• DocumentCode
    2666986
  • Title

    Study on ant colony optimization for people assign to job problem

  • Author

    Wang, Suxin ; Wang, Leizhen ; Li, Yongqing ; Sun, Jianyong

  • Author_Institution
    Northeastern Univ. at Qinhuangdao, Qinhuangdao, China
  • fYear
    2012
  • fDate
    23-25 May 2012
  • Firstpage
    872
  • Lastpage
    874
  • Abstract
    To deal with people assign to job optimization problem in getting into local minima, people assign to job problem (PATJP) model and ant colony optimization (ACO) are developed for people assign to job optimization problem. In PATJP model, one people can assign to more than one job, and one job can be done by more than one people. People assign to job optimization is searched by ACO, optimization processes tend to get the global solution. Illustration results show that PATJP model and ACO algorithm are effective and offer a way to PATJP.
  • Keywords
    ant colony optimisation; ACO algorithm; PATJP model; ant colony optimization; global solution; job optimization problem; local minima; people assign to job problem model; Algorithm design and analysis; Ant colony optimization; Cybernetics; Educational institutions; Electronic mail; Learning automata; Optimization; Ant Colony Optimization (ACO); Assignment Problem (AP); People Assign to Job Problem (PATJP);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2012 24th Chinese
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4577-2073-4
  • Type

    conf

  • DOI
    10.1109/CCDC.2012.6244135
  • Filename
    6244135