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Premium Decision making with probabilistic hesitant fuzzy information based on multiplicative consistency
Author(s)
Lin Mingwei,
Zhan Qianshan,
Xu Zeshui
Publication year2020
Publication title
international journal of intelligent systems
Resource typeJournals
PublisherWiley-Blackwell
Abstract The probabilistic hesitant fuzzy preference relations (PHFPRs) provide the decision makers with an efficient means to express the preference information on pairwise comparisons over alternatives. In this paper, we propose an automatic consistency improving model for PHFPRs. First, we propose a novel normalization algorithm to normalize probabilistic hesitant fuzzy elements (PHFEs) by using probability splitting idea and develop novel operational laws. Then, we define the consistency index to compute the degree of deviation between the PHFPRs and their multiplicative consistent PHFPRs. We also develop a novel consistency threshold estimation method for obtaining the threshold of consistency index and then put forward an automatic consistency improving algorithm for repairing inconsistent PHFPRs. Moreover, two probabilistic hesitant fuzzy aggregation operators are put forward to aggregate preference values in acceptably multiplicative consistent PHFPRs for obtaining the ranking orders of alternatives. Finally, an illustrative example is given to show the implementation process of our proposed automatic consistency improving model and also we compare our proposed model with the existing studies.
Subject(s)artificial intelligence , computer science , consistency (knowledge bases) , data mining , mathematical analysis , mathematics , multiplicative function , probabilistic logic
Language(s)English
SCImago Journal Rank1.291
H-Index87
eISSN1098-111X
pISSN0884-8173
DOI10.1002/int.22240

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