• DocumentCode
    577610
  • Title

    An ant colony algorithm for permutation flow shop problem

  • Author

    Shang, Ke ; Feng, Zuren ; Ke, Liangjun

  • Author_Institution
    State Key Lab. for Manuf. Syst. Eng., Xi´´an Jiaotong Univ., Xi´´an, China
  • fYear
    2012
  • fDate
    6-8 July 2012
  • Firstpage
    596
  • Lastpage
    600
  • Abstract
    In this paper, a new ant colony optimization algorithm, called finite grade ant colony optimization, is proposed to solve permutation flow shop problem, its main characteristic is that the updated quantities of pheromone trails are independent of objective function values, and the heuristic information provide by Moccellin is adopted. The developed algorithm has been applied to the benchmark problems given by Taillard, Comparison results demonstrate that the performance of the proposed algorithm is promising.
  • Keywords
    ant colony optimisation; flow shop scheduling; Moccellin; ant colony optimization algorithm; finite grade ant colony optimization; heuristic information; objective function value; permutation flow shop problem; pheromone trail; Ant colony optimization; Benchmark testing; Cities and towns; Europe; Job shop scheduling; Linear programming; Traveling salesman problems; ant colony algorithm; finite grade pheromone; permutation flow shop problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2012 10th World Congress on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-1397-1
  • Type

    conf

  • DOI
    10.1109/WCICA.2012.6357949
  • Filename
    6357949