Generalized intuitionistic fuzzy Bonferroni means

Meimei Xia, Zeshui Xu*, Bin Zhu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

155 Citations (Scopus)

Abstract

Intuitionistic fuzzy set is a widely used tool to express the membership, nonmembership, and hesitancy information of an element to a set. To aggregate the intuitionistic fuzzy information, a lot of aggregation techniques have been developed, especially, the ones which reflect the correlations of the aggregated arguments are the hot research topics, among which Bonferroni mean (BM) is an important aggregation technique. However, the classical BM ignores some aggregation information and the weight vector of the aggregated arguments. In this paper, we introduce the generalized weighted BM and the generalized intuitionistic fuzzy weighted BM, both of which focus on the group opinion. Paying more attention to the individual opinions, we further define the generalized weighted Bonferroni geometric mean and the generalized intuitionistic fuzzy weighted Bonferroni geometric mean. Various families of the existing operators can be obtained when the parameters of the developed aggregation techniques are assigned different values. Finally, we propose an approach to multicriteria decision making on the basis of the proposed aggregation techniques and an example is also given to illustrate our results.

Original languageEnglish
Pages (from-to)23-47
Number of pages25
JournalInternational Journal of Intelligent Systems
Volume27
Issue number1
DOIs
Publication statusPublished - Jan 2012
Externally publishedYes

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