• DocumentCode
    2326038
  • Title

    Modal mutations in evolutionary algorithms

  • Author

    Voigt, Hans-Michael ; Anheyer, Thomas

  • Author_Institution
    Bionics & Evolution Techniques Lab., Tech. Univ. Berlin, Germany
  • fYear
    1994
  • fDate
    27-29 Jun 1994
  • Firstpage
    88
  • Abstract
    With this paper modal mutation schemes for evolutionary algorithms as a generalization of the breeder genetic algorithm mutation scheme are introduced and analyzed for multimodal continuous parameter optimization problems. A new scaling rule for multiple mutations is formalized and compared with a new step-size scaling for evolution strategies. A performance comparison of the multivalued evolutionary algorithm with modal mutations with recently published results concerning the performance of Bayesian/sampling and very fast simulated reannealing techniques for global optimization is given
  • Keywords
    Bayes methods; genetic algorithms; optimisation; simulated annealing; evolution strategies; evolutionary algorithms; global optimization; modal mutation schemes; multimodal continuous parameter optimization; multiple mutations; multivalued evolutionary algorithm; performance comparison; scaling rule; simulated annealing; simulated reannealing; Algorithm design and analysis; Bayesian methods; Educational institutions; Evolutionary computation; Genetic algorithms; Genetic mutations; Robustness; Sampling methods; Technology management; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1899-4
  • Type

    conf

  • DOI
    10.1109/ICEC.1994.350036
  • Filename
    350036