Theory of Evolutionary Computation Recent Developments in Discrete O
This edited book reports on recent developments in the theory of evolutionary computation, or more generally the domain of randomized search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of random
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Benjamin Doerr Frank Neumann Editors
Theory of Evolutionary Computation Recent Developments in Discrete Optimization
Natural Computing Series Series Editors: Thomas Bäck
Lila Kari
Natural Computing is one of the most exciting developments in computer science, and there is a growing consensus that it will become a major field in this century. This series includes monographs, textbooks, and state-of-the-art collections covering the whole spectrum of Natural Computing and ranging from theory to applications. More information about this series at http://www.springer.com/series/4190
Benjamin Doerr • Frank Neumann Editors
Theory of Evolutionary Computation Recent Developments in Discrete Optimization
Editors Benjamin Doerr Laboratoire d’Informatique (LIX) - UMR 7161 École Polytechnique Palaiseau, France
Frank Neumann School of Computer Science The University of Adelaide Adelaide, SA, Australia
ISSN 1619-7127 Natural Computing Series ISBN 978-3-030-29413-7 ISBN 978-3-030-29414-4 (eBook) https://doi.org/10.1007/978-3-030-29414-4 © Springer Nature Switzerland AG 2020 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
Preface
The theory of evolutionary computation, or, more generally, randomized search heuristics, is aimed at understanding how these methods work and why they are so successful in many applications. While there has always been theoretical work in this field, and even more since Ingo Wegener (1950– 2008) pushed for a mathematical approach inspired by the classical field of randomized algorithms, this research area remains young and many astonishing advances have only been made in the last five to ten years. These include new and more powerful methods, the solution of long-st
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