• DocumentCode
    2373983
  • Title

    Implementation of PGAs in conjunction with fuzzy algorithm

  • Author

    Key Lou Kwon ; Alouani, A.T.

  • Author_Institution
    School of Information & Communication, Engineering Sungkyunkwan University, Suwon, Korea
  • fYear
    2004
  • fDate
    16-18 Dec. 2004
  • Firstpage
    463
  • Lastpage
    468
  • Abstract
    Genetic algorithms(GA), which are based on the idea of natural selection and survival of the fittest, have proven successful in solving complex problems that are not easily solved through conventional methods. Parallel genetic algorithm(PGA) is an extension of the classical GA. The important aspect in PGA is migration and GA operation. This paper presents PGAs that use fuzzy algorithm and natural select concept to migration of subpopulations. Fuzzy algorithm is used to change GA operators. Experimental results show that the proposed methods exhibit good performance compared to the classical method.
  • Keywords
    Biological cells; Computational efficiency; Convergence; Electronics packaging; Genetic algorithms; NP-complete problem; Optimization methods; Parallel processing; Genetic algorithm; fuzzy algorithm; migration; parallel genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications, 2004. Proceedings. 2004 International Conference on
  • Conference_Location
    Louisville, Kentucky, USA
  • Print_ISBN
    0-7803-8823-2
  • Type

    conf

  • DOI
    10.1109/ICMLA.2004.1383551
  • Filename
    1383551