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Hierarchical Genetic Algorithms

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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

Current Genetic Algorithms can efficiently address order-k separable problems, in which the order of the linkage is restricted to a low value k. Outside this class, there exist hierarchical problems that cannot be addressed by current genetic algorithms, yet can be addressed efficiently in principle by exploiting hierarchy. We delineate the class of hierarchical problems, and describe a framework for Hierarchical Genetic Algorithms. Based on this outline for algorithms, we investigate under what conditions hierarchical problems may be solved efficiently. Sufficient conditions are provided under which hierarchical problems can be addressed in polynomial time. The analysis points to the importance of efficient sampling techniques that assess the quality of module settings.

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Author information

Authors and Affiliations

  1. Decision Support Systems Group, Universiteit Utrecht, The Netherlands

    Edwin D. de Jong & Dirk Thierens

  2. Dept. of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA

    Richard A. Watson

Authors
  1. Edwin D. de Jong
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  2. Dirk Thierens
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  3. Richard A. Watson
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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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de Jong, E.D., Thierens, D., Watson, R.A. (2004). Hierarchical Genetic Algorithms. 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_24

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  • DOI: https://doi.org/10.1007/978-3-540-30217-9_24

  • 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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