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Parallelizable evolutionary dynamics principles for solving the maximum clique problem

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Parallel Problem Solving from Nature — PPSN IV (PPSN 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1141))

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Abstract

An algorithm for approximately solving the maximum clique is presented which uses relaxation labeling neural network techniques, focusing on the continuous problem formulation: maximize a quadratic form over the standard simplex. We employ somewhat surprising connections of the latter problem with dynamic principles of evolutionary game theory, and give a detailed report on our numerical experiences with the method proposed.

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Author information

Authors and Affiliations

  1. Dipartimento di Matematica Applicata e Informatica, Università “Ca' Foscari” di Venezia, Via Torino 155, 30173, Venezia Mestre, Italy

    Marcello Pelillo

  2. Institut für Statistik, Operations Research und Computerverfahren, Universität Wien, UniversitätsstraΒe 5, A-1010, Wien, Austria

    Immanuel M. Bomze

Authors
  1. Marcello Pelillo
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  2. Immanuel M. Bomze
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Editor information

Hans-Michael Voigt Werner Ebeling Ingo Rechenberg Hans-Paul Schwefel

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© 1996 Springer-Verlag Berlin Heidelberg

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Pelillo, M., Bomze, I.M. (1996). Parallelizable evolutionary dynamics principles for solving the maximum clique problem. In: Voigt, HM., Ebeling, W., Rechenberg, I., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN IV. PPSN 1996. Lecture Notes in Computer Science, vol 1141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61723-X_1031

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  • DOI: https://doi.org/10.1007/3-540-61723-X_1031

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61723-5

  • Online ISBN: 978-3-540-70668-7

  • eBook Packages: Springer Book Archive

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