle nitrogen and mineral excretions as well as methane emissions. The model was developed as a minimum cost diet model. Two types of environmental policies were examined: a tax and a constraint on methane emissions. A tax was incorporated to simulate a greenhouse gas emissions tax policy, and prices of carbon credits in the current carbon markets were attributed to the methane production variable. Three independent runs were made, using carbon dioxide equivalent prices of $5, $17, and $250/t. A constraint was incorporated into the model to simulate the second type of environmental policy, reducing methane emissions by predetermined amounts. The linear programming formulation of this second alternative enabled the calculation of marginal costs of reducing methane emissions. Methane emission and manure production by dairy cows were calculated according to published equations, and nitrogen and mineral excretions were calculated by mass conservation laws. Results were compared with respect to the values generated by a base least-cost model. Current prices of the carbon credit market did not appear onerous enough to have a substantive incentive effect in reducing methane emissions and altering diet costs of our hypothetical dairy herd. However, when emissions of methane were assumed to be reduced by 5, 10, and 13.5% from the base model, total diet costs increased by 5, 19.1, and 48.5%, respectively. Either these increased costs would be passed onto the consumer or dairy producers would go out of business. Nitrogen and potassium excretions were increased by 16.5 and 16.7% with a 13.5% reduction in methane emissions from the base model. Imposing methane restrictions would further increase the demand for grains and other human-edible crops, which is not a progressive
Directory of Open Access Journals (Sweden)
Yen Sun
2010-05-01
Full Text Available It is observed that the number of Indonesia’s domestic investor who involved in the stock exchange is very less compare to its total number of population (only about 0.1%. As a result, Indonesia Stock Exchange (IDX is highly affected by foreign investor that can threat the economy. Domestic investor tends to invest in risk-free asset such as deposit in the bank since they are not familiar yet with the stock market and anxious about the risk (risk-averse type of investor. Therefore, it is important to educate domestic investor to involve in the stock exchange. Investing in portfolio of stock is one of the best choices for risk-averse investor (such as Indonesia domestic investor since it offers lower risk for a given level of return. This paper studies the optimization of Indonesian stock portfolio. The data is the historical return of 10 stocks of LQ 45 for 5 time series (January 2004 – December 2008. It will be focus on selecting stocks into a portfolio, setting 10 of stock portfolios using mean variance method combining with the linear programming (solver. Furthermore, based on Efficient Frontier concept and Sharpe measurement, there will be one stock portfolio picked as an optimum Portfolio (Namely Portfolio G. Then, Performance of portfolio G will be evaluated by using Sharpe, Treynor and Jensen Measurement to show whether the return of Portfolio G exceeds the market return. This paper also illustrates how the stock composition of the Optimum Portfolio (G succeeds to predict the portfolio return in the future (5th January – 3rd April 2009. The result of the study observed that optimization portfolio using Mean-Variance (consistent with Markowitz theory combine with linear programming can be applied into Indonesia stock’s portfolio. All the measurements (Sharpe, Jensen, and Treynor show that the portfolio G is a superior portfolio. It is also been found that the composition (weights stocks of optimum portfolio (G can be used to
A LINEAR PROGRAMMING METHOD TO ENHANCE RESOURCE UTILIZATION CASE OF ETHIOPIAN APPAREL SECTOR
Directory of Open Access Journals (Sweden)
Gezahegn Tesfaye
2016-06-01
Full Text Available The Ethiopian industrial development strategy is characterized by export-led and labor intensive industrialization. The country is emerging as the most important investment destination in its apparel sector. Thought this sector is expected to generate more income from the export market, its export earnings remain trivial mainly due to the inefficient organizational resource utilization. One of the competent techniques that help companies to efficiently improve the use of their resources to increase their profit is linear programming. In apparel manufacturing firms, efficient use of materials such as fabrics and sewing threads and processing time at different stages of production as well as minimization of labor and materials cost are necessary to enhance their profitability. Cutting, sewing, and finishing operations deserve more attention for apparel process optimization. However, the issue of proper resource allocation remains an unsolved problem within the Ethiopian apparel industry. The aim of this research is to devise efficient resource utilization mechanism for Ethiopian apparel sector to improve their resource utilization and profitability, taking one of the garment factories engaged in the export market as a case study. Five types of products the company is currently producing, the amount of resources employed to produce each unit of the products, and the value of profit per unit from the sale of each products have been collected from the case company. The monthly availability of resources utilized and the monthly production volume of the five products have also been collected from the company. The data gathered was mathematically modeled using a linear programming technique, and solved using MS-Excel solver. The findings of the study depicts that all of the organizational resources are severely underutilized. This research proved that the resource utilization of the case company can be improved from 46.41% of the current resource
International Nuclear Information System (INIS)
Nixon, J.D.
