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Introduction to Optimization

ISBN-10: 1118279018
ISBN-13: 9781118279014
Edition: 4th 2013
List price: $181.95 Buy it from $69.24 Rent it from $34.29
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Description: Fully updated to reflect modern developments in the field, this new edition fills the need for an accessible, yet rigorous, introduction to optimization theory and methods.  Featuring innovative coverage and a straightforward approach, the Fourth  More...

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Book details

List price: $181.95
Edition: 4th
Copyright year: 2013
Publisher: John Wiley & Sons, Incorporated
Publication date: 1/4/2013
Binding: Hardcover
Pages: 640
Size: 6.50" wide x 9.50" long x 1.75" tall
Weight: 2.156
Language: English

Fully updated to reflect modern developments in the field, this new edition fills the need for an accessible, yet rigorous, introduction to optimization theory and methods.  Featuring innovative coverage and a straightforward approach, the Fourth Edition includes a new chapter on integer programming, expanded coverage on one-dimensional methods, improvements to the sections on linear matrix inequalities, and numerous new exercises at the end of all chapters.  The book begins with a review of basic definitions and notations and also provides the related fundamental background of linear algebra, geometry, and calculus. With this foundation, the authors explore the essential topics of unconstrained optimization problems, linear programming problems, and nonlinear constrained optimization.  An optimization perspective on global search methods is featured and includes discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm.  In addition, the book includes an elementary introduction to artificial neural networks, convex optimization, and multi-objective optimization, all of which are of tremendous interest to students, researchers, and practitioners.  Numerous diagrams and figures found throughout the book complement the written presentation of key concepts, and each chapter is followed by MATLAB® exercises and drill problems that reinforce the discussed theory and algorithms.

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