Advances in Metaheuristics for Hard Optimization
Many advances have been made recently in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu
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Advisory Board: S. Amari G. Brassard K.A. De Jong C.C.A.M. Gielen T. Head L. Kari L. Landweber T. Martinetz Z. Michalewicz M.C. Mozer E. Oja G. P˘aun J. Reif H. Rubin A. Salomaa M. Schoenauer H.-P. Schwefel C. Torras D. Whitley E. Winfree J.M. Zurada
Patrick Siarry · Zbigniew Michalewicz (Eds.)
Advances in Metaheuristics for Hard Optimization
With 167 Figures and 82 Tables
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Editors
Series Editors
Patrick Siarry University of Paris 12 Laboratory LiSSi 61 Avenue du Général de Gaulle 94010 Créteil, France [email protected]
G. Rozenberg (Managing Editor) [email protected] Th. Bäck, J.N. Kok, H.P. Spaink Leiden Center for Natural Computing Leiden University Niels Bohrweg 1 2333 CA Leiden, The Netherlands
Zbigniew Michalewicz School of Computer Science University of Adelaide Adelaide, SA 5005, Australia [email protected]
A.E. Eiben Vrije Universiteit Amsterdam The Netherlands
Library of Congress Control Number: 2007929485
ACM Computing Classification (1998): F.2, G.1, I.2, J.6 ISSN 1619-7127 ISBN 978-3-540-72959-4 Springer Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable for prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springer.com © Springer-Verlag Berlin Heidelberg 2008 The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover Design: KünkelLopka, Werbeagentur, Heidelberg Typesetting and Production: LE-TEX Jelonek, Schmidt & Vöckler GbR, Leipzig Printed on acid-free paper
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Preface
The community of researchers claiming the relevance of their work to the field of metaheuristics is growing faster and faster, despite the fact that the term itself has not been precisely defined. Numerous books have been published specializing in any one of the most widely known methods, namely, simulated annealing, tabu search, evolutionary algorithms, ant colony algorithms, particle swarm optimization, but attempts to bring metaheuristics closer together are scarce. Yet some common features clearly appear in most metaheuristics, such as the use of diversification to force the exploration of regions of the search space, rarely visited until now, and the use of intensification, to investigate thoroughly some promising regions. Another common feature is the use of memory to archive the best solutions encountered. One common short
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