Introduction to Global Optimization / Edition 2

by R. Horst, Panos M. Pardalos, Nguyen Van Thoai

Overview

Global optimization concerns the computation and characterization of global optima of nonlinear functions. Such problems are widespread in the mathematical modelling of real systems in a very wide range of applications and the last 30 years have seen the development of many new theoretical, algorithmic and computational contributions which have helped to solve globally multiextreme problems in important practical applications.
Most of the existing books on optimization focus on the problem of computing locally optimal solutions. Introduction to Global Optimization, however, is a comprehensive textbook on constrained global optimization that covers the fundamentals of the subject, presenting much new material, including algorithms, applications and complexity results for quadratic programming, concave minimization, DC and Lipschitz problems, and nonlinear network flow. Each chapter contains illustrative examples and ends with carefully selected exercises, designed to help students grasp the material and enhance their knowledge of the methods involved.
Audience: Students of mathematical programming, and all scientists, from whatever discipline, who need global optimization methods in such diverse areas as economic modelling, fixed charges, finance, networks and transportation, databases, chip design, image processing, nuclear and mechanical design, chemical engineering design and control, molecular biology, and environmental engineering.

Product Details

ISBN-13:	9780792367567
Publisher:	Springer US
Publication date:	12/31/2000
Series:	Nonconvex Optimization and Its Applications , #48
Edition description:	2nd ed. 2001
Pages:	354
Product dimensions:	6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

Preface to the Second Edition. Preface to the First Edition. 1. Fundamental results. 2. Quadratic Programming. 3. General Concave Minimization. 4. D.C. Programming. 5. Lipschitz Optimization. 6. Global Optimization on Networks. 7. Decomposition Algorithms. Solutions. Selected References. Index.

Editorial Reviews

A textbook for an undergraduate course in mathematical programming for students with a knowledge of elementary real analysis, linear algebra, and classical linear programming (simple techniques). Focuses on the computation and characterization of global optima of nonlinear functions, rather than the locally optimal solutions addressed by most books on optimization. Incorporates the theoretical, algorithmic, and computational advances of the past three decades that help solve globally multi-extreme problems in the mathematical modeling of real world systems. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Booknews

‘Each chapter contains illustrative examples and exercises. This excellent book is the first textbook on deterministic global optimization.'
Mathematical Reviews, 96g:90001
‘The authors provide a nice selection of homework exercises (with solutions) at an appropriate level and a good mixture of theory, application, and numerical problems throughout the text. The text would be perfect for a course on global optimization.'
Interfaces, 28 (1998)
‘Overall, this book provides an excellent introduction to the fascinating field of global optimization. The authors have used their extensive knowledge of and perspective on the field to create a coherent text that is accessible to a large audience that includes both students of mathematical programming and scientists who utilize optimization in their work.'
Journal of Global Optimization, 9 (1996)

From the Publisher