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Introduction To Linear Optimization And Extensions With Matlabr
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Book Synopsis Introduction to Linear Optimization and Extensions with MATLAB by : Roy H. Kwon
Download or read book Introduction to Linear Optimization and Extensions with MATLAB written by Roy H. Kwon and published by CRC Press. This book was released on 2013-09-05 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with MATLAB provides a concrete and intuitive yet rigorous introduction to modern linear optimization. In addition to fundamental topics, the book discusses current l
Book Synopsis Introduction to Linear Optimization and Extensions with MATLAB® by : Roy H. Kwon
Download or read book Introduction to Linear Optimization and Extensions with MATLAB® written by Roy H. Kwon and published by CRC Press. This book was released on 2013-09-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with MATLAB® provides a concrete and intuitive yet rigorous introduction to modern linear optimization. In addition to fundamental topics, the book discusses current linear optimization technologies such as predictor-path following interior point methods for both linear and quadratic optimization as well as the inclusion of linear optimization of uncertainty i.e. stochastic programming with recourse and robust optimization. The author introduces both stochastic programming and robust optimization as frameworks to deal with parameter uncertainty. The author’s unusual approach—developing these topics in an introductory book—highlights their importance. Since most applications require decisions to be made in the face of uncertainty, the early introduction of these topics facilitates decision making in real world environments. The author also includes applications and case studies from finance and supply chain management that involve the use of MATLAB. Even though there are several LP texts in the marketplace, most do not cover data uncertainty using stochastic programming and robust optimization techniques. Most emphasize the use of MS Excel, while this book uses MATLAB which is the primary tool of many engineers, including financial engineers. The book focuses on state-of-the-art methods for dealing with parameter uncertainty in linear programming, rigorously developing theory and methods. But more importantly, the author’s meticulous attention to developing intuition before presenting theory makes the material come alive.
Book Synopsis Linear Programming with MATLAB by : Michael C. Ferris
Download or read book Linear Programming with MATLAB written by Michael C. Ferris and published by SIAM. This book was released on 2007-01-01 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a self-contained introduction to linear programming using MATLAB software to elucidate the development of algorithms and theory. Early chapters cover linear algebra basics, the simplex method, duality, the solving of large linear problems, sensitivity analysis, and parametric linear programming. In later chapters, the authors discuss quadratic programming, linear complementarity, interior-point methods, and selected applications of linear programming to approximation and classification problems. Exercises are interwoven with the theory presented in each chapter, and two appendices provide additional information on linear algebra, convexity, nonlinear functions, and on available MATLAB commands, respectively. Readers can access MATLAB codes and associated mex files at a Web site maintained by the authors. Only a basic knowledge of linear algebra and calculus is required to understand this textbook, which is geared toward junior and senior-level undergraduate students, first-year graduate students, and researchers unfamiliar with linear programming.
Book Synopsis Introduction to Linear Programming with MATLAB by : Shashi Kant Mishra
Download or read book Introduction to Linear Programming with MATLAB written by Shashi Kant Mishra and published by CRC Press. This book was released on 2017-09-07 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on the lecture notes of the author delivered to the students at the Institute of Science, Banaras Hindu University, India. It covers simplex, revised simplex, two-phase method, duality, dual simplex, complementary slackness, transportation and assignment problems with good number of examples, clear proofs, MATLAB codes and homework problems. The book will be useful for both students and practitioners.
Book Synopsis Linear Programming Using MATLAB® by : Nikolaos Ploskas
Download or read book Linear Programming Using MATLAB® written by Nikolaos Ploskas and published by Springer. This book was released on 2017-10-28 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 rules, basis update methods, and sensitivity analysis.
Book Synopsis Linear Optimization and Extensions by : Dimitris Alevras
Download or read book Linear Optimization and Extensions written by Dimitris Alevras and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Books on a technical topic - like linear programming - without exercises ignore the principal beneficiary of the endeavor of writing a book, namely the student - who learns best by doing course. Books with exercises - if they are challenging or at least to some extent so exercises, of - need a solutions manual so that students can have recourse to it when they need it. Here we give solutions to all exercises and case studies of M. Padberg's Linear Optimization and Exten sions (second edition, Springer-Verlag, Berlin, 1999). In addition we have included several new exercises and taken the opportunity to correct and change some of the exercises of the book. Here and in the main text of the present volume the terms "book", "text" etc. designate the second edition of Padberg's LPbook and the page and formula references refer to that edition as well. All new and changed exercises are marked by a star * in this volume. The changes that we have made in the original exercises are inconsequential for the main part of the original text where several ofthe exercises (especiallyin Chapter 9) are used on several occasions in the proof arguments. None of the exercises that are used in the estimations, etc. have been changed.
