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Searching for Maximum Cliques with Ant Colony Optimization

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Applications of Evolutionary Computing (EvoWorkshops 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2611))

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Abstract

In this paper, we investigate the capabilities of Ant Colony Optimization (ACO) for solving the maximum clique problem. We describe Ant-Clique, an algorithm that successively generates maximal cliques through the repeated addition of vertices into partial cliques. ACO is used to choose, at each step, the vertex to add. We illustrate the behaviour of this algorithm on two representative benchmark instances and we study the impact of pheromone on the solution process. We also experimentally compare Ant-Clique with GLS, a Genetic Local Search approach, and we show that Ant-Clique finds larger cliques, on average, on a majority of DIMACS benchmark instances, even though it does not reach the best known results on some instances.

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References

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Author information

Authors and Affiliations

  1. LIRIS, Nautibus, University Lyon I, 43 Bd du 11 novembre, 69622, Villeurbanne cedex, France

    Serge Fenet & Christine Solnon

Authors
  1. Serge Fenet
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  2. Christine Solnon
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Editor information

Editors and Affiliations

  1. Dept. of Computer Engineering, University of Parma, Parco Area delle Scienze 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  2. Computing Laboratory, University of Kent, Canterbury, Kent, CT2 7NF, UK

    Colin G. Johnson

  3. Dept. of Information and Communications Technologies Faculty of Computer Science, University of A Coruña, A Coruña, CP 15071, Spain

    Juan J. Romero Cardalda

  4. Dept. of Mathematics and Computer Science, Free University of Amsterdam, de Boelelaan 1081a, 1081 HV, Amsterdam, The Netherlands

    Elena Marchiori

  5. Schol of Systems Engineering, University of Reading, PO Box 225, Whiteknights, Reading, RG6 6AY, UK

    David W. Corne

  6. AnimatLab, 8 rue du capitaine Scott, 75015, Paris, France

    Jean-Arcady Meyer  & Agnès Guillot  & 

  7. SAP AG, Neurottstrasse 16, 69190, Walldorf, Germany

    Jens Gottlieb

  8. Parallel Computing and Complex Systems Group, University of Leipzig, Augustusplatz 10/11, 04109, Leipzig, Germany

    Martin Middendorf

  9. Algorithms and Data Structures Group Institute of Computer Graphics, Vienna University of Technology, Favoritenstrasse 9-11/186, 1040, Vienna, Austria

    Günther R. Raidl

  10. School of Computing, Napier University, 219 Colinton Road, Edinburgh, EH14 1DJ, UK

    Emma Hart

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© 2003 Springer-Verlag Berlin Heidelberg

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Fenet, S., Solnon, C. (2003). Searching for Maximum Cliques with Ant Colony Optimization. In: Cagnoni, S., et al. Applications of Evolutionary Computing. EvoWorkshops 2003. Lecture Notes in Computer Science, vol 2611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36605-9_22

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  • DOI: https://doi.org/10.1007/3-540-36605-9_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00976-4

  • Online ISBN: 978-3-540-36605-8

  • eBook Packages: Springer Book Archive

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