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Workshops on Applications of Evolutionary Computation

EvoWorkshops 2001: Applications of Evolutionary Computing pp 120–129Cite as

An Evolutionary Annealing Approach to Graph Coloring

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2037))

Abstract

This paper presents a new heuristic algorithm for the graph coloring problem based on a combination of genetic algorithms and simulated annealing. Our algorithm exploits a novel crossover operator for graph coloring. Moreover, we investigate various ways in which simulated annealing can be used to enhance the performance of an evolutionary algorithm. Experiments performed on various collections of instances have justified the potential of this approach. We also discuss some possible enhancements and directions for further research.

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References

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Author information

Authors and Affiliations

  1. Computer Engineering & Informatics Department, University of Patras, 26500, Greece

    Dimitris A. Fotakis & Spiridon D. Likothanassis

  2. Department of Computer Science, ETH Zurich, CH, 8092, Zurich, Switzerland

    Stamatis K. Stefanakos

Authors
  1. Dimitris A. Fotakis
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  2. Spiridon D. Likothanassis
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  3. Stamatis K. Stefanakos
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Editor information

Editors and Affiliations

  1. Leiden University, Niels Bohrweg1, 2333, CA, Leiden, The Netherlands

    Egbert J. W. Boers

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© 2001 Springer-Verlag Berlin Heidelberg

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Fotakis, D.A., Likothanassis, S.D., Stefanakos, S.K. (2001). An Evolutionary Annealing Approach to Graph Coloring. In: Boers, E.J.W. (eds) Applications of Evolutionary Computing. EvoWorkshops 2001. Lecture Notes in Computer Science, vol 2037. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45365-2_13

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  • DOI: https://doi.org/10.1007/3-540-45365-2_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41920-4

  • Online ISBN: 978-3-540-45365-9

  • eBook Packages: Springer Book Archive

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