• DocumentCode
    3593254
  • Title

    Selection Strategies of Evolutionary Algorithms in Multiobjective Optimization

  • Author

    Xie, C.W. ; Ding, L.X.

  • Author_Institution
    State Key Lab. of Software Eng., Wuhan Univ., Wuhan, China
  • Volume
    4
  • fYear
    2009
  • Firstpage
    633
  • Lastpage
    637
  • Abstract
    The study on selection strategies of evolutionary algorithms in multiobjective optimization (MOEAs) is scarce.This paper mostly researches on various selection strategies of MOEAs. Firstly, the paper discusses how to construct an appropriate fitness function in multiobjective optimization problem, then, selection strategies are classified as six categories through systematically analyzing various MOEAs. To each selection strategy, we not only analyze its operation mechanism but also point out its advantages, weaknesses and applications. Although our study is not profound, it will be helpful to design more efficient MOEAs.
  • Keywords
    evolutionary computation; evolutionary algorithms; multiobjective optimization; selection strategies; Algorithm design and analysis; Evolutionary computation; Laboratories; Software engineering; Sorting; Evolutionary Algorithm; Multiobjective Optimization; Selection Strategy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.35
  • Filename
    5363435