• DocumentCode
    445566
  • Title

    Adaptive random search with intensification and diversification combined with genetic algorithm

  • Author

    Sohn, Dongkyu ; Hirasawa, Kotaro ; Hu, Jinglu

  • Author_Institution
    Graduate Sch. of Inf., Production & Syst., Waseda Univ., Fukuoka, Japan
  • Volume
    2
  • fYear
    2005
  • fDate
    2-5 Sept. 2005
  • Firstpage
    1462
  • Abstract
    A novel optimization method named RasID-GA (an abbreviation of adaptive random search with intensification and diversification combined with genetic algorithm) is proposed in order to enhance the searching ability of conventional RasID, which is a kind of random search with intensification and diversification. RasID-GA is compared with conventional RasID and GA using 23 different objective functions, and it turns out that RasID-GA performs well compared with other methods.
  • Keywords
    genetic algorithms; search problems; RasID-GA; adaptive random search; diversification; genetic algorithm; intensification; objective functions; optimization method; Evolutionary computation; Genetic algorithms; Genetic mutations; Mathematics; Optimization methods; Probability density function; Production systems; Search methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2005. The 2005 IEEE Congress on
  • Print_ISBN
    0-7803-9363-5
  • Type

    conf

  • DOI
    10.1109/CEC.2005.1554862
  • Filename
    1554862