Consistency- and Consensus-Based Group Decision-Making Method With Incomplete Probabilistic Linguistic Preference Relations

The use of incomplete probabilistic linguistic term sets (InPLTSs) can enrich the flexibility of qualitative decision-making information expression, especially in decision-making situations with high time pressure and insufficient knowledge. In this article, we develop a method for group decision-ma...

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Vydané v:IEEE transactions on fuzzy systems Ročník 29; číslo 9; s. 2565 - 2579
Hlavní autori: Liu, Peide, Wang, Peng, Pedrycz, Witold
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.09.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Consensus
Consistency
Decision making
expected multiplicative consistency
group decision-making (GDM)
incomplete probabilistic linguistic preference relation (InPLPRs)
Indexes
induced ordered weighted geometric operator
Linguistics
Mathematical analysis
Mathematical model
Mathematical programming
mathematical programming model
Optimization
Probabilistic logic
Reliability
ISSN:1063-6706, 1941-0034
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Shrnutí:The use of incomplete probabilistic linguistic term sets (InPLTSs) can enrich the flexibility of qualitative decision-making information expression, especially in decision-making situations with high time pressure and insufficient knowledge. In this article, we develop a method for group decision-making (GDM) with incomplete probabilistic linguistic preference relations (InPLPRs), considering consistency and consensus simultaneously. First, to fully explore the ability of InPLTSs to express uncertain information, InPLTSs are specifically classified. Then, an expected multiplicative consistency of InPLPRs is introduced, which is conducive to estimating the missing information more accurately and effectively. Subsequently, considering the consensus of GDM problems, a consensus index, which considers the principle of majority and minority, is developed to measure the agreement degree among multiple individuals. Because individual InPLPRs may not all meet acceptable consistency after reaching consensus, a consistency- and consensus-improving mathematical programming model considering information distortion is presented. Then, to aggregate all individual preference relations into a collective one, a reliability-induced ordered weighted geometric operator is introduced, whose induced variable reliability is determined by the confidence degree and consistency index of individual preference relations. Furthermore, a multiphase algorithm with InPLPRs is developed to solve GDM problems. Finally, a numerical example of fire emergency decisions is presented to illustrate the applicability of the proposed method, and a detailed validity test and comparative analysis are conducted to highlight the advantages of the proposed method.
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ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2020.3003501