• DocumentCode
    2006036
  • Title

    Vendor selection using genetic algorithm

  • Author

    Sharmeen, S. ; Ali, M.A. ; Ripon, Shamim ; Kabir, Md Humayun ; Shil, N.C.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., East West Univ., Dhaka, Bangladesh
  • fYear
    2012
  • fDate
    20-24 Nov. 2012
  • Firstpage
    1877
  • Lastpage
    1881
  • Abstract
    Selecting the right vendor is a complex business decision due to a huge number of competing vendors with a large number of complex criteria. The organization will suffer in the long run if vendors are not chosen wisely. Under multi criteria decision making, an algorithm, named VSFI, based on fuzzy clustering was proposed to select the most optimal vendors. VSFI highly depends on the randomized initial values of fuzzy clustering algorithm. This may sometime select wrong vendor. Addressing this problem, this paper proposes a genetic algorithm based solution using a fitness function. This solution finds the best vendor successfully. It can also suggest the competing vendors to improve themselves in some criteria so that they can increase their chance of winning in the selection process.
  • Keywords
    decision making; fuzzy set theory; genetic algorithms; operations research; pattern clustering; VSFI algorithm; business decision; complex criteria; fitness function; fuzzy clustering algorithm; genetic algorithm; most optimal vendor selection; multicriteria decision making; randomized initial values; AHP; Fuzzy clustering; genetic algorithm and vendor selection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
  • Conference_Location
    Kobe
  • Print_ISBN
    978-1-4673-2742-8
  • Type

    conf

  • DOI
    10.1109/SCIS-ISIS.2012.6505246
  • Filename
    6505246