An Introduction to Optimization

WileyInterscience Series in Discrete Mathematics and Optimization
John Wiley & Sons, Inc.
New York
Copyright © 1996
ISBN 0471089494, xiii+409 pp.
From the back cover:
An uptodate, accessible introduction to an increasingly important
field
This timely authoritative book fills a growing need for an introductory
text to optimization methods and theory at the senior undergraduate and
beginning graduate levels. With consistently accessible and elementary
treatment of all topics, An Introduction to Optimization
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 workedout examples to illustrate
both theory and algorithms, this book 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 the most recent developments, including neural
networks, genetic algorithms, and the nonsimplex method of Karmarkar
 A chapter on the use of descent algorithms for the training of
neural networks
 Exercise problems after every chapter
 MATLAB exercises and examples
 An optional solutions manual with MATLAB source listings
(Instructors only: To obtain a copy of the solutions manual, see
ordering information
below.)
This book helps students to 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.
Errata
An uptodate errata is available, in
Postscript and
PDF formats.
Brief Table of Contents
(A more detailed table of contents is available.)
 Preface
Part I. Mathematical Review
 1 Methods of Proof and Some Notation
 2 Real Vector Spaces and Matrices
 3 Transformations
 4 Concepts from Geometry
 5 Elements of Differential Calculus
Part II. Unconstrained Optimization
 6 Basics of Unconstrained Optimization
 7 OneDimensional Search Methods
 8 Gradient Methods
 9 Newton's Method
 10 Conjugate Direction Methods
 11 QuasiNewton Methods
 12 Solving Ax=b
 13 Unconstrained Optimization and Feedforward Neural Networks
 14 Genetic Algorithms
Part III. Linear Programming
 15 Introduction to Linear Programming
 16 The Simplex Method
 17 Duality
 18 NonSimplex Methods
Part IV. Nonlinear Constrained Optimization
 19 Problems with Equality Constraints
 20 Problems With Inequality Constraints
 21 Convex Optimization Problems
 22 Algorithms for Constrained Optimization
 Bibliography
 Index
Ordering information
Wiley has
information on how to order the book.
Instructors only:
Copies of the solutions manuals are held inhouse at
Wiley's New York office.
For a copy of the solutions manual, fax an official request
letter on
university letterhead to 2017486825, or contact
Sari Friedman (sfriedman@wiley.com)
Professor Edwin Chong,
This document was last modified
September 09, 2020.