• DocumentCode
    2911395
  • Title

    Convergent analysis on evolutionary algorithm with non-uniform mutation

  • Author

    Zhao, Xinchao

  • Author_Institution
    Sch. of Sci., Beijing Univ. of Posts & Telecommun., Beijing
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    940
  • Lastpage
    944
  • Abstract
    Evolutionary algorithm (EA) with non-uniform mutation has the merits of even ldquolonger jumpsrdquo than Cauchy mutation at the early stage of the algorithm and much ldquofiner-tuningsrdquo than Gaussian mutation operator at the later stage. Empirical comparisons with the recently proposed EAs show its excellence solution quality and reliability. One unified algorithmic framework with non-uniform mutation operator and its convergence analysis based on this algorithmic framework are provided in this paper. Two lemmas and two theorems are presented to show the relevant convergence properties of unimodal and multimodal functions.
  • Keywords
    convergence; evolutionary computation; convergence analysis; evolutionary algorithm; nonuniform mutation operator; Algorithm design and analysis; Biological information theory; Encoding; Evolution (biology); Evolutionary computation; Genetic algorithms; Genetic mutations; Genetic programming; Probability distribution; Stochastic processes; evolutionary algorithm; non-uniform mutation; stochastic process; theoretical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4630909
  • Filename
    4630909