2016-01-01
This paper presents a method for optimising the design parameters of an anaerobic digestion (AD) system by using first-order kinetics and multi-objective non-linear goal programming. A model is outlined that determines the ideal operating tank temperature and hydraulic retention time, based on objectives for minimising levelised cost of electricity, and maximising energy potential and feedstock mass reduction. The model is demonstrated for a continuously stirred tank reactor processing food waste in two case study locations. These locations are used to investigate the influence of different environmental and economic climates on optimal conditions. A sensitivity analysis is performed to further examine the variation in optimal results for different financial assumptions and objective weightings. The results identify the conditions for the preferred tank temperature to be in the psychrophilic, mesophilic or thermophilic range. For a tank temperature of 35 °C, ideal hydraulic retention times, in terms of achieving a minimum levelised electricity cost, were found to range from 29.9 to 33 days. Whilst there is a need for more detailed information on rate constants for use in first-order models, multi-objective optimisation modelling is considered to be a promising option for AD design. - Highlights: • Nonlinear goal programming is used to optimise anaerobic digestion systems. • Multiple objectives are set including minimising the levelised cost of electricity. • A model is developed and applied to case studies for the UK and India. • Optimal decisions are made for tank temperature and retention time. • A sensitivity analysis is carried out to investigate different model objectives.
Pradanti, Paskalia; Hartono
2018-03-01
Determination of insulin injection dose in diabetes mellitus treatment can be considered as an optimal control problem. This article is aimed to simulate optimal blood glucose control for patient with diabetes mellitus. The blood glucose regulation of diabetic patient is represented by Ackerman’s Linear Model. This problem is then solved using dynamic programming method. The desired blood glucose level is obtained by minimizing the performance index in Lagrange form. The results show that dynamic programming based on Ackerman’s Linear Model is quite good to solve the problem.
International Nuclear Information System (INIS)
Viana, Rodrigo Sartorelo S.; Lima, Ernesto A.B.F.; Florentino, Helenice de Oliveira; Fonseca, Paulo Roberto da; Homem, Thiago Pedro Donadon
2009-01-01
Linear programming models are widely found in the literature addressing various aspects involved in the creation of optimized planning for radiotherapy. However, most mathematical formulations does not incorporate certain factors that are of extreme importance for the formulation of a real planning like the attenuation of the beam of radiation and heterogeneity in the composition of tissue irradiated. In this context are proposed in this paper some modifications in the formulation of a linear programming problem with the objective of making the simulation closer to the real planning for radiotherapy and thus enable a more reliable and comprehensive planning requirements. (author)
Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G
2012-01-01
Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.
Directory of Open Access Journals (Sweden)
Alexander Mitsos
Full Text Available Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i excessive CPU time requirements and ii loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.
Optimization of planting pattern plan in Logung irrigation area using linear program
Wardoyo, Wasis; Setyono
2018-03-01
Logung irrigation area is located in Kudus Regency, Central Java Province, Indonesia. Irrigation area with 2810 Ha of extent is getting water supply from Logung dam. Yet, the utilization of water at Logung dam is not optimal and the distribution of water is still not evenly distributed. Therefore, this study will discuss about the optimization of irrigation water utilization based on the beginning of plant season. This optimization begins with the analysis of hydrology, climatology and river discharge in order to determine the irrigation water needs. After determining irrigation water needs, six alternatives of planting patterns with the different early planting periods, i.e. 1st November, 2nd November, 3rd November, 1st December, 2nd December, and 3rd December with the planting pattern of rice-secondary crop-sugarcane is introduced. It is continued by the analysis of water distribution conducted using linear program assisted by POM-Quantity method for Windows 3 with the reliable discharge limit and the available land area. Output of this calculation are to determine the land area that can be planted based on the type of plant and growing season, and to obtaine the profits of harvest yields. Based on the optimum area of each plant species with 6 alternatives, the most optimum area was obtained at the early planting periods on 3rd December with the production profit of Rp 113.397.338.854,- with the planting pattern of rice / beans / sugarcane-rice / beans / sugarcane-beans / sugarcane.