Book Synopsis Introduction to Nonlinear Optimization by : Amir Beck
Download or read book Introduction to Nonlinear Optimization written by Amir Beck and published by . This book was released on 2014 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the foundations of the theory of nonlinear optimization as well as some related algorithms and presents a variety of applications from diverse areas of applied sciences. The author combines three pillars of optimization-theoretical and algorithmic foundation, familiarity with various applications, and the ability to apply the theory and algorithms on actual problems--and rigorously and gradually builds the connection between theory, algorithms, applications, and implementation.
Book Synopsis Solving Optimization Problems with MATLAB® by : Dingyü Xue
Download or read book Solving Optimization Problems with MATLAB® written by Dingyü Xue and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-04-06 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on solving optimization problems with MATLAB. Descriptions and solutions of nonlinear equations of any form are studied first. Focuses are made on the solutions of various types of optimization problems, including unconstrained and constrained optimizations, mixed integer, multiobjective and dynamic programming problems. Comparative studies and conclusions on intelligent global solvers are also provided.
Book Synopsis Linear Optimization and Extensions by : Manfred Padberg
Download or read book Linear Optimization and Extensions written by Manfred Padberg and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the reviews: "Do you know M.Padberg's Linear Optimization and Extensions? [...] Now here is the continuation of it, discussing the solutions of all its exercises and with detailed analysis of the applications mentioned. Tell your students about it. [...] For those who strive for good exercises and case studies for LP this is an excellent volume." Acta Scientiarum Mathematicarum
Book Synopsis Optimization Methods and Mathematical Programming Using MATLAB by : Scientific Books
Download or read book Optimization Methods and Mathematical Programming Using MATLAB written by Scientific Books and published by Createspace Independent Publishing Platform. This book was released on 2016-01-08 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book iegins by introducing the MATLAB environment and the structure of MATLAB programming. Below it is developed especially the Optimization Toolbox that includes algorithms for solving multiobjective problems, non-linear minimization with boundary conditions and restrictions, minimax optimization, semi-infinitely constrained minimization and linear and quadratic programming. A wide range of exercises are included, illustrating techniques such as linear programming, quadratic programming, non-linear least-squares and the solution of non-linear equations. These topics are augmented with examples that put into practice the most widely used optimization methods.
Book Synopsis Optimization in Practice with MATLAB® by : Achille Messac
Download or read book Optimization in Practice with MATLAB® written by Achille Messac and published by Cambridge University Press. This book was released on 2015-03-19 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization in Practice with MATLAB® provides a unique approach to optimization education. It is accessible to both junior and senior undergraduate and graduate students, as well as industry practitioners. It provides a strongly practical perspective that allows the student to be ready to use optimization in the workplace. It covers traditional materials, as well as important topics previously unavailable in optimization books (e.g. numerical essentials - for successful optimization). Written with both the reader and the instructor in mind, Optimization in Practice with MATLAB® provides practical applications of real-world problems using MATLAB®, with a suite of practical examples and exercises that help the students link the theoretical, the analytical, and the computational in each chapter. Additionally, supporting MATLAB® m-files are available for download via www.cambridge.org.messac. Lastly, adopting instructors will receive a comprehensive solution manual with solution codes along with lectures in PowerPoint with animations for each chapter, and the text's unique flexibility enables instructors to structure one- or two-semester courses.
Book Synopsis Operations Research. Optimization With Matlab. Multiobjective, Quadratic and Mixed Programming by : Perez C.
