• DocumentCode
    356951
  • Title

    A new fitness function for discovering a lot of satisfiable solutions in constraint satisfaction problems

  • Author

    Handa, Hisashi ; Katai, Osamu ; Konishi, Tadataka ; Baba, Mitsuru

  • Author_Institution
    Dept. of Inf. Technol., Okayama Univ., Japan
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1184
  • Abstract
    In this paper, we discuss how many satisfiable solutions a genetic algorithm can find in a problem instance of a constraint satisfaction problems in a single execution. Hence, we propose a framework for a new fitness function which can be applied to traditional fitness functions. However, the mechanism of the proposed fitness function is quite simple, and several experimental results on a variety of instances of general constraint satisfaction problems demonstrate the effectiveness of the proposed fitness function
  • Keywords
    constraint theory; functions; genetic algorithms; operations research; constraint satisfaction problems; fitness function; genetic algorithm; problem instances; satisfiable solutions discovery; Artificial intelligence; Books; Computer simulation; Genetic algorithms; Genetic engineering; Informatics; Information technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
  • Conference_Location
    La Jolla, CA
  • Print_ISBN
    0-7803-6375-2
  • Type

    conf

  • DOI
    10.1109/CEC.2000.870783
  • Filename
    870783