Optimal Airport Surface Traffic Planning Using Mixed-Integer Linear Programming
Directory of Open Access Journals (Sweden)
P. C. Roling
2008-01-01
Full Text Available We describe an ongoing research effort pertaining to the development of a surface traffic automation system that will help controllers to better coordinate surface traffic movements related to arrival and departure traffic. More specifically, we describe the concept for a taxi-planning support tool that aims to optimize the routing and scheduling of airport surface traffic in such a way as to deconflict the taxi plans while optimizing delay, total taxi-time, or some other airport efficiency metric. Certain input parameters related to resource demand, such as the expected landing times and the expected pushback times, are rather difficult to predict accurately. Due to uncertainty in the input data driving the taxi-planning process, the taxi-planning tool is designed such that it produces solutions that are robust to uncertainty. The taxi-planning concept presented herein, which is based on mixed-integer linear programming, is designed such that it is able to adapt to perturbations in these input conditions, as well as to account for failure in the actual execution of surface trajectories. The capabilities of the tool are illustrated in a simple hypothetical airport.
High Productivity Programming of Dense Linear Algebra on Heterogeneous NUMA Architectures
Alomairy, Rabab M.
2013-07-01
High-end multicore systems with GPU-based accelerators are now ubiquitous in the hardware landscape. Besides dealing with the nontrivial heterogeneous environ- ment, end users should often take into consideration the underlying memory architec- ture to decrease the overhead of data motion, especially when running on non-uniform memory access (NUMA) platforms. We propose the OmpSs parallel programming model approach using its Nanos++ dynamic runtime system to solve the two challeng- ing problems aforementioned, through 1) an innovative NUMA node-aware scheduling policy to reduce data movement between NUMA nodes and 2) a nested parallelism feature to concurrently exploit the resources available from the GPU devices as well as the CPU host, without compromising the overall performance. Our approach fea- tures separation of concerns by abstracting the complexity of the hardware from the end users so that high productivity can be achieved. The Cholesky factorization is used as a benchmark representative of dense numerical linear algebra algorithms. Superior performance is also demonstrated on the symmetric matrix inversion based on Cholesky factorization, commonly used in co-variance computations in statistics. Performance on a NUMA system with Kepler-based GPUs exceeds that of existing implementations, while the OmpSs-enabled code remains very similar to its original sequential version.
Optimising the selection of food items for FFQs using Mixed Integer Linear Programming.
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.
Chun, Tae Yoon; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho
2018-06-01
In this paper, we propose two multirate generalised policy iteration (GPI) algorithms applied to discrete-time linear quadratic regulation problems. The proposed algorithms are extensions of the existing GPI algorithm that consists of the approximate policy evaluation and policy improvement steps. The two proposed schemes, named heuristic dynamic programming (HDP) and dual HDP (DHP), based on multirate GPI, use multi-step estimation (M-step Bellman equation) at the approximate policy evaluation step for estimating the value function and its gradient called costate, respectively. Then, we show that these two methods with the same update horizon can be considered equivalent in the iteration domain. Furthermore, monotonically increasing and decreasing convergences, so called value iteration (VI)-mode and policy iteration (PI)-mode convergences, are proved to hold for the proposed multirate GPIs. Further, general convergence properties in terms of eigenvalues are also studied. The data-driven online implementation methods for the proposed HDP and DHP are demonstrated and finally, we present the results of numerical simulations performed to verify the effectiveness of the proposed methods.
Error Analysis Of Students Working About Word Problem Of Linear Program With NEA Procedure
Santoso, D. A.; Farid, A.; Ulum, B.
2017-06-01
Evaluation and assessment is an important part of learning. In evaluation process of learning, written test is still commonly used. However, the tests usually do not following-up by further evaluation. The process only up to grading stage not to evaluate the process and errors which done by students. Whereas if the student has a pattern error and process error, actions taken can be more focused on the fault and why is that happen. NEA procedure provides a way for educators to evaluate student progress more comprehensively. In this study, students’ mistakes in working on some word problem about linear programming have been analyzed. As a result, mistakes are often made students exist in the modeling phase (transformation) and process skills (process skill) with the overall percentage distribution respectively 20% and 15%. According to the observations, these errors occur most commonly due to lack of precision of students in modeling and in hastiness calculation. Error analysis with students on this matter, it is expected educators can determine or use the right way to solve it in the next lesson.
Applying linear programming model to aggregate production planning of coated peanut products
Rohmah, W. G.; Purwaningsih, I.; Santoso, EF S. M.