Download or read book Operations Research. Optimization With Matlab. Multiobjective, Quadratic and Mixed Programming written by Perez C. and published by . This book was released on 2017-08-16 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The generalization of optimization theory and techniques to other formulations comprises a large area of applied mathematics. Optimization includes finding "best available" values of some objective function given a defined domain (or input), including a variety of different types of objective functions and different types of domains.Adding more than one objective to an optimization problem adds complexity. For example, to optimize a structural design, one would desire a design that is both light and rigid. When two objectives conflict, a trade-off must be created. There may be one lightest design, one stiffest design, and an infinite number of designs that are some compromise of weight and rigidity. The set of trade-off designs that cannot be improved upon according to one criterion without hurting another criterion is known as the Pareto set. The curve created plotting weight against stiffness of the best designs is known as the Pareto frontier.A design is judged to be "Pareto optimal" (equivalently, "Pareto efficient" or in the Pareto set) if it is not dominated by any other design: If it is worse than another design in some respects and no better in any respect, then it is dominated and is not Pareto optimal. The choice among "Pareto optimal" solutions to determine the "favorite solution" is delegated to the decision maker. In other words, defining the problem as multi-objective optimization signals that some information is missing: desirable objectives are given but combinations of them are not rated relative to each other. In some cases, the missing information can be derived by interactive sessions with the decision maker.Multi-objective optimization problems have been generalized further into vector optimization problems where the (partial) ordering is no longer given by the Pareto ordering.Optimization problems are often multi-modal; that is, they possess multiple good solutions. They could all be globally good or there could be a mix of globally good and locally good solutions. Obtaining all (or at least some of) the multiple solutions is the goal of a multi-modal optimizer.Classical optimization techniques due to their iterative approach do not perform satisfactorily when they are used to obtain multiple solutions, since it is not guaranteed that different solutions will be obtained even with different starting points in multiple runs of the algorithm. Evolutionary algorithms, however, are a very popular approach to obtain multiple solutions in a multi-modal optimization task.This book develops the following topics:* "Multiobjective Optimization Algorithms" * "Using fminimax with a Simulink Model" * "Signal Processing Using fgoalattain" * "Generate and Plot a Pareto Front" * "Linear Programming Algorithms" * "Maximize Long-Term Investments Using Linear Programming" * "Mixed-Integer Linear Programming Algorithms" * "Tuning Integer Linear Programming" * "Mixed-Integer Linear Programming Basics" * "Optimal Dispatch of Power Generators" * "Mixed-Integer Quadratic Programming Portfolio Optimization" * "Quadratic Programming Algorithms"* "Quadratic Minimization with Bound Constraints" * "Quadratic Minimization with Dense, Structured Hessian"* "Large Sparse Quadratic Program with Interior Point Algorithm" * "Least-Squares (Model Fitting) Algorithms" * "lsqnonlin with a Simulink Model" * "Nonlinear Least Squares With and Without Jacobian" * "Linear Least Squares with Bound Constraints" * "Optimization App with the lsqlin Solver" * "Maximize Long-Term Investments Using Linear Programming" * "Jacobian Multiply Function with Linear Least Squares" * "Nonlinear Curve Fitting with lsqcurvefit" * "Fit a Model to Complex-Valued Data" * "Systems of Equations" * "Nonlinear Equations with Analytic Jacobian" * "Nonlinear Equations with Jacobian" * "Nonlinear Equations with Jacobian Sparsity Pattern"* "Nonlinear Systems with Constraints" * "Parallel Computing for Optimization"
Book Synopsis Applied Optimization with MATLAB Programming by : P. Venkataraman
Download or read book Applied Optimization with MATLAB Programming written by P. Venkataraman and published by John Wiley & Sons. This book was released on 2009-03-23 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology/Engineering/Mechanical Provides all the tools needed to begin solving optimization problems using MATLAB® The Second Edition of Applied Optimization with MATLAB® Programming enables readers to harness all the features of MATLAB® to solve optimization problems using a variety of linear and nonlinear design optimization techniques. By breaking down complex mathematical concepts into simple ideas and offering plenty of easy-to-follow examples, this text is an ideal introduction to the field. Examples come from all engineering disciplines as well as science, economics, operations research, and mathematics, helping readers understand how to apply optimization techniques to solve actual problems. This Second Edition has been thoroughly revised, incorporating current optimization techniques as well as the improved MATLAB® tools. Two important new features of the text are: Introduction to the scan and zoom method, providing a simple, effective technique that works for unconstrained, constrained, and global optimization problems New chapter, Hybrid Mathematics: An Application, using examples to illustrate how optimization can develop analytical or explicit solutions to differential systems and data-fitting problems Each chapter ends with a set of problems that give readers an opportunity to put their new skills into practice. Almost all of the numerical techniques covered in the text are supported by MATLAB® code, which readers can download on the text's companion Web site www.wiley.com/go/venkat2e and use to begin solving problems on their own. This text is recommended for upper-level undergraduate and graduate students in all areas of engineering as well as other disciplines that use optimization techniques to solve design problems.
