• DocumentCode
    3200158
  • Title

    Fuzzy logic controlled genetic algorithms

  • Author

    Wang, P.Y. ; Wang, G.S. ; Song, Y.H. ; Johns, A.T.

  • Author_Institution
    Electr. Power Res. Inst., Beijing, China
  • Volume
    2
  • fYear
    1996
  • fDate
    8-11 Sep 1996
  • Firstpage
    972
  • Abstract
    The fuzzy logic controlled genetic algorithm (FCGA) is presented, in which two fuzzy logic controllers are implemented to adaptively adjust the crossover rate and mutation rate during the optimization process. The FCGA is implemented in TC++ on a PC486 and tested by a power economic dispatch problem. The comparison between the FCGA and the conventional genetic algorithm (CGAs) is performed, which demonstrates that the FCGA has much better performance
  • Keywords
    controllers; fuzzy control; fuzzy logic; genetic algorithms; PC486; TC++; conventional genetic algorithm; crossover rate; fuzzy logic controlled genetic algorithms; fuzzy logic controllers; mutation rate; optimization process; power economic dispatch problem; Automatic control; Biological cells; Constraint optimization; Cost function; Decoding; Equations; Fuzzy logic; Genetic algorithms; Genetic mutations; Random number generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    0-7803-3645-3
  • Type

    conf

  • DOI
    10.1109/FUZZY.1996.552310
  • Filename
    552310