DocumentCode
510134
Title
Group Decision Making with Linguistic Preference Relations Based on Fuzzy Measures
Author
Tan, Chunqiao
Author_Institution
Sch. of Bus., Central South Univ., Changsha, China
Volume
1
fYear
2009
fDate
7-8 Nov. 2009
Firstpage
500
Lastpage
504
Abstract
Linguistic preference relation is a useful tool for expressing preferences of decision makers in group decision making according to linguistic scales. But in the real decision problems, there usually exist interactive phenomena among the preference of decision makers so that it is not suitable for us to aggregate preference information by conventional additive aggregation operators. Thus, to approximate the human subjective preference evaluation process, it would be more suitable to apply non-additive measures tool, where it is not necessary to assume additivity and independence among preference of decision makers. In this paper, based on the fuzzy measure, we developed a new linguistic ordered geometric averaging operator to aggregate the multiplicative linguistic preference relations, where interactions or dependence among subjective preference of decision makers are considered. Further, the procedure and algorithm of group decision making based on the new linguistic aggregation operators is given. Finally, a practical example is provided to illustrate the developed approaches.
Keywords
computational linguistics; decision making; fuzzy set theory; fuzzy measures; group decision making; human subjective preference evaluation process; linguistic ordered geometric averaging operator; multiplicative linguistic preference relations; Additives; Aggregates; Artificial intelligence; Computational intelligence; Concrete; Decision making; Fuzzy sets; Humans; Phase measurement; Power measurement; Fuzzy measure; Group decision making; Linguistic preference relations; aggregation operator;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-3835-8
Electronic_ISBN
978-0-7695-3816-7
Type
conf
DOI
10.1109/AICI.2009.140
Filename
5376283
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