• DocumentCode
    1870101
  • Title

    An empirical comparison of simulated annealing and genetic algorithms on NK fitness landscapes

  • Author

    Park, Lae-Jeong ; Nam, Dong-Kyung ; Park, Cheol Hoon ; Oh, San-Hoon

  • Author_Institution
    Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea
  • fYear
    1997
  • fDate
    13-16 Apr 1997
  • Firstpage
    147
  • Lastpage
    151
  • Abstract
    The paper presents the features of GAs as static optimization techniques through an empirical comparison with SA on the NK fitness landscape model. This is done with consideration of the problem size and the ruggedness. Experimental results show that the genetic search is not comparable to simulated annealing on the NK fitness landscapes. Furthermore, the performance gap gets larger as the problem size increases and the landscape becomes rugged
  • Keywords
    genetic algorithms; search problems; simulated annealing; NK fitness landscape model; empirical comparison; genetic algorithms; genetic search; performance gap; problem size; simulated annealing; static optimization techniques; Analytical models; Cities and towns; Controllability; Genetic algorithms; Optimization methods; Performance analysis; Simulated annealing; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1997., IEEE International Conference on
  • Conference_Location
    Indianapolis, IN
  • Print_ISBN
    0-7803-3949-5
  • Type

    conf

  • DOI
    10.1109/ICEC.1997.592286
  • Filename
    592286