Book Synopsis Introduction to Nonlinear Optimization by : Amir Beck
Download or read book Introduction to Nonlinear Optimization written by Amir Beck and published by SIAM. This book was released on 2023-06-29 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Built on the framework of the successful first edition, this book serves as a modern introduction to the field of optimization. The author’s objective is to provide the foundations of theory and algorithms of nonlinear optimization as well as to present a variety of applications from diverse areas of applied sciences. Introduction to Nonlinear Optimization gradually yet rigorously builds connections between theory, algorithms, applications, and actual implementation. The book contains several topics not typically included in optimization books, such as optimality conditions in sparsity constrained optimization, hidden convexity, and total least squares. Readers will discover a wide array of applications such as circle fitting, Chebyshev center, the Fermat–Weber problem, denoising, clustering, total least squares, and orthogonal regression. These applications are studied both theoretically and algorithmically, illustrating concepts such as duality. Python and MATLAB programs are used to show how the theory can be implemented. The extremely popular CVX toolbox (MATLAB) and CVXPY module (Python) are described and used. More than 250 theoretical, algorithmic, and numerical exercises enhance the reader's understanding of the topics. (More than 70 of the exercises provide detailed solutions, and many others are provided with final answers.) The theoretical and algorithmic topics are illustrated by Python and MATLAB examples. This book is intended for graduate or advanced undergraduate students in mathematics, computer science, electrical engineering, and potentially other engineering disciplines.
Author :Reyolando M.L.R.F. Brasil Publisher :Walter de Gruyter GmbH & Co KG ISBN 13 :3110625679 Total Pages :160 pages Book Rating :4.1/5 (16 download)
Book Synopsis Project Optimization by : Reyolando M.L.R.F. Brasil
Download or read book Project Optimization written by Reyolando M.L.R.F. Brasil and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-10-04 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and easy to understand introduction to a wide range of tools to help designers to optimize their projects. The authors are engineers and therefore many of the examples are on engineering applications, but the techniques presented are common to various areas of knowledge and pervade disciplinary divisions. The book describes the fundamental ideas, mathematical and graphic methods and shows how to use Matlab and EXCEL for optimization.
Book Synopsis Linear Programming by : Robert J Vanderbei
Download or read book Linear Programming written by Robert J Vanderbei and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to optimization. It details constrained optimization, beginning with a substantial treatment of linear programming and proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. Coverage underscores the purpose of optimization: to solve practical problems on a computer. C programs that implement the major algorithms and JAVA tools are available online.
Book Synopsis An Introduction to Optimization by : Edwin K. P. Chong
Download or read book An Introduction to Optimization written by Edwin K. P. Chong and published by Wiley-Interscience. This book was released on 1996 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely and authoritative book fills a growing need for an introductory text to optimization methods and theory at the senior undergraduate and beginning graduate levels. With consistently accessible and elementary treatment of all topics, An Introduction to Optimization helps students build a solid working knowledge of the field, including unconstrained optimization, linear programming, and constrained optimization. Supplemented with more than one hundred tables and illustrations, an extensive bibliography, and numerous worked-out examples to illustrate both theory and algorithms, this book also provides: a review of the required mathematical background material; a mathematical discussion at a level accessible to MBA and business students; a treatment of both linear and nonlinear programming; an introduction to the most recent developments, including neural networks, genetic algorithms, and the nonsimplex method of Karmarkar; a chapter on the use of descent algorithms for the training of feedforward neural networks; exercise problems after every chapter; MATLAB exercises and examples; and an optional solutions manual with MATLAB source listings. This book helps students prepare for the advanced topics and technological developments that lie ahead. It is also a useful book for researchers and professionals in mathematics, electrical engineering, economics, statistics, and business.
