• DocumentCode
    2325083
  • Title

    Extended forking genetic algorithm for order representation (o-fGA)

  • Author

    Tsutsui, Shigeyoshi ; Fujimoto, Yoshiji ; Hayashi, Isao

  • Author_Institution
    Dept. of Manage. & Inf. Sci., Hannan Univ., Osaka, Japan
  • fYear
    1994
  • fDate
    27-29 Jun 1994
  • Firstpage
    639
  • Abstract
    There are two types of GAs with difference of their representation of strings. They are the binary coded GA and the order-based GA. We´ve already proposed a new type of binary coded GA, called the forking GA (fGA), as a kind of multi-population GA and showed that the searching power of the fGA is superior to the standard GA. The distinguished feature of the fGA is that each population takes a different role in optimization. That is, each population is responsible for searching in a non-overlapping sub-area of the search space. In this paper, the extended forking GA for order representation, called the o-fGA, is proposed. The results of experiments for the blind traveling salesperson problem (TSP) show that the approach of fGA is also effective for the order representation
  • Keywords
    combinatorial mathematics; genetic algorithms; optimisation; search problems; binary coded GA; blind traveling salesperson problem; extended forking genetic algorithm; forking genetic algorithm; order representation; order-based GA; searching power; Code standards; Convergence; Genetic algorithms; Informatics; Information management; Information science; Mathematics; Position measurement; Space exploration; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1899-4
  • Type

    conf

  • DOI
    10.1109/ICEC.1994.349984
  • Filename
    349984