2018-03-01
The aim of this study was to set the overall production level for each grade of coated peanut product to meet market demands with a minimum production cost. The linear programming model was applied in this study. The proposed model was used to minimize the total production cost based on the limited demand of coated peanuts. The demand values applied to the method was previously forecasted using time series method and production capacity aimed to plan the aggregate production for the next 6 month period. The results indicated that the production planning using the proposed model has resulted a better fitted pattern to the customer demands compared to that of the company policy. The production capacity of product family A, B, and C was relatively stable for the first 3 months of the planning periods, then began to fluctuate over the next 3 months. While, the production capacity of product family D and E was fluctuated over the 6-month planning periods, with the values in the range of 10,864 - 32,580 kg and 255 – 5,069 kg, respectively. The total production cost for all products was 27.06% lower than the production cost calculated using the company’s policy-based method.
International Nuclear Information System (INIS)
Kumaran, P.; Hari, Z.; Boosroh, M.H.
2006-01-01
Two technologies have been considered to generate electricity using palm oil mill waste, the Empty Fruit Bunch (EFB) as power plant fuel. One technology is to build new 100% EFB fired power plants, located in the vicinity of the palm oil mill, in which the produced electricity would be connected to the national electricity grid system. The other technology is to transport all the available EFB fuel to an existing coal power station in which the EFB fuel would be blended with coal and co-fired in conventional coal power plant to produce electricity. A study intended to compare the difference between these two technologies, to obtain the same electricity generation, has been done. Linear programming software was used simulate the two technologies to generate 5% of Peninsular Malaysia's electricity demand in the year 2005. The study indicated that the co firing technology total cost is 43.7% cheaper than EFB technology and the fuel coat is competitive until transport cost reaches 78 RM/tone
Linear genetic programming application for successive-station monthly streamflow prediction
Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit
2014-09-01
In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.
Directory of Open Access Journals (Sweden)
Winasis Winasis
2013-06-01
Full Text Available One of hydro power plant operational problem is how to maximize available water resouces to gather optimal electric power generation. Water availability which is limited and can be stored in a reservoir will influence electrical energy generated by the plant. This paper present a new approach of short term optimization of hydro power plant operation. The objective function is to maximize energy which is produced by power plant on scheduling operation period, with consider water resource availability in reservoir as operational constraint. The optimization problem is formulated in Linear Programming Method, in which this method is a commonly used to solve optimization problem in hydro power plant. Based on simulation results on Ketenger Hydro Power Plant using water flow data on June 1st 2013 shows that this method can be used to solve hydro power plant operation optimization problem well. Electrical energy as main objective function is maximized and all prevailing constrain is satisfied. On this short term operation (24 hour simulation, total energy can be produced is 96121,55 kWh, or 1427 kWh (1,51% greater comparing with real generation condition with 96694 kWh.
An improved exploratory search technique for pure integer linear programming problems
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.
Boundary Control of Linear Uncertain 1-D Parabolic PDE Using Approximate Dynamic Programming.
Talaei, Behzad; Jagannathan, Sarangapani; Singler, John
2018-04-01
This paper develops a near optimal boundary control method for distributed parameter systems governed by uncertain linear 1-D parabolic partial differential equations (PDE) by using approximate dynamic programming. A quadratic surface integral is proposed to express the optimal cost functional for the infinite-dimensional state space. Accordingly, the Hamilton-Jacobi-Bellman (HJB) equation is formulated in the infinite-dimensional domain without using any model reduction. Subsequently, a neural network identifier is developed to estimate the unknown spatially varying coefficient in PDE dynamics. Novel tuning law is proposed to guarantee the boundedness of identifier approximation error in the PDE domain. A radial basis network (RBN) is subsequently proposed to generate an approximate solution for the optimal surface kernel function online. The tuning law for near optimal RBN weights is created, such that the HJB equation error is minimized while the dynamics are identified and closed-loop system remains stable. Ultimate boundedness (UB) of the closed-loop system is verified by using the Lyapunov theory. The performance of the proposed controller is successfully confirmed by simulation on an unstable diffusion-reaction process.
