Title :
Grey relational analysis method for multiple attribute decision making with incomplete weight information in intuitionistic fuzzy setting
Author :
Wei, Guiwu ; Yi, Wende
Author_Institution :
Dept. of Econ. & Manage., Chongqing Univ. of Arts & Sci., Chongqing
Abstract :
The aim of this paper is to investigate the multiple attribute decision making problems with intuitionistic fuzzy information, in which the information about attribute weights is incompletely known, and the attribute values take the form of intuitionistic fuzzy numbers. In order to get the weight vector of the attribute, we establish an optimization model based on the basic ideal of traditional grey relational analysis (GRA) method, by which the attribute weights can be determined. Then, based on the traditional GRA method, calculation steps for solving intuitionistic fuzzy multiple attribute decision-making problems with incompletely known weight information are given. The degree of grey relation between every alternative and positive ideal solution and negative ideal solution are calculated. Then, a relative relational degree is defined to determine the ranking order of all alternatives by calculating the degree of grey relation to both the positive-ideal solution (PIS) and negative-ideal solution (NIS) simultaneously. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Keywords :
decision making; fuzzy set theory; grey systems; fuzzy multiple attribute decision-making problems; grey relational analysis method; incomplete weight information; intuitionistic fuzzy setting; multiple attribute decision making; negative-ideal solution; positive-ideal solution; Decision making; Fuzzy sets; Information analysis; GRA; Incomplete weight information; Intuitionistic fuzzy numbers; Multiple attribute decision-making;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4597669