An Introduction to Optimization, Second Edition
-
Wiley-Interscience Series in Discrete Mathematics and Optimization
John Wiley & Sons, Inc.
New York
Copyright © 2001
ISBN 0-471-39126-3, xvi+476 pp.
From the back cover:
A modern, up-to-date introduction to optimzation 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 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 interior-point methods
- A chapter on the use of descent algorithms for the training of
neural networks
- Exercise problems after every chapter
- MATLAB exercises and examples
- Accompanying Instructor's Solutions Manual available on request
(Instructors only: To obtain a copy of the solutions manual, see
ordering information
below.)
An Introduction to Optimization, Second Edition
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 up-to-date 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 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 Ax=b
- 13 Unconstrained Optimization and Neural Networks
- 14 Genetic Algorithms
Part III. Linear Programming
- 15 Introduction to Linear Programming
- 16 Simplex Method
- 17 Duality
- 18 Non-Simplex 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
- References
- Index
Ordering information
Wiley has
information on how to order the book.
Instructors only:
Copies of the solutions manuals are held in-house at
Wiley's New York office.
For a copy of the solutions manual, fax an official request letter on
university letterhead to 201-748-6825, or contact
Sari Friedman (sfriedman@wiley.com)
Professor Edwin Chong,
This document was last modified
September 09, 2020.