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Impact Factor:8.139
DOI number:10.1016/j.knosys.2021.107740
Journal:Knowledge-based systems (中科院一区)
Key Words:Distributed preference relation；Group decision making；Consistency；Consensus；Evidential reasoning
Abstract:Belief distribution (BD) is a scheme of representing qualitative information with subjective uncertainty and imprecision. Distributed preference relation (DPR) extends BDs to the form of pairwise comparison by expressing the preferred, non-preferred, indifferent, and uncertain degrees of one decision alternative over another. However, previous studies on DPR only require comparison of adjacent alternatives, and consensus reaching is not considered fully in the decision making process. To solve this problem, a complete DPR model is presented in this paper to support group decision making (GDM). First, a consistency index is defined to measure the consistency level of the complete DPR representing experts’ judgments. Second, an automatic adjustment algorithm is proposed to improve the consistency of DPRs with unacceptable consistency to an acceptable level. Third, the evidential reasoning (ER) algorithm is utilized to aggregate all the DPRs together, and an optimization model is further constructed to generate experts’ weights, which maximizes the degree of consensus among experts. A GDM example is provided to illustrate the applicability and validity of the proposed DPR model, and comparative analysis demonstrates the potential of the proposed method in supporting real-world GDM problems.
Co-author:Meng Hu (共同通讯),Yu-Wang Chen (共同通讯),Ba-Yi Cheng,Jian Wu,Enrique Herrera-Viedma
First Author:Mi Zhou
Indexed by:Journal paper
Document Code:107740
Discipline:Management Science
Document Type:J
Volume:236
Page Number:107740
Translation or Not:no
Date of Publication:2022-01-01
Included Journals:SCI