Nykänen, Esa-Pekka A; Dunning, Hanna E; Aryeetey, Richmond N O; Robertson, Aileen; Parlesak, Alexandr
2018-04-07
The Ghanaian population suffers from a double burden of malnutrition. Cost of food is considered a barrier to achieving a health-promoting diet. Food prices were collected in major cities and in rural areas in southern Ghana. Linear programming (LP) was used to calculate nutritionally optimized diets (food baskets (FBs)) for a low-income Ghanaian family of four that fulfilled energy and nutrient recommendations in both rural and urban settings. Calculations included implementing cultural acceptability for families living in extreme and moderate poverty (food budget under USD 1.9 and 3.1 per day respectively). Energy-appropriate FBs minimized for cost, following Food Balance Sheets (FBS), lacked key micronutrients such as iodine, vitamin B12 and iron for the mothers. Nutritionally adequate FBs were achieved in all settings when optimizing for a diet cheaper than USD 3.1. However, when delimiting cost to USD 1.9 in rural areas, wild foods had to be included in order to meet nutritional adequacy. Optimization suggested to reduce roots, tubers and fruits and to increase cereals, vegetables and oil-bearing crops compared with FBS. LP is a useful tool to design culturally acceptable diets at minimum cost for low-income Ghanaian families to help advise national authorities how to overcome the double burden of malnutrition.
Jung, Ho-Won; El Emam, Khaled
2014-05-29
A linear programming (LP) model was proposed to create de-identified data sets that maximally include spatial detail (e.g., geocodes such as ZIP or postal codes, census blocks, and locations on maps) while complying with the HIPAA Privacy Rule's Expert Determination method, i.e., ensuring that the risk of re-identification is very small. The LP model determines the transition probability from an original location of a patient to a new randomized location. However, it has a limitation for the cases of areas with a small population (e.g., median of 10 people in a ZIP code). We extend the previous LP model to accommodate the cases of a smaller population in some locations, while creating de-identified patient spatial data sets which ensure the risk of re-identification is very small. Our LP model was applied to a data set of 11,740 postal codes in the City of Ottawa, Canada. On this data set we demonstrated the limitations of the previous LP model, in that it produces improbable results, and showed how our extensions to deal with small areas allows the de-identification of the whole data set. The LP model described in this study can be used to de-identify geospatial information for areas with small populations with minimal distortion to postal codes. Our LP model can be extended to include other information, such as age and gender.
A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.
Röhl, Annika; Bockmayr, Alexander
2017-01-03
Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.
A depth-first search algorithm to compute elementary flux modes by linear programming.
Quek, Lake-Ee; Nielsen, Lars K
2014-07-30
The decomposition of complex metabolic networks into elementary flux modes (EFMs) provides a useful framework for exploring reaction interactions systematically. Generating a complete set of EFMs for large-scale models, however, is near impossible. Even for moderately-sized models (linear programming (LP) to enumerate EFMs in an exhaustive fashion. Constraints can be introduced to directly generate a subset of EFMs satisfying the set of constraints. The depth-first search algorithm has a constant memory overhead. Using flux constraints, a large LP problem can be massively divided and parallelized into independent sub-jobs for deployment into computing clusters. Since the sub-jobs do not overlap, the approach scales to utilize all available computing nodes with minimal coordination overhead or memory limitations. The speed of the algorithm was comparable to efmtool, a mainstream Double Description method, when enumerating all EFMs; the attrition power gained from performing flux feasibility tests offsets the increased computational demand of running an LP solver. Unlike the Double Description method, the algorithm enables accelerated enumeration of all EFMs satisfying a set of constraints.
Integer Linear Programming for Constrained Multi-Aspect Committee Review Assignment
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
How to use composite indicator and linear programming model for determine sustainable tourism.
Ziaabadi, Maryam; Malakootian, Mohammad; Zare Mehrjerdi, Mohammad Reza; Jalaee, Seied Abdolmajid; Mehrabi Boshrabadi, Hosein
2017-01-01
The tourism industry which is one of the most dynamic economic activities in today's world plays a significant role in the sustainable development. Therefore, in addition to paying attention to tourism, sustainable tourism must be taken into huge account; otherwise, the environment and its health will be damaged irreparably. To determine the level of sustainability in this study, indicators of sustainable tourism were first presented in three environmental health, economic and social aspects. Then, the levels of sustainable tourism and environmental sustainability were practically measured in different cities of Kerman Province using a composite indicator, a linear programming model, Delphi method and the questionnaire technique. Finally, the study cities (tourist attractions) were ranked. Result of this study showed that unfortunately the tourism opportunities were not used appropriately in these cities and tourist destinations, and that environmental aspect (health and environmental sustainability) had very bad situations compared to social and economic aspects. In other words, environmental health had the lowest levels of sustainability. The environment is a place for all human activities like tourism, social and economic issues; therefore, its stability and health is of great importance. Thus, it is necessary to pay more attention to sustainability of activities, management and environmental health in planning sustainable development in regional and national policy.
lpNet: a linear programming approach to reconstruct signal transduction networks.
