Group Decision Making Process for Supplier Selection with TOPSIS Method under Interval-Valued Intuitionistic Fuzzy Numbers
Author(s) -
Mohammad Izadikhah
Publication year - 2012
Publication title -
advances in fuzzy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 19
eISSN - 1687-711X
pISSN - 1687-7101
DOI - 10.1155/2012/407942
Subject(s) - topsis , group decision making , selection (genetic algorithm) , ideal solution , mathematical optimization , interval (graph theory) , mathematics , decision matrix , supply chain management , supply chain , group (periodic table) , hamming distance , multiple criteria decision analysis , computer science , operations research , artificial intelligence , algorithm , combinatorics , chemistry , physics , organic chemistry , political science , law , thermodynamics
Supplier selection is a fundamental issue of supply chain area that heavily contributes to the overall supply chain performance, and, also, it is a hard problem since supplier selection is typically a multicriteria group decision problem. In many practical situations, there usually exists incomplete and uncertain, and the decision makers cannot easily express their judgments on the candidates with exact and crisp values. Therefore, in this paper an extended technique for order preference by similarity to ideal solution (TOPSIS) method for group decision making with Atanassov's interval-valued intuitionistic fuzzy numbers is proposed to solve the supplier selection problem under incomplete and uncertain information environment. In other researches in this area, the weights of each decision maker and in many of them the weights of criteria are predetermined, but these weights have been calculated in this paper by using the decision matrix of each decision maker. Also, the normalized Hamming distance is proposed to calculate the distance between Atanassov's interval-valued intuitionistic fuzzy numbers. Finally, a numerical example for supplier selection is given to clarify the main results developed in this paper
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