Linear And Nonlinear Programming


Linear And Nonlinear Programming
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Linear And Nonlinear Programming


Linear And Nonlinear Programming
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Author : David G. Luenberger
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-07-07

Linear And Nonlinear Programming written by David G. Luenberger and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-07 with Business & Economics categories.


This third edition of the classic textbook in Optimization has been fully revised and updated. It comprehensively covers modern theoretical insights in this crucial computing area, and will be required reading for analysts and operations researchers in a variety of fields. The book connects the purely analytical character of an optimization problem, and the behavior of algorithms used to solve it. Now, the third edition has been completely updated with recent Optimization Methods. The book also has a new co-author, Yinyu Ye of California’s Stanford University, who has written lots of extra material including some on Interior Point Methods.



Problems In Linear And Nonlinear Programming


Problems In Linear And Nonlinear Programming
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Author : S. Vajda
language : en
Publisher: Oxford University Press, USA
Release Date : 1987

Problems In Linear And Nonlinear Programming written by S. Vajda and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Language Arts & Disciplines categories.


This collection of 235 problems is designed for undergraduates who have completed a year's course in mathematical programming. Each section of linear and non-linear problems begins with simple exercises and proceeds to more difficult ones. Solutions are based on first principles and can be found using a desk calculator. Answers to all problems are provided.



Linear And Nonlinear Optimization


Linear And Nonlinear Optimization
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Author : Igor Griva
language : en
Publisher: SIAM
Release Date : 2009-01-01

Linear And Nonlinear Optimization written by Igor Griva and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-01 with Mathematics categories.


Provides an introduction to the applications, theory, and algorithms of linear and nonlinear optimization. The emphasis is on practical aspects - discussing modern algorithms, as well as the influence of theory on the interpretation of solutions or on the design of software. The book includes several examples of realistic optimization models that address important applications. The succinct style of this second edition is punctuated with numerous real-life examples and exercises, and the authors include accessible explanations of topics that are not often mentioned in textbooks, such as duality in nonlinear optimization, primal-dual methods for nonlinear optimization, filter methods, and applications such as support-vector machines. The book is designed to be flexible. It has a modular structure, and uses consistent notation and terminology throughout. It can be used in many different ways, in many different courses, and at many different levels of sophistication.



Linear And Nonlinear Optimization


Linear And Nonlinear Optimization
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Author : Richard W. Cottle
language : en
Publisher: Springer
Release Date : 2017-06-11

Linear And Nonlinear Optimization written by Richard W. Cottle and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-11 with Business & Economics categories.


​This textbook on Linear and Nonlinear Optimization is intended for graduate and advanced undergraduate students in operations research and related fields. It is both literate and mathematically strong, yet requires no prior course in optimization. As suggested by its title, the book is divided into two parts covering in their individual chapters LP Models and Applications; Linear Equations and Inequalities; The Simplex Algorithm; Simplex Algorithm Continued; Duality and the Dual Simplex Algorithm; Postoptimality Analyses; Computational Considerations; Nonlinear (NLP) Models and Applications; Unconstrained Optimization; Descent Methods; Optimality Conditions; Problems with Linear Constraints; Problems with Nonlinear Constraints; Interior-Point Methods; and an Appendix covering Mathematical Concepts. Each chapter ends with a set of exercises. The book is based on lecture notes the authors have used in numerous optimization courses the authors have taught at Stanford University. It emphasizes modeling and numerical algorithms for optimization with continuous (not integer) variables. The discussion presents the underlying theory without always focusing on formal mathematical proofs (which can be found in cited references). Another feature of this book is its inclusion of cultural and historical matters, most often appearing among the footnotes. "This book is a real gem. The authors do a masterful job of rigorously presenting all of the relevant theory clearly and concisely while managing to avoid unnecessary tedious mathematical details. This is an ideal book for teaching a one or two semester masters-level course in optimization – it broadly covers linear and nonlinear programming effectively balancing modeling, algorithmic theory, computation, implementation, illuminating historical facts, and numerous interesting examples and exercises. Due to the clarity of the exposition, this book also serves as a valuable reference for self-study." Professor Ilan Adler, IEOR Department, UC Berkeley "A carefully crafted introduction to the main elements and applications of mathematical optimization. This volume presents the essential concepts of linear and nonlinear programming in an accessible format filled with anecdotes, examples, and exercises that bring the topic to life. The authors plumb their decades of experience in optimization to provide an enriching layer of historical context. Suitable for advanced undergraduates and masters students in management science, operations research, and related fields." Michael P. Friedlander, IBM Professor of Computer Science, Professor of Mathematics, University of British Columbia



Nonlinear Programming


Nonlinear Programming
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Author : J. B. Rosen
language : en
Publisher: Elsevier
Release Date : 2014-05-10

Nonlinear Programming written by J. B. Rosen and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Mathematics categories.


