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Behavior of Evolutionary Algorithms in Chaotically Changing Fitness Landscapes

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Parallel Problem Solving from Nature - PPSN VIII (PPSN 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3242))

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Abstract

We study an evolutionary algorithm used for optimizing in a chaotically changing dynamic environment. The corresponding chaotic non-stationary fitness landscape can be characterized by quantifiers of the underlying dynamics-generating system. We give experimental results about how these quantifiers, namely the Lyapunov exponents, together with the environmental change period of the landscape influence performance measures of the evolutionary algorithm used for tracking optima.

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Author information

Authors and Affiliations

  1. HTWK Leipzig, Fachbereich Elektrotechnik und Informationstechnik, Institut Mess-, Steuerungs- und Regelungstechnik, Postfach 30 11 66, D–04125, Leipzig, Germany

    Hendrik Richter

Authors
  1. Hendrik Richter
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Editor information

Editors and Affiliations

  1. University of Birmingham, Birmingham, UK

    Xin Yao

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

    Edmund K. Burke

  3. Intelligent Systems Group Department of Computer Science and Artificial Intelligence, University of the Basque Country, Paseo Manuel de Lardizábal 1, 20018, San Sebastian, Donostia, Spain

    José A. Lozano

  4. University of the West of England, Bristol, United Kingdom

    Jim Smith

  5. GeNeura Team, Depto. Arquitectura y Tecnología de Computadores, Universidad de Granada, Spain

    Juan Julián Merelo-Guervós

  6. School of Computer Science, The University of Birmingham, B15 1TT, Edgbaston, Birmingham, UK

    John A. Bullinaria

  7. School of Computer Science, University of Birmingham, B15 2TT, Birmingham, Great Britain

    Jonathan E. Rowe

  8. School of Computer Science, University of Birmingham, United Kingdom

    Peter Tiňo

  9. School of Computer Science, The University of Birmingham, B15 2TT, Birmingham, UK

    Ata Kabán

  10. Faculty of Computer Science, Dortmund University of Technology, 44221, Dortmund, Germany

    Hans-Paul Schwefel

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© 2004 Springer-Verlag Berlin Heidelberg

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Richter, H. (2004). Behavior of Evolutionary Algorithms in Chaotically Changing Fitness Landscapes. In: Yao, X., et al. Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. Lecture Notes in Computer Science, vol 3242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30217-9_12

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  • DOI: https://doi.org/10.1007/978-3-540-30217-9_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23092-2

  • Online ISBN: 978-3-540-30217-9

  • eBook Packages: Springer Book Archive

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