Evolutionary Strategies
Evolutionary strategy (ES) paradigm is one of the most successful EAs. Evolutionary gradient search and gradient evolution are two methods that use EA to construct gradient information for directing the search efficiently. Covariance matrix adaptation (CM
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Search and Optimization by Metaheuristics Techniques and Algorithms Inspired by Nature
Ke-Lin Du M.N.S. Swamy •
Search and Optimization by Metaheuristics Techniques and Algorithms Inspired by Nature
M.N.S. Swamy Department of Electrical and Computer Engineering Concordia University Montreal, QC Canada
Ke-Lin Du Xonlink Inc Ningbo, Zhejiang China and
Department of Electrical and Computer Engineering Concordia University Montreal, QC Canada
ISBN 978-3-319-41191-0 DOI 10.1007/978-3-319-41192-7
ISBN 978-3-319-41192-7
(eBook)
Library of Congress Control Number: 2016943857 Mathematics Subject Classification (2010): 49-04, 68T20, 68W15 © Springer International Publishing Switzerland 2016 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. Printed on acid-free paper This book is published under the trade name Birkhäuser The registered company is Springer International Publishing AG Switzerland (www.birkhauser-science.com)
To My Friends Jiabin Lu and Biaobiao Zhang Ke-Lin Du and To My Parents M.N.S. Swamy
Preface
Optimization is a branch of applied mathematics and numerical analysis. Almost every problem in engineering, science, economics, and life can be formulated as an optimization or a search problem. While some of the problems can be simple that can be solved by traditional optimization methods based on mathematical analysis, most of the problems are very hard to be solved using analysis-based approaches. Fortunately, we can solve these hard optimization problems by inspirations from nature, since we know that nature is a system of vast complexity and it always generates a near-optimum solution. Natural computing is concerned with computing inspired by nature, as well as with computations taking place in nature. Well-known examples of natural computing are evolutionary computation, neural computation, cellular automata, swarm intelligence, molecular computing, quantum computation, artificial immune systems, and membrane computing. Together, they constitute the discipline
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