A Multi-criteria Interval-Valued Intuitionistic Fuzzy Group Decision Making for Supplier Selection with TOPSIS Method

2009 ◽  
pp. 303-312 ◽  
Author(s):  
Kavita ◽  
Shiv Prasad Yadav ◽  
Surendra Kumar
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Topsis Method ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Group ◽  
Fuzzy Group Decision Making ◽  
Interval Valued

scholarly journals Group Decision Making Process for Supplier Selection with TOPSIS Method under Interval-Valued Intuitionistic Fuzzy Numbers

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Mohammad Izadikhah
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Topsis Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Interval Valued

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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