Foraging-Inspired Optimisation Algorithms
This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foragin
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Anthony Brabazon Seán McGarraghy
ForagingInspired Optimisation Algorithms
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
Anthony Brabazon • Seán McGarraghy
Foraging-Inspired Optimisation Algorithms
Anthony Brabazon School of Business University College Dublin Dublin, Ireland
Seán McGarraghy UCD Centre for Business Analytics University College Dublin Dublin, Ireland
ISSN 1619-7127 Natural Computing Series ISBN 978-3-319-59155-1 ISBN 978-3-319-59156-8 (eBook) https://doi.org/10.1007/978-3-319-59156-8 Library of Congress Control Number: 2018957425 © 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
To Maria, my mother Rose, and to the memory of my father Kevin Tony
To Milena, Martin and Alex Se´an
Preface
In recent times there has been growing interest in biomimicry, or ‘learning from nature’, with many disciplines turning to natural phenomena for inspiration as to how to solve particular problems in their field. Examples include the development of pharmaceutical products based on substances found in plants, and inspiration for engineering designs based on structures and materials found in nature. Another strand of ‘learning from nature’ concerns the development of powerful computational algorithms whose design is inspired by natural processes
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