Finding maximum cliques with distributed ants

Thang N. Bui, Joseph R. Rizzo

Research output: Chapter in Book/Report/Conference proceedingChapter

12 Scopus citations

Abstract

In this paper we describe an ant system algorithm (ASMC) for the problem of finding the maximum clique in a given graph. In the algorithm each ant has only local knowledge of the graph. Working together the ants induce a candidate set of vertices from which a clique can be constructed. The algorithm was designed so that it can be easily implemented in a distributed system. One such implementation is also described in the paper. For 22 of the 30 graphs tested ASMC found the optimal solution. For the remaining graphs ASMC produced solutions that are within 16% of the optimal, with most being within 8% of the optimal. The performance of ASMC is comparable to existing algorithms.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsKalyanmoy Deb, Riccardo Poli, Owen Holland, Kalyanmoy Banzhaf, Hans-Georg Beyer, Edmund Burke, Paul Darwen, Dipankar Dasgupta, Dario Floreano, James Foster, Mark Harman, Pier Luca Lanzi, Lee Spector, Andrea G. B. Tettamanzi, Dirk Thierens, Andrew M. Tyrrell
PublisherSpringer Verlag
Pages24-35
Number of pages12
ISBN (Print)3540223444, 9783540223443
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3102
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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