An Introduction to Metaheuristics for Optimization
The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in
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Bastien Chopard · Marco Tomassini
An Introduction to Metaheuristics for Optimization
Natural Computing Series Series Editors: G. Rozenberg Th. Bäck A.E. Eiben J.N. Kok H.P. Spaink Leiden Center for Natural Computing
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. Paun J. Reif H. Rubin A. Salomaa M. Schoenauer ˘ H.-P. Schwefel C. Torras D. Whitley E. Winfree J.M. Zurada
More information about this series at http://www.springer.com/series/4190
Bastien Chopard • Marco Tomassini
An Introduction to Metaheuristics for Optimization
Bastien Chopard Département d’informatique Université de Genève Carouge, Switzerland
Marco Tomassini Faculté des hautes études commerciales (HEC) Université de Lausanne Lausanne, Switzerland
ISSN 1619-7127 Natural Computing Series ISBN 978-3-319-93072-5 ISBN 978-3-319-93073-2 (eBook) https://doi.org/10.1007/978-3-319-93073-2 Library of Congress Control Number: 2018959278 © Springer Nature Switzerland AG 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
We would like to express our gratitude to our wives, Joanna and Anne, for their encouragement and patience during the writing of the book.
Preface
Heuristic methods are used when rigorous ones are either unknown or cannot be applied, typically because they would be too slow. A metaheuristic is a general optimization framework that is used to control an underlying problem-specific heuristic such that the method can be easily applied to different problems. In the last two decades metaheuristics have been successful for solving, or at least for obtaining satisfactory results in, the optimization of many difficult p
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