Designing Evolutionary Algorithms for Dynamic Environments
The robust capability of evolutionary algorithms (EAs) to find solutions to difficult problems has permitted them to become popular as optimization and search techniques for many industries. Despite the success of EAs, the resultant solutions are often fr
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Advisory Board: S. Amari G. Brassard K.A. De Jong e.C.A.M. Gielen T. Head 1. Kari 1. Landweber T. Martinetz Z. Michalewicz M.e. Mozer E. Oja G. Paun J. Reif H. Rubin A. Salomaa M. Schoenauer H.-P. Schwefel C. Torras D. Whitley E. Winfree J.M. Zurada
Springer-Verlag Berlin Heidelberg GmbH
Ronald W. Morrison
Designing Evolutionary Algorithllls for Dynalllic Environlllents With 78 Figures
,
Springer
Author
Ronald W. Morrison Mitretek Systems 3150 Fairview Park Drive South Falls Church, Virginia 22042, USA
[email protected]
Series Editors
G. Rozenberg (Managing Editor) [email protected] Th. Blick, J. N. Kok, H. P. Spaink Leiden Center for Natural Computing, Leiden University Niels Bohrweg 1, 2333 CA Leiden, The Netherlands A.E.Eiben Vrije Universiteit Amsterdam, The Netherlands
Library of Congress Control Number: 2004102479 ACM Computing Classification (1998): I.2.8, F.3 ISBN 978-3-642-05952-0 ISBN 978-3-662-06560-0 (eBook) DOI 10.1007/978-3-662-06560-0 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-Verlag. Violations are liable to prosecution under the German Copyright Law. © Springer-Verlag Berlin Heidelberg 2004 Originally published by Springer-Verlag Berlin Heidelberg New York in 2004. Softcover reprint of the hardcover 15t edition 2004
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: KiinkelLopka, Heidelberg Typesetting: Digital data supplied by author Printed on acid-free paper 45/3142GF - 5432 1 0
To Peggy, Kimberly, and Erica
Preface
The robust capability of evolutionary algorithms (EAs) to find solutions to difficult problems has permitted them to become popular as optimization and search techniques for many industries. Despite the success of EAs, the resultant solutions are often fragile and prone to failure when the problem changes, usually requiring human intervention to keep the EA on track. Since many optimization problems in engineering, finance, and information technology require systems that can adapt to changes over time, it is desirable that EAs be able to respond to changes in the environment on their own. This book provides an analysis of what an EA needs to do to automatically and continuously solve dynamic problems, focusing on detecting changes in the problem environment and responding to those changes. In this book we identify and quantify a key attribute needed to improve the
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