Nonlinear Programming contains the proceedings of a Symposium on Nonlinear Programming held in Madison, Wisconsin on May 4-6, 1970. This book emphasizes algorithms and related theories that lead to efficient computational methods for solving nonlinear programming problems. This compilation consists of 17 chapters. Chapters 1 to 9 are concerned primarily with computational algorithms, while Chapters 10 to 13 are devoted to theoretical aspects of nonlinear programming. Certain applications of nonlinear programming are considered in Chapters 14 to 17. The algorithms for nonlinear constraint problems, investigation of convergence rates, and use of nonlinear programming for approximation are also covered in this text. This publication is a good source for students and researchers concerned with nonlinear programming.



Nonlinear Programming


Nonlinear Programming
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Author : Mokhtar S. Bazaraa
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-12

Nonlinear Programming written by Mokhtar S. Bazaraa and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-12 with Mathematics categories.


COMPREHENSIVE COVERAGE OF NONLINEAR PROGRAMMING THEORY AND ALGORITHMS, THOROUGHLY REVISED AND EXPANDED Nonlinear Programming: Theory and Algorithms—now in an extensively updated Third Edition—addresses the problem of optimizing an objective function in the presence of equality and inequality constraints. Many realistic problems cannot be adequately represented as a linear program owing to the nature of the nonlinearity of the objective function and/or the nonlinearity of any constraints. The Third Edition begins with a general introduction to nonlinear programming with illustrative examples and guidelines for model construction. Concentration on the three major parts of nonlinear programming is provided: Convex analysis with discussion of topological properties of convex sets, separation and support of convex sets, polyhedral sets, extreme points and extreme directions of polyhedral sets, and linear programming Optimality conditions and duality with coverage of the nature, interpretation, and value of the classical Fritz John (FJ) and the Karush-Kuhn-Tucker (KKT) optimality conditions; the interrelationships between various proposed constraint qualifications; and Lagrangian duality and saddle point optimality conditions Algorithms and their convergence, with a presentation of algorithms for solving both unconstrained and constrained nonlinear programming problems Important features of the Third Edition include: New topics such as second interior point methods, nonconvex optimization, nondifferentiable optimization, and more Updated discussion and new applications in each chapter Detailed numerical examples and graphical illustrations Essential coverage of modeling and formulating nonlinear programs Simple numerical problems Advanced theoretical exercises The book is a solid reference for professionals as well as a useful text for students in the fields of operations research, management science, industrial engineering, applied mathematics, and also in engineering disciplines that deal with analytical optimization techniques. The logical and self-contained format uniquely covers nonlinear programming techniques with a great depth of information and an abundance of valuable examples and illustrations that showcase the most current advances in nonlinear problems.



Linear And Nonlinear Programming


Linear And Nonlinear Programming
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Author : Roger Hartley
language : en
Publisher:
Release Date : 1985

Linear And Nonlinear Programming written by Roger Hartley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Mathematics categories.




Linear Complementarity Linear And Nonlinear Programming


Linear Complementarity Linear And Nonlinear Programming
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Author : Katta G. Murty
language : en
Publisher:
Release Date : 1988

Linear Complementarity Linear And Nonlinear Programming written by Katta G. Murty and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Linear complementarity problem categories.




Traces And Emergence Of Nonlinear Programming


Traces And Emergence Of Nonlinear Programming
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Author : Giorgio Giorgi
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-04

Traces And Emergence Of Nonlinear Programming written by Giorgio Giorgi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-04 with Computers categories.


The book contains reproductions of the most important papers that gave birth to the first developments in nonlinear programming. Of particular interest is W. Karush's often quoted Master Thesis, which is published for the first time. The anthology includes an extensive preliminary chapter, where the editors trace out the history of mathematical programming, with special reference to linear and nonlinear programming.​



Linear And Nonlinear Programming


Linear And Nonlinear Programming
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Author : David Gilbert Luenberger
language : en
Publisher:
Release Date : 2000

Linear And Nonlinear Programming written by David Gilbert Luenberger and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Linear programming categories.