Towards achieving consistent opinion fusion in group decision making with complete distributed preference relations
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影响因子：8.139
DOI码：10.1016/j.knosys.2021.107740
发表刊物：Knowledge-based systems (中科院一区)
关键字：Distributed preference relation；Group decision making；Consistency；Consensus；Evidential reasoning
摘要：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.
合写作者：Meng Hu (共同通讯),Yu-Wang Chen (共同通讯),Ba-Yi Cheng,Jian Wu,Enrique Herrera-Viedma
第一作者：Mi Zhou
论文类型：期刊论文
论文编号：107740
学科门类：管理学
文献类型：J
卷号：236
页面范围：107740
是否译文：否
发表时间：2022-01-01
收录刊物：SCI