Download or read book Computational Experience with an Approximative Method for Solving Large scale Linear Programming Problems written by Károly Patyi and published by . This book was released on 1972 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Survey of Computational Methods for Solving Large Scale Systems written by Stanford University. Department of Operations Research. Operations Research House and published by . This book was released on 1972 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years computational methods for solving large scale mathematical programming problems have improved enormously. The most fundamental of these improvements have been linear programming, where problems are becoming both larger and more complex in their own right and as sub-problems in non-linear and integer programs. Sophisticated new techniques have enhanced the inversion, pivot selection and updating steps of the simplex algorithm, while generalized upper bounding (GUB) has made possible the solution of some problems of staggering size. In integer and non-convex programming new techniques such as special order sets and pseudo-costs have advanced the art to a stage where problems with a few thousand constraints can be handled with confidence. Similarly improvements in the Method of Approximation Programming (MAP) have made the solution of large and complex non-linear programs computationally attractive. (Author).

Download or read book Computational Mathematical Programming written by Karla L. Hoffman and published by . This book was released on 1987 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: An implicit enumeration procedure for the general linear complementarity problem. Recursive quadratic programming methods based on the augmented lagrangian. A primal truncated newton algorithm with application to large-scale nonlinear network optimization. Approximating some convez programs in terms of borel fields. Computer-assisted analysis for diagnosing infeasible or unbounded linear programs. Ventura, restricted simplicial decomposition: computation and extensions.A note solution on approach to linear programming problems with imprecise function and gradient values. Z; a maany, a new algorithm for highly curved constrained optimization. An implementation of an algorithm for univariate minimization and an application to nested optimization. On practical stopping rules for the simplex method. An experimental approach to karmarkar's projective method for linear programming.

Download or read book On Approximative Solution of Large scale Linear Programming Problems written by Ferenc Forgó and published by . This book was released on 1969 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Approximation Algorithms and Metaheuristics written by Teofilo F. Gonzalez and published by CRC Press. This book was released on 2007-05-15 with total page 1434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical applications. It is the first book to comprehensively study both approximation algorithms and metaheuristics. Starting with basic approaches, the handbook presents the methodologies to design and analyze efficient approximation algorithms for a large class of problems, and to establish inapproximability results for another class of problems. It also discusses local search, neural networks, and metaheuristics, as well as multiobjective problems, sensitivity analysis, and stability. After laying this foundation, the book applies the methodologies to classical problems in combinatorial optimization, computational geometry, and graph problems. In addition, it explores large-scale and emerging applications in networks, bioinformatics, VLSI, game theory, and data analysis. Undoubtedly sparking further developments in the field, this handbook provides the essential techniques to apply approximation algorithms and metaheuristics to a wide range of problems in computer science, operations research, computer engineering, and economics. Armed with this information, researchers can design and analyze efficient algorithms to generate near-optimal solutions for a wide range of computational intractable problems.

Download or read book Potential Function Methods for Approximately Solving Linear Programming Problems Theory and Practice written by Daniel Bienstock and published by Springer Science & Business Media. This book was released on 2002-08-31 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments.

Download or read book Algorithms for Continuous Optimization written by E. Spedicato and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NATO Advanced Study Institute on "Algorithms for continuous optimiza tion: the state of the art" was held September 5-18, 1993, at II Ciocco, Barga, Italy. It was attended by 75 students (among them many well known specialists in optimiza tion) from the following countries: Belgium, Brasil, Canada, China, Czech Republic, France, Germany, Greece, Hungary, Italy, Poland, Portugal, Rumania, Spain, Turkey, UK, USA, Venezuela. The lectures were given by 17 well known specialists in the field, from Brasil, China, Germany, Italy, Portugal, Russia, Sweden, UK, USA. Solving continuous optimization problems is a fundamental task in computational mathematics for applications in areas of engineering, economics, chemistry, biology and so on. Most real problems are nonlinear and can be of quite large size. Devel oping efficient algorithms for continuous optimization has been an important field of research in the last 30 years, with much additional impetus provided in the last decade by the availability of very fast and parallel computers. Techniques, like the simplex method, that were already considered fully developed thirty years ago have been thoroughly revised and enormously improved. The aim of this ASI was to present the state of the art in this field. While not all important aspects could be covered in the fifty hours of lectures (for instance multiob jective optimization had to be skipped), we believe that most important topics were presented, many of them by scientists who greatly contributed to their development.

