Simple Surrogate Model Assisted Optimization with Covariance Matrix Adaptation
We aim to observe differences between surrogate model assisted covariance matrix adaptation evolution strategies applied to simple test problems. We propose a simple Gaussian process assisted strategy as a baseline. The performance of the algorithm is com
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Thomas Bäck · Mike Preuss · André Deutz · Hao Wang · Carola Doerr · Michael Emmerich · Heike Trautmann (Eds.)
Parallel Problem Solving from Nature – PPSN XVI 16th International Conference, PPSN 2020 Leiden, The Netherlands, September 5–9, 2020 Proceedings, Part I
Lecture Notes in Computer Science Founding Editors Gerhard Goos Karlsruhe Institute of Technology, Karlsruhe, Germany Juris Hartmanis Cornell University, Ithaca, NY, USA
Editorial Board Members Elisa Bertino Purdue University, West Lafayette, IN, USA Wen Gao Peking University, Beijing, China Bernhard Steffen TU Dortmund University, Dortmund, Germany Gerhard Woeginger RWTH Aachen, Aachen, Germany Moti Yung Columbia University, New York, NY, USA
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More information about this series at http://www.springer.com/series/7407
Thomas Bäck Mike Preuss André Deutz Hao Wang Carola Doerr Michael Emmerich Heike Trautmann (Eds.) •
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Parallel Problem Solving from Nature – PPSN XVI 16th International Conference, PPSN 2020 Leiden, The Netherlands, September 5–9, 2020 Proceedings, Part I
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Editors Thomas Bäck Leiden University Leiden, The Netherlands
Mike Preuss Leiden University Leiden, The Netherlands
André Deutz Leiden University Leiden, The Netherlands
Hao Wang Sorbonne University Paris, France
Carola Doerr Sorbonne University Paris, France
Michael Emmerich Leiden University Leiden, The Netherlands
Heike Trautmann University of Münster Münster, Germany
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-58111-4 ISBN 978-3-030-58112-1 (eBook) https://doi.org/10.1007/978-3-030-58112-1 LNCS Sublibrary: SL1 – Theoretical Computer Science and General Issues © Springer Nature Switzerland AG 2020 Chapters 22, 30, 31, 35 and 40 are licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). For further details see licence information in the chapters. 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, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have be