Matos, Marta R A; Knapp, Bettina; Kaderali, Lars
2015-10-01
With the widespread availability of high-throughput experimental technologies it has become possible to study hundreds to thousands of cellular factors simultaneously, such as coding- or non-coding mRNA or protein concentrations. Still, extracting information about the underlying regulatory or signaling interactions from these data remains a difficult challenge. We present a flexible approach towards network inference based on linear programming. Our method reconstructs the interactions of factors from a combination of perturbation/non-perturbation and steady-state/time-series data. We show both on simulated and real data that our methods are able to reconstruct the underlying networks fast and efficiently, thus shedding new light on biological processes and, in particular, into disease's mechanisms of action. We have implemented the approach as an R package available through bioconductor. This R package is freely available under the Gnu Public License (GPL-3) from bioconductor.org (http://bioconductor.org/packages/release/bioc/html/lpNet.html) and is compatible with most operating systems (Windows, Linux, Mac OS) and hardware architectures. bettina.knapp@helmholtz-muenchen.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Lu, Zhao; Sun, Jing; Butts, Kenneth
2014-05-01
Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.
Quality evaluation of millet-soy blended extrudates formulated through linear programming.
Balasubramanian, S; Singh, K K; Patil, R T; Onkar, Kolhe K
2012-08-01
Whole pearl millet, finger millet and decorticated soy bean blended (millet soy) extrudates formulations were designed using a linear programming (LP) model to minimize the total cost of the finished product. LP formulated composite flour was extruded through twin screw food extruder at different feed rate (6.5-13.5 kg/h), screw speed (200-350 rpm, constant feed moisture (14% wb), barrel temperature (120 °C) and cutter speed (15 rpm). The physical, functional, textural and pasting characteristics of extrudates were examined and their responses were studied. Expansion index (2.31) and sectional expansion index (5.39) was found to be was found maximum for feed rate and screw speed combination 9.5 kg/h and 250 rpm. However, density (0.25 × 10(-3) g/mm(3)) was maximum for 9.5 kg/h and 300 rpm combination. Maximum color change (10.32) was found for 9.5 kg/h feed rate and 200 rpm screw speed. The lower hardness was obtained for the samples extruded at lowest feed rate (6.5 kg/h) for all screw speed and feed rate at 9.5 kg/h for 300-350 rpm screw speed. Peak viscosity decreases with all screw speed of 9.5 kg/h feed rate.
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.
A linear programming approach to max-sum problem: a review.
Werner, Tomás
2007-07-01
The max-sum labeling problem, defined as maximizing a sum of binary (i.e., pairwise) functions of discrete variables, is a general NP-hard optimization problem with many applications, such as computing the MAP configuration of a Markov random field. We review a not widely known approach to the problem, developed by Ukrainian researchers Schlesinger et al. in 1976, and show how it contributes to recent results, most importantly, those on the convex combination of trees and tree-reweighted max-product. In particular, we review Schlesinger et al.'s upper bound on the max-sum criterion, its minimization by equivalent transformations, its relation to the constraint satisfaction problem, the fact that this minimization is dual to a linear programming relaxation of the original problem, and the three kinds of consistency necessary for optimality of the upper bound. We revisit problems with Boolean variables and supermodular problems. We describe two algorithms for decreasing the upper bound. We present an example application for structural image analysis.
Automatic Design of Synthetic Gene Circuits through Mixed Integer Non-linear Programming
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
Improving an Integer Linear Programming Model of an Ecovat Buffer by Adding Long-Term Planning
Directory of Open Access Journals (Sweden)
Gijs J. H. de Goeijen
2017-12-01
Full Text Available The Ecovat is a seasonal thermal storage solution consisting of a large underground water tank divided into a number of virtual segments that can be individually charged and discharged. The goal of the Ecovat is to supply heat demand to a neighborhood throughout the entire year. In this work, we extend an integer linear programming model to describe the charging and discharging of such an Ecovat buffer by adding a long-term (yearly planning step to the model. We compare the results from the model using this extension to previously obtained results and show significant improvements when looking at the combination of costs and the energy content of the buffer at the end of the optimization. Furthermore, we show that the model is very robust against prediction errors. For this, we compare two different cases: one case in which we assume perfect predictions are available and one case in which we assume no predictions are available. The largest observed difference in costs between these two cases is less than 2%.
