An Introduction to Optimization, Fourth Edition
Wiley-Interscience Series in Discrete Mathematics and Optimization
John Wiley & Sons, Inc.
Copyright © 2013
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."
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
Featuring an elementary introduction to artificial neural networks,
convex optimization, and multi-objective optimization, the Fourth
Edition also offers:
Introduction to Optimization, Fourth Edition is an ideal textbook
for courses on optimization theory and methods. In addition, the
book is also a useful reference for professionals in mathematics,
operations research, electrical engineering, economics, statistics,
- 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
- MATLABŪ exercises and drill problems to reinforce the discussed and algorithms
- Numerous diagrams and figures that complement the written of key concepts
- MATLABŪ M-files for implementation of the discussed theory and
algorithms (available via the book's website)
An up-to-date errata is available.
Brief Table of Contents
(A more detailed table of contents is available.)
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
information on how to order the book.
Instructors only: The Instructor's Solutions Manual is available
to Instructors who adopt the book. Please visit the Book Companion
Site for the book and register to receive access to the Solutions:
Website for courses:
translation by Alexander Nikiforov,
Professor, Doctor of Physical and Mathematical Sciences, Head of the
Kazan Technical University named after AN Tupolev (KNITU-KAI).
Translation by Artur Weber.
this page in Hindi
the Third Edition page in Romanian courtesy of azoft
View the Third Edition
page in Polish.
Professor Edwin Chong,
This document was last modified
May 28, 2019.