Introduction to Global Optimization / Edition 2

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

Overview

In this edition, the scope and character of the monograph did not change with respect to the first edition. Taking into account the rapid development of the field, we have, however, considerably enlarged its contents. Chapter 4 includes two additional sections 4.4 and 4.6 on theory and algorithms of D.C. Programming. Chapter 7, on Decomposition Algorithms in Nonconvex Optimization, is completely new. Besides this, we added several exercises and corrected errors and misprints in the first edition. We are grateful for valuable suggestions and comments that we received from several colleagues. R. Horst, P.M. Pardalos and N.V. Thoai March 2000 Preface to the First Edition Many recent advances in science, economics and engineering rely on nu­ merical techniques for computing globally optimal solutions to corresponding optimization problems. Global optimization problems are extraordinarily di­ verse and they include economic modeling, fixed charges, finance, networks and transportation, databases and chip design, image processing, nuclear and mechanical design, chemical engineering design and control, molecular biology, and environment al engineering. Due to the existence of multiple local optima that differ from the global solution all these problems cannot be solved by classical nonlinear programming techniques. During the past three decades, however, many new theoretical, algorithmic, and computational contributions have helped to solve globally multi­ extreme problems arising from important practical applications.

Product Details

ISBN-13:	9780792365747
Publisher:	Springer US
Publication date:	10/31/2000
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

Comments on the first edition:
‘Each chapter contains illlustrative 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