A multiple objective mixed integer linear programming model for power generation expansion planning
Energy Technology Data Exchange (ETDEWEB)
Antunes, C. Henggeler; Martins, A. Gomes [INESC-Coimbra, Coimbra (Portugal); Universidade de Coimbra, Dept. de Engenharia Electrotecnica, Coimbra (Portugal); Brito, Isabel Sofia [Instituto Politecnico de Beja, Escola Superior de Tecnologia e Gestao, Beja (Portugal)
2004-03-01
Power generation expansion planning inherently involves multiple, conflicting and incommensurate objectives. Therefore, mathematical models become more realistic if distinct evaluation aspects, such as cost and environmental concerns, are explicitly considered as objective functions rather than being encompassed by a single economic indicator. With the aid of multiple objective models, decision makers may grasp the conflicting nature and the trade-offs among the different objectives in order to select satisfactory compromise solutions. This paper presents a multiple objective mixed integer linear programming model for power generation expansion planning that allows the consideration of modular expansion capacity values of supply-side options. This characteristic of the model avoids the well-known problem associated with continuous capacity values that usually have to be discretized in a post-processing phase without feedback on the nature and importance of the changes in the attributes of the obtained solutions. Demand-side management (DSM) is also considered an option in the planning process, assuming there is a sufficiently large portion of the market under franchise conditions. As DSM full costs are accounted in the model, including lost revenues, it is possible to perform an evaluation of the rate impact in order to further inform the decision process (Author)
A linear bi-level multi-objective program for optimal allocation of water resources.
Directory of Open Access Journals (Sweden)
Ijaz Ahmad
Full Text Available This paper presents a simple bi-level multi-objective linear program (BLMOLP with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON technique which creates a compromise between upper and lower level decision makers (DMs, and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.
Yager’s ranking method for solving the trapezoidal fuzzy number linear programming
Karyati; Wutsqa, D. U.; Insani, N.
2018-03-01
In the previous research, the authors have studied the fuzzy simplex method for trapezoidal fuzzy number linear programming based on the Maleki’s ranking function. We have found some theories related to the term conditions for the optimum solution of fuzzy simplex method, the fuzzy Big-M method, the fuzzy two-phase method, and the sensitivity analysis. In this research, we study about the fuzzy simplex method based on the other ranking function. It is called Yager's ranking function. In this case, we investigate the optimum term conditions. Based on the result of research, it is found that Yager’s ranking function is not like Maleki’s ranking function. Using the Yager’s function, the simplex method cannot work as well as when using the Maleki’s function. By using the Yager’s function, the value of the subtraction of two equal fuzzy numbers is not equal to zero. This condition makes the optimum table of the fuzzy simplex table is undetected. As a result, the simplified fuzzy simplex table becomes stopped and does not reach the optimum solution.
Decision-making methodology of optimal shielding materials by using fuzzy linear programming
International Nuclear Information System (INIS)
Kanai, Y.; Miura, T.; Hirao, Y.
2000-01-01
The main purpose of our studies are to select materials and determine the ratio of constituent materials as the first stage of optimum shielding design to suit the individual requirements of nuclear reactors, reprocessing facilities, casks for shipping spent fuel, etc. The parameters of the shield optimization are cost, space, weight and some shielding properties such as activation rates or individual irradiation and cooling time, and total dose rate for neutrons (including secondary gamma ray) and for primary gamma ray. Using conventional two-valued logic (i.e. crisp) approaches, huge combination calculations are needed to identify suitable materials for optimum shielding design. Also, re-computation is required for minor changes, as the approach does not react sensitively to the computation result. Present approach using a fuzzy linear programming method is much of the decision-making toward the satisfying solution might take place in fuzzy environment. And it can quickly and easily provide a guiding principle of optimal selection of shielding materials under the above-mentioned conditions. The possibility or reducing radiation effects by optimizing the ratio of constituent materials is investigated. (author)
International Nuclear Information System (INIS)
Ding, C; Hrycushko, B; Jiang, S; Meyer, J; Timmerman, R
2014-01-01
Purpose: To compare the radiobiological effect on large tumors and surrounding normal tissues from single fraction SRS, multi-fractionated SRT, and multi-staged SRS treatment. Methods: An anthropomorphic head phantom with a centrally located large volume target (18.2 cm 3 ) was scanned using a 16 slice large bore CT simulator. Scans were imported to the Multiplan treatment planning system where a total prescription dose of 20Gy was used for a single, three staged and three fractionated treatment. Cyber Knife treatment plans were inversely optimized for the target volume to achieve at least 95% coverage of the prescription dose. For the multistage plan, the target was segmented into three subtargets having similar volume and shape. Staged plans for individual subtargets were generated based on a planning technique where the beam MUs of the original plan on the total target volume are changed by weighting the MUs based on projected beam lengths within each subtarget. Dose matrices for each plan were export in DICOM format and used to calculate equivalent dose distributions in 2Gy fractions using an alpha beta ratio of 10 for the target and 3 for normal tissue. Results: Singe fraction SRS, multi-stage plan and multi-fractionated SRT plans had an average 2Gy dose equivalent to the target of 62.89Gy, 37.91Gy and 33.68Gy, respectively. The normal tissue within 12Gy physical dose region had an average 2Gy dose equivalent of 29.55Gy, 16.08Gy and 13.93Gy, respectively. Conclusion: The single fraction SRS plan had the largest predicted biological effect for the target and the surrounding normal tissue. The multi-stage treatment provided for a more potent biologically effect on target compared to the multi-fraction SRT treatments with less biological normal tissue than single-fraction SRS treatment
Shea, John E.
