Introduction to Global Optimization

Horst, Reiner; Pardalos, Panos M.; Van-Thoai, Nguyen

ISBN 10: 0792367561 / ISBN 13: 9780792367567

Edité par Kluwer Academic Publishers, 2000

Covers the fundamentals in global optimization. This edition includes algorithms, applications, and complexity results for quadratic programming, concave minimization, DC and Lipshitz problems, decomposition algorithms for nonconvex optimization, and nonlinear network flow problems. Each chapter contains illustrative examples. Series: Nonconvex Optimization and Its Applications. Num Pages: 368 pages, biography. BIC Classification: PBU; PBW; UM. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 19. Weight in Grams: 1150. . 2000. 2 Rev ed. Paperback. . . . . N° de réf. du vendeur V9780792367567

Synopsis :

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, algorith- mic, and computational contributions have helped to solve globally multi- extreme problems arising from important practical applications.

Détails bibliographiques

Titre : Introduction to Global Optimization
Éditeur : Kluwer Academic Publishers
Date d'édition : 2000
Reliure : Couverture souple
Etat : New
Edition : 2ème Édition