• DocumentCode
    3458718
  • Title

    Ant Colony Optimization for the Stochastic Loader Problem

  • Author

    Zhao, Peixin ; Wang, Hong

  • Author_Institution
    Sch. of Manage., Shandong Univ., Jinan
  • fYear
    2006
  • fDate
    20-23 Aug. 2006
  • Firstpage
    1052
  • Lastpage
    1056
  • Abstract
    In 2004, Tang proposed a new NP-hard combinational optimization problem that frequently arises in practice - the loader problem (a transportation model). Two special cases of the problem (the restricted loader problem and the equal loader problem) and optimal solution strategy have been considered. In this paper, we extend Tang´s model by proposing the stochastic quantity of load and unload at each station that make the model more applicable in practice. An ant colony optimization (ACO) algorithm is designed for solving the .stochastic loader problem. Two numerical examples are presented to illustrate the application of the developed model.
  • Keywords
    combinatorial mathematics; computational complexity; optimisation; stochastic processes; transportation; NP-hard; ant colony optimization; combinational optimization; stochastic loader problem; stochastic quantity; Ant colony optimization; Conference management; Educational institutions; Embryo; Linear programming; Logistics; Mathematics; Remuneration; Stochastic processes; Transportation; ant colony optimization; loader problem; stochastic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Acquisition, 2006 IEEE International Conference on
  • Conference_Location
    Shandong
  • Print_ISBN
    1-4244-0528-9
  • Electronic_ISBN
    1-4244-0529-7
  • Type

    conf

  • DOI
    10.1109/ICIA.2006.305885
  • Filename
    4097818