from a catalog of courses is difficult because of the many factors being considered. To assist this process, the multi-objective model and the curriculum requirements were incorporated in a linear program to select the "optimum" curriculum. The application of this tool was also beneficial in identifying the active constraints that limit curriculum development and content.
Verma, Ram U; Seol, Youngsoo
2016-01-01
First a new notion of the random exponential Hanson-Antczak type [Formula: see text]-V-invexity is introduced, which generalizes most of the existing notions in the literature, second a random function [Formula: see text] of the second order is defined, and finally a class of asymptotically sufficient efficiency conditions in semi-infinite multi-objective fractional programming is established. Furthermore, several sets of asymptotic sufficiency results in which various generalized exponential type [Formula: see text]-V-invexity assumptions are imposed on certain vector functions whose components are the individual as well as some combinations of the problem functions are examined and proved. To the best of our knowledge, all the established results on the semi-infinite aspects of the multi-objective fractional programming are new, which is a significantly new emerging field of the interdisciplinary research in nature. We also observed that the investigated results can be modified and applied to several special classes of nonlinear programming problems.
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
Ready-to-use therapeutic food (RUTF) is the standard of care for children suffering from noncomplicated severe acute malnutrition (SAM). The objective was to develop a comprehensive linear programming (LP) tool to create novel RUTF formulations for Ethiopia. A systematic approach that surveyed inter...
Mills, James W.; And Others
1973-01-01
The Study reported here tested an application of the Linear Programming Model at the Reading Clinic of Drew University. Results, while not conclusive, indicate that this approach yields greater gains in speed scores than a traditional approach for this population. (Author)
Maillot, Matthieu; Ferguson, Elaine L; Drewnowski, Adam; Darmon, Nicole
2008-06-01
Nutrient profiling ranks foods based on their nutrient content. They may help identify foods with a good nutritional quality for their price. This hypothesis was tested using diet modeling with linear programming. Analyses were undertaken using food intake data from the nationally representative French INCA (enquête Individuelle et Nationale sur les Consommations Alimentaires) survey and its associated food composition and price database. For each food, a nutrient profile score was defined as the ratio between the previously published nutrient density score (NDS) and the limited nutrient score (LIM); a nutritional quality for price indicator was developed and calculated from the relationship between its NDS:LIM and energy cost (in euro/100 kcal). We developed linear programming models to design diets that fulfilled increasing levels of nutritional constraints at a minimal cost. The median NDS:LIM values of foods selected in modeled diets increased as the levels of nutritional constraints increased (P = 0.005). In addition, the proportion of foods with a good nutritional quality for price indicator was higher (P linear programming and the nutrient profiling approaches indicates that nutrient profiling can help identify foods of good nutritional quality for their price. Linear programming is a useful tool for testing nutrient profiling systems and validating the concept of nutrient profiling.
Patricia K. Lebow; Henry Spelter; Peter J. Ince
2003-01-01
This report provides documentation and user information for FPL-PELPS, a personal computer price endogenous linear programming system for economic modeling. Originally developed to model the North American pulp and paper industry, FPL-PELPS follows its predecessors in allowing the modeling of any appropriate sector to predict consumption, production and capacity by...