Fireworks Algorithm A Novel Swarm Intelligence Optimization Method
This book is devoted to the state-of-the-art in all aspects of fireworks algorithm (FWA), with particular emphasis on the efficient improved versions of FWA. It describes the most substantial theoretical analysis including basic principle and implementati
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Fireworks Algorithm A Novel Swarm Intelligence Optimization Method
Fireworks Algorithm
Ying Tan
Fireworks Algorithm A Novel Swarm Intelligence Optimization Method
123
Ying Tan Peking University Beijing China
ISBN 978-3-662-46352-9 DOI 10.1007/978-3-662-46353-6
ISBN 978-3-662-46353-6
(eBook)
Library of Congress Control Number: 2015947937 Springer Heidelberg New York Dordrecht London Parts of the edition are translations from the Chinese language edition: 烟花算法引论 by Ying Tan © Science Press 2015. All rights reserved © Springer-Verlag Berlin Heidelberg 2015 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 Springer-Verlag GmbH Berlin Heidelberg is part of Springer Science+Business Media (www.springer.com)
Dedicated to my wife Chao Deng and my daughter Fei Tan for their unconditional love and support!
Preface
The swarm intelligence optimization method is used to study bio- or non-bioinspired and population-based iterative algorithms for seeking the intrinsic cooperative mechanism in a swarm. It has recently attracted a great deal of attention from researchers from different fields and diverse domains. Many novel algorithms and their efficient improvements have been proposed continuously. The swarm intelligence optimization method is increasingly becoming one of the hottest and most important paradigms under the big umbrella of evolutionary computation (EC). Inspired by the fireworks explosion in the night sky, fireworks algorithm, abbreviated as FWA, was proposed by the author in 2010. FWA is a swarm intelligence optimization algorithm, which seems effective at finding a good enough solution to the global optimum of a complex optimization problem. In FWA, as a firework explodes, a shower of sparks is shown in the adjacent area. These sparks explode again and generate other showers of sparks in a smaller area. Gradually, the sparks search the whole solution space in a fine structure and focus on a small region to eventually find (a) good enough soluti
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