Details

An Introduction to Optimization

2. Aufl.

von: Edwin K. P. Chong, Stanislaw H. Zak
80,99 €
Verlag:	Wiley
Format:	PDF
Veröffentl.:	05.04.2004
ISBN/EAN:	9780471654001
Sprache:	englisch
Anzahl Seiten:	496

In den Warenkorb

Als Gutschein

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

Titelbeschreibung

A modern, up-to-date introduction to optimization theory and methods This authoritative book serves as an introductory text to optimization at the senior undergraduate and beginning graduate levels. With consistently accessible and elementary treatment of all topics, An Introduction to Optimization, Second Edition 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 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 recent developments, including neural networks, genetic algorithms, and interior-point methods * A chapter on the use of descent algorithms for the training of feedforward neural networks * Exercise problems after every chapter, many new to this edition * MATLAB(r) exercises and examples * Accompanying Instructor's Solutions Manual available on request An Introduction to Optimization, Second Edition 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. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

Inhaltsverzeichnis

Preface. xiii PART I MATHEMATICAL REVIEW Methods of Proof and Some Notation 1 Vector Spaces and Matrices 5 Transformations 21 Concepts from Geometry 39 Elements of Calculus 49 Part II UNCONSTRAINED OPTIMIZATION Basics of Set-Constrained and Unconstrained Optimization 73 One-Dimensional Search Methods 91 Gradient Methods 113 Newton's Method 139 Conjugate Direction Methods 151 Quasi-Newton Methods 167 Solving Ax = b 187 Unconstrained Optimization and Neural Networks 219 Genetic Algorithms 237 Part III LINEAR PROGRAMMING Introduction to Linear Programming. 255 Simplex Method 287 Duality 321 Non-Simplex Methods 339 Part IV NONLINEAR CONSTRAINED OPTIMIZATION Problems with Equality Constraints 365 Problems with Inequality Constraints 397 Convex Optimization Problems 417 Algorithms for Constrained Optimization 439 References 455 Index 462

Rezension

"...an excellent introduction to optimization theory..." (Journal of Mathematical Psychology, 2002) "A textbook for a one-semester course on optimization theory and methods at the senior undergraduate or beginning graduate level." (SciTech Book News, Vol. 26, No. 2, June 2002)

Autorenportrait

EDWIN K. P. CHONG, PhD, is Professor of Electrical and Computer Engineering at Colorado State University, Fort Collins, Colorado. He was an Associate Editor for the IEEE Transactions on Automatic Control and received the 1998 ASEE Frederick Emmons Terman Award. STANISLAW H. ZAK, PhD, is Professor in the School of Electrical and Computer Engineering at Purdue University, West Lafayette, Indiana. He was an Associate Editor of Dynamics and Control and the IEEE Transactions on Neural Networks.

Back cover copy

A modern, up-to-date introduction to optimization theory and methods This authoritative book serves as an introductory text to optimization at the senior undergraduate and beginning graduate levels. With consistently accessible and elementary treatment of all topics, An Introduction to Optimization, Second Edition 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 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 recent developments, including neural networks, genetic algorithms, and interior-point methods * A chapter on the use of descent algorithms for the training of feedforward neural networks * Exercise problems after every chapter, many new to this edition * MATLAB(r) exercises and examples * Accompanying Instructor's Solutions Manual available on request An Introduction to Optimization, Second Edition 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.