• DocumentCode
    1449442
  • Title

    Fitness sharing and niching methods revisited

  • Author

    Sareni, Bruno ; Krähenbühl, Laurent

  • Author_Institution
    CEGELY, UPRESA CNRS, Ecully, France
  • Volume
    2
  • Issue
    3
  • fYear
    1998
  • fDate
    9/1/1998 12:00:00 AM
  • Firstpage
    97
  • Lastpage
    106
  • Abstract
    Interest in multimodal optimization function is expanding rapidly since real-world optimization problems often require the location of multiple optima in the search space. In this context, fitness sharing has been used widely to maintain population diversity and permit the investigation of manly peaks in the feasible domain. This paper reviews various strategies of sharing and proposes new recombination schemes to improve its efficiency. Some empirical results are presented for high and a limited number of fitness function evaluations. Finally, the study compares the sharing method with other niching techniques
  • Keywords
    genetic algorithms; evolutionary computation; fitness sharing; genetic algorithms; multimodal optimization; niching methods; Animals; Ecosystems; Evolutionary computation; Genetic algorithms; Optimization methods; Shape; Standards development; Testing;
  • fLanguage
    English
  • Journal_Title
    Evolutionary Computation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1089-778X
  • Type

    jour

  • DOI
    10.1109/4235.735432
  • Filename
    735432