• DocumentCode
    1635754
  • Title

    Ant colony optimization for FOP shop scheduling: a case study on different pheromone representations

  • Author

    Blum, Christian ; Sampels, Michael

  • Author_Institution
    IRIDIA, Univ. Libre de Bruxelles, Brussels, Belgium
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1558
  • Lastpage
    1563
  • Abstract
    In this work we deal with the FOP shop scheduling problem which is a general scheduling problem including job shop scheduling, open shop scheduling and mixed shop scheduling as special cases. The aim of this paper is to compare different pheromone representations taken from the literature with our new approach. The pheromone representations are used by an ant colony optimization algorithm to construct solutions to the FOP shop scheduling problem
  • Keywords
    combinatorial mathematics; genetic algorithms; scheduling; FOP shop scheduling; ant colony optimization; job shop scheduling; mixed shop scheduling; open shop scheduling; pheromone representations; Ant colony optimization; Computer aided software engineering; Humans; Job shop scheduling; NP-hard problem; Scheduling algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7282-4
  • Type

    conf

  • DOI
    10.1109/CEC.2002.1004474
  • Filename
    1004474