Stochastic Global Optimization
This book presents the main methodological and theoretical developments in stochastic global optimization. The extensive text is divided into four chapters; the topics include the basic principles and methods of global random search, statistical inference
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Springer Optimization and Its Applications VOLUME 1 Managing Editor Panos M. Pardalos (University of Florida) Editor—Combinatorial Optimization Ding-Zhu Du (University of Texas at Dallas) Advisory Board J. Birge (University of Chicago) C.A. Floudas (Princeton University) F. Giannessi (University of Pisa) H.D. Sherali (Virginia Polytechnic and State University) T. Terlaky (McMaster University) Y. Ye (Stanford University)
Aims and Scope Optimization has been expanding in all directions at an astonishing rate during the last few decades. New algorithmic and theoretical techniques have been developed, the diffusion into other disciplines has proceeded at a rapid pace, and our knowledge of all aspects of the field has grown even more profound. At the same time, one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in all areas of applied mathematics, engineering, medicine, economics and other sciences. The series Springer Optimization and Its Applications publishes undergraduate and graduate textbooks, monographs and state-of-the-art expository works that focus on algorithms for solving optimization problems and also study applications involving such problems. Some of the topics covered include nonlinear optimization (convex and nonconvex), network flow problems, stochastic optimization, optimal control, discrete optimization, multi-objective programming, description of software packages, approximation techniques and heuristic approaches.
STOCHASTIC GLOBAL OPTIMIZATION
By Anatoly Zhigljavsky School of Mathematics Cardiff University, UK Antanas Žilinskas Institute of Mathematics and Informatics Vilnius, Lithuania
Anatoly Zhigljavsky School of Mathematics Cardiff University, UK
Antanas Žilinskas Institute of Mathematics and Informatics Vilnius, Lithuania
Library of Congress Control Number: 2007933821 ISBN-13: 978-0-387-74022-5
e-ISBN: 978-0-387-74740-8
© 2008 Springer Science+Business Media, LLC All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed in the United States of America. Printed on acid-free paper. 987654321 springer.com
Preface
This book aims to cover major methodological and theoretical developments in the field of stochastic global optimization. This field includes global random search and methods based on probabil
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