DocumentCode
15807
Title
Preference Relations Based on Intuitionistic Multiplicative Information
Author
Meimei Xia ; Zeshui Xu ; Huchang Liao
Author_Institution
Sch. of Econ. & Manage., Tsinghua Univ., Beijing, China
Volume
21
Issue
1
fYear
2013
fDate
Feb. 2013
Firstpage
113
Lastpage
133
Abstract
Preference relations are powerful techniques to express the preferences over alternatives (or criteria) and mainly fall into two categories: fuzzy preference relations (also called reciprocal preference relations) and multiplicative preference relations. For a pair of alternatives, a fuzzy preference relation only gives the degree that an alternative is prior to another; thus, the intuitionistic fuzzy preference relation is introduced by adding the degree that an alternative is not prior to another, which can describe the preferences over two alternatives more comprehensively. However, the intuitionistic fuzzy preference uses the symmetrical scale to express the decision makers´ preference relations, which are inconsistent with our intuition in some situations. If we use the unsymmetrical scale to express the preferences about two alternatives instead of the symmetrical scale in intuitionistic fuzzy preference relation, then a new concept is introduced, which we call the intuitionistic multiplicative preference relation reflecting our intuition more objectively. In this paper, we study the aggregation of intuitionistic multiplicative preference information, propose some aggregation techniques, investigate their properties, and apply them to decision making based on intuitionistic multiplicative preference relations.
Keywords
decision making; fuzzy set theory; decision making; information aggregation technique; intuitionistic fuzzy preference relation; intuitionistic multiplicative information; intuitionistic multiplicative preference relation; reciprocal preference relations; unsymmetrical scale; Aggregates; Decision making; Fuzzy set theory; Aggregation operator; decision making; intuitionistic fuzzy set; preference relation;
fLanguage
English
Journal_Title
Fuzzy Systems, IEEE Transactions on
Publisher
ieee
ISSN
1063-6706
Type
jour
DOI
10.1109/TFUZZ.2012.2202907
Filename
6212345
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