Download or read book Linear Programming Computation written by Ping-Qi PAN and published by Springer. This book was released on 2016-09-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With emphasis on computation, this book is a real breakthrough in the field of LP. In addition to conventional topics, such as the simplex method, duality, and interior-point methods, all deduced in a fresh and clear manner, it introduces the state of the art by highlighting brand-new and advanced results, including efficient pivot rules, Phase-I approaches, reduced simplex methods, deficient-basis methods, face methods, and pivotal interior-point methods. In particular, it covers the determination of the optimal solution set, feasible-point simplex method, decomposition principle for solving large-scale problems, controlled-branch method based on generalized reduced simplex framework for solving integer LP problems.

Download or read book Linear Programming Computation written by Ping-Qi PAN and published by Springer Nature. This book was released on 2023-01-01 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph represents a historic breakthrough in the field of linear programming (LP)since George Dantzig first discovered the simplex method in 1947. Being both thoughtful and informative, it focuses on reflecting and promoting the state of the art by highlighting new achievements in LP. This new edition is organized in two volumes. The first volume addresses foundations of LP, including the geometry of feasible region, the simplex method and its implementation, duality and the dual simplex method, the primal-dual simplex method, sensitivity analysis and parametric LP, the generalized simplex method, the decomposition method, the interior-point method and integer LP method. The second volume mainly introduces contributions of the author himself, such as efficient primal/dual pivot rules, primal/dual Phase-I methods, reduced/D-reduced simplex methods, the generalized reduced simplex method, primal/dual deficient-basis methods, primal/dual face methods, a new decomposition principle, etc. Many important improvements were made in this edition. The first volume includes new results, such as the mixed two-phase simplex algorithm, dual elimination, fresh pricing scheme for reduced cost, bilevel LP models and intercepting of optimal solution set. In particular, the chapter Integer LP Method was rewritten with great gains of the objective cutting for new ILP solvers {\it controlled-cutting/branch} methods, as well as with an attractive implementation of the controlled-branch method. In the second volume, the `simplex feasible-point algorithm' was rewritten, and removed from the chapter Pivotal Interior-Point Method to form an independent chapter with the new title `Simplex Interior-Point Method', as it represents a class of efficient interior-point algorithms transformed from traditional simplex algorithms. The title of the original chapter was then changed to `Facial Interior-Point Method', as the remaining algorithms represent another class of efficient interior-point algorithms transformed from normal interior-point algorithms. Without exploiting sparsity, the original primal/dual face methods were implemented using Cholesky factorization. In order to deal with sparse computation, two new chapters discussing LU factorization were added to the second volume. The most exciting improvement came from the rediscovery of the reduced simplex method. In the first edition, the derivation of its prototype was presented in a chapter with the same title, and then converted into the so-called `improved' version in another chapter. Fortunately, the author recently found a quite concise new derivation, so he can now introduce the distinctive fresh simplex method in a single chapter. It is exciting that the reduced simplex method can be expected to be the best LP solver ever. With a focus on computation, the current edition contains many novel ideas, theories and methods, supported by solid numerical results. Being clear and succinct, its content reveals in a fresh manner, from simple to profound. In particular, a larger number of examples were worked out to demonstrate algorithms. This book is a rare work in LP and an indispensable tool for undergraduate and graduate students, teachers, practitioners, and researchers in LP and related fields.

Download or read book Decomposition of Structured Large scale Optimization Problems and Parallel Optimization written by Deepankar Medhi and published by . This book was released on 1987 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Lancelot written by A.R. Conn and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: LANCELOT is a software package for solving large-scale nonlinear optimization problems. This book is our attempt to provide a coherent overview of the package and its use. This includes details of how one might present examples to the package, how the algorithm tries to solve these examples and various technical issues which may be useful to implementors of the software. We hope this book will be of use to both researchers and practitioners in nonlinear programming. Although the book is primarily concerned with a specific optimization package, the issues discussed have much wider implications for the design and im plementation of large-scale optimization algorithms. In particular, the book contains a proposal for a standard input format for large-scale optimization problems. This proposal is at the heart of the interface between a user's problem and the LANCE LOT optimization package. Furthermore, a large collection of over five hundred test ex amples has already been written in this format and will shortly be available to those who wish to use them. We would like to thank the many people and organizations who supported us in our enterprise. We first acknowledge the support provided by our employers, namely the the Facultes Universitaires Notre-Dame de la Paix (Namur, Belgium), Harwell Laboratory (UK), IBM Corporation (USA), Rutherford Appleton Laboratory (UK) and the University of Waterloo (Canada). We are grateful for the support we obtained from NSERC (Canada), NATO and AMOCO (UK).

