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Towards an Adaptive Multimeme Algorithm for Parameter Optimisation Suiting the Engineers’ Needs

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Parallel Problem Solving from Nature - PPSN IX (PPSN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4193))

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Abstract

Important factors for the easy usage of an Evolutionary Algorithm (EA) are numbers of fitness calculations as low as possible, its robustness, and the reduction of its strategy parameters as far as possible. Multimeme Algorithms (MMA) are good candidates for the first two properties. In this paper a cost-benefit-based approach shall be introduced for the adaptive control of both meme selection and the ratio between local and global search. The latter is achieved by adaptively adjusting the intensity of the search of the memes and the frequency of their usage. It will be shown in which way the proposed kind of adaptation fills the gap previous work leaves. Detailed experiments in the field of continuous parameter optimisation demonstrate the superiority of the adaptive MMA over the simple MA and the pure EA.

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Authors and Affiliations

  1. Institute for Applied Computer Science, Forschungszentrum Karlsruhe GmbH, P.O. Box 3640, 76021, Karlsruhe, Germany

    Wilfried Jakob

Authors
  1. Wilfried Jakob
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Editor information

Editors and Affiliations

  1. Science Institute, University of Iceland, P.O. Box, Iceland

    Thomas Philip Runarsson

  2. Vorarlberg University of Applied Sciences, Hochschulstr. 1, A-6850, Dornbirn, Austria

    Hans-Georg Beyer

  3. Automated Scheduling, Optimisation and Planning Group, School of Computer Science & IT, University of Nottingham, NG8 1BB, Nottingham, UK

    Edmund Burke

  4. Depto. Arquitectura y Tecnologa de Computadores, ETS Ingeiera Informtica, C/Daniel Saucedo Aranda, s/n, 18071, Granada, Spain

    Juan J. Merelo-Guervós

  5. Colorado State University, 80523, Fort Collins, CO, USA

    L. Darrell Whitley

  6. University of Birmingham, Birmingham, UK

    Xin Yao

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© 2006 Springer-Verlag Berlin Heidelberg

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Jakob, W. (2006). Towards an Adaptive Multimeme Algorithm for Parameter Optimisation Suiting the Engineers’ Needs. In: Runarsson, T.P., Beyer, HG., Burke, E., Merelo-Guervós, J.J., Whitley, L.D., Yao, X. (eds) Parallel Problem Solving from Nature - PPSN IX. PPSN 2006. Lecture Notes in Computer Science, vol 4193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11844297_14

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  • DOI: https://doi.org/10.1007/11844297_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38990-3

  • Online ISBN: 978-3-540-38991-0

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