• DocumentCode
    1634913
  • Title

    Convergence of evolutionary algorithms in general search spaces

  • Author

    Rudolph, Günter

  • Author_Institution
    Informatik Centrum Dortmund, Germany
  • fYear
    1996
  • Firstpage
    50
  • Lastpage
    54
  • Abstract
    This paper provides conditions under which evolutionary algorithms with an elitist selection rule will converge to the global optimum of some function whose domain may be an arbitrary space. These results generalize the previously developed convergence theory for binary and Euclidean search spaces to general search spaces
  • Keywords
    Markov processes; convergence; genetic algorithms; probability; search problems; Euclidean search spaces; Markov model; arbitrary space; binary search; convergence theory; elitist selection rule; evolutionary algorithm convergence; function; general search spaces; global optimum; Algorithm design and analysis; Convergence; Design optimization; Evolution (biology); Evolutionary computation; Extraterrestrial measurements; Particle measurements; Random variables; State-space methods; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
  • Conference_Location
    Nagoya
  • Print_ISBN
    0-7803-2902-3
  • Type

    conf

  • DOI
    10.1109/ICEC.1996.542332
  • Filename
    542332
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1634913