• DocumentCode
    2344269
  • Title

    Multiple attribute decision making with intuitionistic fuzzy information and uncertain attribute weights using minimization of regret

  • Author

    Luo, Yujun ; Wei, Guiwu

  • Author_Institution
    Dept. of Comput. Sci. & Math., North Sichuan Med. Coll., Nanchong
  • fYear
    2009
  • fDate
    25-27 May 2009
  • Firstpage
    3720
  • Lastpage
    3723
  • Abstract
    In regard to the multiple attribute decision making problems with the information about attribute weights incompletely known under the intuitionistic fuzzy environment, the score function and accuracy function are introduced. The decision making matrix with the attribute value expressed by form of intuitionistic fuzzy number is transformed into the score matrix of the alternatives. Then according to the concept of regret, regret matrix of the alternatives is obtained. And an optimization model based on the principle of minimization of regret, by which the attribute weights can be derived, is established. The alternatives can be ranked, and the most desirable one can be selected according to the score function and accuracy function. Finally, an illustrative example is given to verify the briefness and effectiveness of the proposed approach.
  • Keywords
    decision making; decision theory; fuzzy set theory; matrix algebra; minimisation; accuracy function; intuitionistic fuzzy information; matrix algebra; multiple attribute decision making; optimization; regret minimization; score function; uncertain attribute weight; Art; Computer science; Decision making; Educational institutions; Environmental economics; Functional programming; Fuzzy sets; Mathematical model; Mathematical programming; Mathematics; Intuitionistic fuzzy set; minimization of regret; multiple attribute decision making; uncertain attribute weights;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4244-2799-4
  • Electronic_ISBN
    978-1-4244-2800-7
  • Type

    conf

  • DOI
    10.1109/ICIEA.2009.5138897
  • Filename
    5138897