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Adaptive penalties for evolutionary graph coloring

  • Genetic Operators
  • Conference paper
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Artificial Evolution (AE 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1363))

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Abstract

In this paper we consider a problem independent constraint handling mechanism, Stepwise Adaptation of Weights (SAW) and show its working on graph coloring problems. SAW-ing technically belongs to the penalty function based approaches and amounts to modifying the penalty function during the search. We show that it has a twofold benefit. First, it proves to be rather insensitive to its technical parameters, thereby providing a general, problem independent way to handle constrained problems. Second, it leads to superior EA performance. In an extensive series of comparative experiments we show that the SAW-ing EA outperforms a powerful graph coloring heuristic algorithm, DSatur, on the hardest graph instances and has a linear scale-up behaviour.

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Authors and Affiliations

  1. Leiden University, The Netherlands

    A. E. Eiben & J. K. van der Hauw

Authors
  1. A. E. Eiben
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  2. J. K. van der Hauw
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Editor information

Jin-Kao Hao Evelyne Lutton Edmund Ronald Marc Schoenauer Dominique Snyers

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© 1998 Springer-Verlag Berlin Heidelberg

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Eiben, A.E., van der Hauw, J.K. (1998). Adaptive penalties for evolutionary graph coloring. In: Hao, JK., Lutton, E., Ronald, E., Schoenauer, M., Snyers, D. (eds) Artificial Evolution. AE 1997. Lecture Notes in Computer Science, vol 1363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0026593

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  • DOI: https://doi.org/10.1007/BFb0026593

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64169-8

  • Online ISBN: 978-3-540-69698-8

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