An Introduction to Optimization, Fourth Edition

Edwin K. P. Chong and Stanislaw H. Żak

Wiley-Interscience Series in Discrete Mathematics and Optimization
John Wiley & Sons, Inc.
New York
Copyright © 2013
ISBN: 978-1-1182-7901-4
640 pages

From the back cover:

Praise for the Third Edition
". guides and leads the reader through the learning path . examples are stated very clearly and the results are presented with attention to detail."
MAA Reviews

Fully updated to reflect new developments in the field, the Fourth Edition of Introduction to Optimization fills the need for accessible treatment on optimization theory and methods with an emphasis on engineering design. Basic definitions and notations are provided in addition to the related fundamental background for linear algebra, geometry, and calculus.

This new edition explores the essential topics of unconstrained optimization problems, linear programming problems, and nonlinear constrained optimization. The authors also present an optimization perspective on global search methods and include discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm.

• A new chapter on integer programming
• Expanded coverage of one-dimensional methods
• Updated and expanded sections on linear matrix inequalities
• Numerous new exercises at the end of each chapter
• MATLAB� exercises and drill problems to reinforce the discussed and algorithms
• Numerous diagrams and figures that complement the written of key concepts
• MATLAB� M-files for implementation of the discussed theory and algorithms (available via the book's website)

Errata

Brief Table of Contents

Part I. Mathematical Review

1 Methods of Proof and Some Notation 2 Vector Spaces and Matrices 3 Transformations 4 Concepts from Geometry 5 Elements of Calculus

Part II. Unconstrained Optimization

6 Basics of Set-Constrained and Unconstrained Optimization 7 One-Dimensional Search Methods 8 Gradient Methods 9 Newton's Method 10 Conjugate Direction Methods 11 Quasi-Newton Methods 12 Solving Linear Equations 13 Unconstrained Optimization and Neural Networks 14 Global Search Algorithms

Part III. Linear Programming

15 Introduction to Linear Programming 16 Simplex Method 17 Duality 18 Nonsimplex Methods 19 Integer Linear Programming

Part IV. Nonlinear Constrained Optimization

20 Problems with Equality Constraints 21 Problems With Inequality Constraints 22 Convex Optimization Problems 23 Algorithms for Constrained Optimization 24 Multiobjective Optimization References Index