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Genetic, Iterated and Multistart Local Search for the Maximum Clique Problem

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Applications of Evolutionary Computing (EvoWorkshops 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2279))

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Abstract

This paper compares experimentally three heuristic algorithms for the maximum clique problem obtained as instances of an evolutionary algorithm scheme. The algorithms use three popular heuristic methods for combinatorial optimization problems, known as genetic, iterated and multistart local search, respectively.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Free University Amsterdam, De Boelelaan 1081a, 1081, HV Amsterdam, The Netherlands

    Elena Marchiori

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  1. Elena Marchiori
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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

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© 2002 Springer-Verlag Berlin Heidelberg

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Marchiori, E. (2002). Genetic, Iterated and Multistart Local Search for the Maximum Clique Problem. In: Cagnoni, S., Gottlieb, J., Hart, E., Middendorf, M., Raidl, G.R. (eds) Applications of Evolutionary Computing. EvoWorkshops 2002. Lecture Notes in Computer Science, vol 2279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46004-7_12

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  • DOI: https://doi.org/10.1007/3-540-46004-7_12

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43432-0

  • Online ISBN: 978-3-540-46004-6

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