Maximizing deviation method for multiple attribute decision making in intuitionistic fuzzy setting

2008 ◽  
Vol 21 (8) ◽  
pp. 833-836 ◽  
Author(s):  
Gui-Wu Wei
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Maximizing Deviation Method ◽  
Fuzzy Setting ◽  
Deviation Method

TOPSIS Method for Multiple Attribute Decision Making Problem in Intuitionistic Fuzzy Setting

2013 ◽  
Vol 427-429 ◽  
pp. 1888-1891
Author(s):  
Yuan Yuan He ◽  
Zai Wu Gong
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Information ◽  
Topsis Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Fuzzy Setting

This paper is concerned with a TOPSIS method for fuzzy multiple attribute decision making, in which the information about attribute weights is completely known and the attribute values take form of intuitionistic fuzzy numbers. A class of distance for describing the deviation degrees between intuitionistic fuzzy sets is used to measure difference between two alternatives. A model of TOPSIS is designed with the introduction of the particular closeness coefficient composed of similarity degrees. Then, we apply the TOPSIS method to aggregate the fuzzy information corresponding to each alternative, and rank the alternatives according to their closeness coefficients. Finally, a numerical example is given to show the feasibility and effectiveness of the method.

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