• DocumentCode
    3001715
  • Title

    A Taguchi method-based crossover operator for the parametrical problems

  • Author

    Chan, K.Y. ; Aydin, M.E. ; Fogarty, T.C.

  • Author_Institution
    Fac. of Bus., Comput. & Inf. Manage., South Bank Univ., London, UK
  • Volume
    2
  • fYear
    2003
  • fDate
    8-12 Dec. 2003
  • Firstpage
    971
  • Abstract
    Based on our observation, some major steps in the genetic algorithm, such as the crossover operator, can be considered as experiments. The aim is to apply experimental design techniques to improve the crossover operator, so that the resulting operator can be more robust and statistically sound. Taguchi method is a systematic and time-efficient approach that can aid in experimental design. Here we apply Taguchi method to tailor a new crossover operator so that the operator can estimate the best point in the search space determined by the parents. Experimental result shows that the proposed operator outperforms the classical GA crossover strategy on some parametrical problems.
  • Keywords
    Taguchi methods; design of experiments; genetic algorithms; search problems; Taguchi method-based crossover operator; experimental design; genetic algorithm; parametrical problem; search space determination; Biological cells; Cost function; Design engineering; Design for experiments; Design optimization; Genetic algorithms; Information management; Robustness; Sampling methods; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
  • Print_ISBN
    0-7803-7804-0
  • Type

    conf

  • DOI
    10.1109/CEC.2003.1299772
  • Filename
    1299772