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A Genetic Algorithm for the Maximal Clique Problem

  • Cristina Bazgan
  • Henri Luchian
Conference paper

Abstract

The maximal clique problem (MaxClique) is known to be difficult (in terms of complexity) both in its exact and in the approximate form. Therefore, probabilistic algorithms for this problem are worthwhile to study. In this paper, we present an evolutionary (genetic) approach to solving the maximal clique problem (we are not directly concerned here with complexity). As opposed to previous work, our solution is inspired by a theoretical result [1] which improves the genetic algorithm. Experimental results for graphs with various properties are given; the convergence towards a good solution (in almost all of the runs, the global optimum) turns out to be quick.

Keywords

Genetic Algorithm Approximation Algorithm Fitness Function Maximal Clique Probabilistic Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag/Wien 1995

Authors and Affiliations

  • Cristina Bazgan
    • 1
  • Henri Luchian
    • 1
  1. 1.Faculty of Computer Science“Al.I.Cuza” University of IasiRomania

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