Download or read book Very Large scale Linear Programming a Case Study in Combining Interior Point and Simplex Methods written by R. E. Bixby and published by . This book was released on 1991 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology written by Neculai Andrei and published by Springer. This book was released on 2017-12-04 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the theoretical details and computational performances of algorithms used for solving continuous nonlinear optimization applications imbedded in GAMS. Aimed toward scientists and graduate students who utilize optimization methods to model and solve problems in mathematical programming, operations research, business, engineering, and industry, this book enables readers with a background in nonlinear optimization and linear algebra to use GAMS technology to understand and utilize its important capabilities to optimize algorithms for modeling and solving complex, large-scale, continuous nonlinear optimization problems or applications. Beginning with an overview of constrained nonlinear optimization methods, this book moves on to illustrate key aspects of mathematical modeling through modeling technologies based on algebraically oriented modeling languages. Next, the main feature of GAMS, an algebraically oriented language that allows for high-level algebraic representation of mathematical optimization models, is introduced to model and solve continuous nonlinear optimization applications. More than 15 real nonlinear optimization applications in algebraic and GAMS representation are presented which are used to illustrate the performances of the algorithms described in this book. Theoretical and computational results, methods, and techniques effective for solving nonlinear optimization problems, are detailed through the algorithms MINOS, KNITRO, CONOPT, SNOPT and IPOPT which work in GAMS technology.

Download or read book Computational Techniques of the Simplex Method written by István Maros and published by Springer Science & Business Media. This book was released on 2002-12-31 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Techniques of the Simplex Method is a systematic treatment focused on the computational issues of the simplex method. It provides a comprehensive coverage of the most important and successful algorithmic and implementation techniques of the simplex method. It is a unique source of essential, never discussed details of algorithmic elements and their implementation. On the basis of the book the reader will be able to create a highly advanced implementation of the simplex method which, in turn, can be used directly or as a building block in other solution algorithms.

Download or read book On Large scale Linear Programming written by Markku Juhani Kallio and published by . This book was released on 1975 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Three classes of methods are proposed for solving large-scale linear programs. First, sequential projection is applied to reformulate the linear program as a dynamic program. Second, the revised simplex method using a special factorization for the basis is considered. Third, a class of feasible direction methods is presented. A comparison of these three classes is made. A probabilistic model is developed to estimate computational effort for matrix multiplications. This model is applied to estimate computational effort for linear programming algorithms.

Download or read book Large Scale Nonlinear Optimization written by Gianni Pillo and published by Springer Science & Business Media. This book was released on 2006-06-03 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews and discusses recent advances in the development of methods and algorithms for nonlinear optimization and its applications, focusing on the large-dimensional case, the current forefront of much research. Individual chapters, contributed by eminent authorities, provide an up-to-date overview of the field from different and complementary standpoints, including theoretical analysis, algorithmic development, implementation issues and applications.

Download or read book Large Scale Optimization written by William W. Hager and published by Springer. This book was released on 1994-05-31 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of papers presented at the Large Scale Optimization Conference held at the Center for Applied Optimization, University of Florida, Gainesville, in February, 1993. Accurate modelling of scientific problems often leads to the formulation of large-scale optimization problems involving thousands of continuous and/or discrete variables. As a consequence of new algorithmic developments and of the increased power of computers, large-scale optimization has seen a dramatic increase in activities in the past decade. Topics include large-scale linear, nonlinear and stochastic programming, network optimization, decomposition methods, methods for optimal control, nonsmooth equations, integer programming, and software development. In addition, applications are included in location theory, structural mechanics, molecular configuration, transportation, multitarget tracking, and database design. The book is a valuable source of information for faculty students and researchers in mathematical programming and related fields.