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
Link To Document