Method Selecting Correct One Among Alternatives Utilizing Intuitionistic Fuzzy Preference Relation Without Consensus Reaching Process

Hengshan Zhang, Qinghua Zheng, Zhongmin Wang, Yanping Chen, Ting Liu, Tianhua Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The methods with consensus reaching process can obtain a collective solution which is supported by most of decision makers in larger-scale group decision making. However, in case decision makers who could give correct opinions are from the minority, the conventional methods with consensus reaching process can not obtain the correct answer. In this paper, a novel method is developed to tackle this challenge. The decision makers give the opinions utilizing pairwise comparisons of the alternatives from positive and negative views based on intuitionistic fuzzy preference relation. The obtained opinions are translated into intuitionistic fuzzy numbers, and are further grouped and aggregated according to the alternatives. Based on the aggregated intuitionistic fuzzy numbers, the prediction normalized rate is defined and calculated for each alternative, the alternative with the minimal prediction normalized rate is selected as correct one. The experimental results show that the proposed method can obtain the correct answer even when the actual correct opinions are reflected by a small number of decision makers.
Original languageEnglish
Title of host publication2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
PublisherIEEE
Number of pages6
ISBN (Electronic)9781538617281
ISBN (Print)9781538617298
DOIs
Publication statusPublished - 10 Oct 2019
Event2019 IEEE International Conference on Fuzzy Systems - New Orleans, United States
Duration: 23 Jun 201926 Jun 2019

Conference

Conference2019 IEEE International Conference on Fuzzy Systems
CountryUnited States
CityNew Orleans
Period23/06/1926/06/19

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