• DocumentCode
    175862
  • Title

    A fast genetic algorithm for solving the maximum clique problem

  • Author

    Suqi Zhang ; Jing Wang ; Qing Wu ; Jin Zhan

  • Author_Institution
    Sch. of Inf. Eng., Tianjin Univ. of Commerce, Tianjin, China
  • fYear
    2014
  • fDate
    19-21 Aug. 2014
  • Firstpage
    764
  • Lastpage
    768
  • Abstract
    Aiming at the defects of Genetic Algorithm (GA) for solving the Maximum Clique Problem (MCP) in more complicated, long-running and poor generality, a fast genetic algorithm (FGA) is proposed in this paper. A new chromosome repair method on the degree, elitist selection based on random repairing, uniform crossover and inversion mutation are adopted in the new algorithm. These components can speed up the search and effectively prevent the algorithm from trapping into the local optimum. The algorithm was tested on DIMACS benchmark graphs. Experimental results show that FGA has better performance and high generality.
  • Keywords
    combinatorial mathematics; genetic algorithms; DIMACS benchmark graphs; FGA; MCP; chromosome repair method; combination optimal problem; elitist selection; fast genetic algorithm; inversion mutation; local optimum; maximum clique problem; random repairing; uniform crossover; Benchmark testing; Biological cells; Educational institutions; Genetic algorithms; Maintenance engineering; Sociology; Statistics; chromosome repair; elitist selection; genetic algorithm; inversion mutation; the maximum clique; uniform crossover;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2014 10th International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4799-5150-5
  • Type

    conf

  • DOI
    10.1109/ICNC.2014.6975933
  • Filename
    6975933