• DocumentCode
    2163939
  • Title

    Application of the improved multi-attribute group decision model based on TOPSIS to select construction-agency

  • Author

    Wu Yunna ; Ping, Lin ; Hongyu, Yan

  • Author_Institution
    Department of Economic & Management, North China Electric Power University, Beijing, China
  • fYear
    2010
  • fDate
    4-6 Dec. 2010
  • Firstpage
    5707
  • Lastpage
    5711
  • Abstract
    Government investment projects play a pivotal role in socialist economic construction, and government indicate clearly that implementation construction-agent system in government investment projects. The key of implementation construction-agent system is to select a professional construction-agency by open competition. We know that science selecting system can control the risk source of government investment projects effectively, and evaluation and determination bidding is the critical process of tender, so the core problem of evaluation of bidding is how to select a rational, scientific decision model which to select optimal solution from finite solutions. In order to increase the efficiency of construction-agency evaluation, the improved multi-attribute group decision model based on TOPSIS is proposed in this paper, we adopt the Minkowski distance to improve TOPSIS model, which solve the over weighted problem in the original TOPSIS model. Finally, a representative case to illuminate the application of the model, which picture the calculation procedures and verify the operability of the model, the model is an effective method to evaluation construction-agency
  • Keywords
    Decision support systems; Minkowski distance; TOPSIS; construction-agency evaluation; un-operating government projects;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2010 2nd International Conference on
  • Conference_Location
    Hangzhou, China
  • Print_ISBN
    978-1-4244-7616-9
  • Type

    conf

  • DOI
    10.1109/ICISE.2010.5691864
  • Filename
    5691864