Problems In Linear And Nonlinear Programming
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Problems In Linear And Non Linear Programming
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Author : S. Vajda
language : en
Publisher: Oxford University Press, USA
Release Date : 1987
Problems In Linear And Non Linear 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.
Problems In Linear And Nonlinear Programming
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Author : S. Vajda
language : en
Publisher:
Release Date : 1975
Problems In Linear And Nonlinear Programming written by S. Vajda and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1975 with Linear programming categories.
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
Linear And Nonlinear Programming
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Author : David G. Luenberger
language : en
Publisher: Springer
Release Date : 2015-06-25
Linear And Nonlinear Programming written by David G. Luenberger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-25 with Business & Economics categories.
This new edition covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely analytical character of an optimization problem and the behavior of algorithms used to solve a problem. This was a major theme of the first edition of this book and the fourth edition expands and further illustrates this relationship. As in the earlier editions, the material in this fourth edition is organized into three separate parts. Part I is a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. It is possible to go directly into Parts II and III omitting Part I, and, in fact, the book has been used in this way in many universities. New to this edition is a chapter devoted to Conic Linear Programming, a powerful generalization of Linear Programming. Indeed, many conic structures are possible and useful in a variety of applications. It must be recognized, however, that conic linear programming is an advanced topic, requiring special study. Another important topic is an accelerated steepest descent method that exhibits superior convergence properties, and for this reason, has become quite popular. The proof of the convergence property for both standard and accelerated steepest descent methods are presented in Chapter 8. As in previous editions, end-of-chapter exercises appear for all chapters. From the reviews of the Third Edition: “... this very well-written book is a classic textbook in Optimization. It should be present in the bookcase of each student, researcher, and specialist from the host of disciplines from which practical optimization applications are drawn.” (Jean-Jacques Strodiot, Zentralblatt MATH, Vol. 1207, 2011)
Linear Programs And Related Problems
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Author : Evar D. Nering
language : en
Publisher: Academic Press
Release Date : 1993
Linear Programs And Related Problems written by Evar D. Nering and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Computers categories.
This text is concerned primarily with the theory of linear and nonlinear programming, and a number of closely-related problems, and with algorithms appropriate to those problems. In the first part of the book, the authors introduce the concept of duality which serves as a unifying concept throughout the book. The simplex algorithm is presented along with modifications and adaptations to problems with special structures. Two alternative algorithms, the ellipsoidal algorithm and Karmarker's algorithm, are also discussed, along with numerical considerations. the second part of the book looks at specific types of problems and methods for their solution. This book is designed as a textbook for mathematical programming courses, and each chapter contains numerous exercises and examples.
Optimization Theory For Large Systems
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Author : Leon S. Lasdon
language : en
Publisher: Courier Corporation
Release Date : 2002-01-01
Optimization Theory For Large Systems written by Leon S. Lasdon and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-01-01 with Mathematics categories.
Important text examines most significant algorithms for optimizing large systems and clarifying relations between optimization procedures. Much data appear as charts and graphs and will be highly valuable to readers in selecting a method and estimating computer time and cost in problem-solving. Initial chapter on linear and nonlinear programming presents all necessary background for subjects covered in rest of book. Second chapter illustrates how large-scale mathematical programs arise from real-world problems. Appendixes. List of Symbols.
Linear And Nonlinear Programming Essentials
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Author : Tanushri Kaniyar
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Linear And Nonlinear Programming Essentials written by Tanushri Kaniyar and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.
"Linear and Nonlinear Programming Essentials" is a comprehensive textbook crafted for undergraduate students, providing an in-depth exploration of optimization theory and practice. Designed to be both accessible and rigorous, this book is an essential resource for students in mathematics, computer science, engineering, economics, and related fields. We begin with an introduction to linear programming, covering fundamental concepts such as linear programming models, the simplex method, duality theory, and sensitivity analysis. Building upon this foundation, we delve into nonlinear programming, exploring convex optimization, gradient-based methods, and algorithms for solving nonlinear optimization problems. Our emphasis on bridging theory with practice is a distinguishing feature. Real-world examples and case studies from fields like logistics, finance, and machine learning illustrate the practical relevance of optimization techniques, providing tangible insights into their applications. With clear explanations, illustrative examples, and engaging exercises, we make the content suitable for students at all levels of expertise. Whether you're encountering optimization for the first time or seeking to deepen your understanding of advanced techniques, "Linear and Nonlinear Programming Essentials" offers a comprehensive and engaging journey into the world of optimization. This book equips you with the tools to tackle optimization problems confidently and proficiently.
Scientific And Technical Aerospace Reports
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Author :
language : en
Publisher:
Release Date : 1971
Scientific And Technical Aerospace Reports written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with Aeronautics categories.
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.
Fuzzy Logic And Neural Network Handbook
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Author : Chi-hau Chen
language : en
Publisher: McGraw-Hill Companies
Release Date : 1996
Fuzzy Logic And Neural Network Handbook written by Chi-hau Chen and has been published by McGraw-Hill Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.
A practical reference that presents concise and comprehensive reports on the major activities in fuzzy logic and neural networks, with emphasis on the applications and systems of interest to computer engineers. Each of the 31 chapters focuses on the most important activity of a specific topic, and the chapters are organized into three parts: principles and algorithms; applications; and architectures and systems. The applications for fuzzy logic include home appliance design and manufacturing process; those for neural networks include radar, sonar, and speech signal processing, remote sensing, and electrical power systems. Annotation copyright by Book News, Inc., Portland, OR