• DocumentCode
    2756855
  • Title

    Synthetic Optimization in Project Schedule by Using Ant Colony Algorithm

  • Author

    Zhang, Weina ; Huang, Yuansheng ; Wang, Mingyan

  • Author_Institution
    Dept. of Economy & Manage., North China Electr. Power Univ., Baoding
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    6554
  • Lastpage
    6558
  • Abstract
    From the view that the maximum economic benefits can be obtained by optimizing the project schedule, this paper uses systemic method and puts forward a mathematical model which considers the synthetic optimization of the cost, the supply of resources and the latent uncertainties, all factors influencing the overall project schedule. Then by changing the election strategy and the local search strategy, the ant colony algorithm is improved and is applied in the process of optimizing the model. Finally, an example is used to prove the improved ant colony algorithm is of high effectiveness in solving the synthetic optimization of project schedule
  • Keywords
    optimisation; project management; scheduling; ant colony algorithm; election strategy; mathematical model; project schedule; resources supply; schedule control; synthetic optimization; Ant colony optimization; Costs; Energy management; Investments; Mathematical model; Optimal scheduling; Power generation economics; Project management; Scheduling algorithm; Uncertainty; Ant colony algorithm; Schedule control; Synthetic optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1714349
  • Filename
    1714349