Decision field theory-combined multi-attribute group decision-making method for incomplete linear ordinal ranking

被引:1
|
作者
Liu, Nana [1 ,4 ]
Xu, Zeshui [2 ]
Wu, Hangyao [3 ]
机构
[1] Chongqing Technol & Business Univ, Sch Business Adm, Chongqing 400067, Peoples R China
[2] Sichuan Univ, Business Sch, Chengdu 610064, Sichuan, Peoples R China
[3] Chongqing Technol & Business Univ, Sch Management Sci & Engn, Chongqing 400067, Peoples R China
[4] Chongqing Technol & Business Univ, Res Ctr Enterprise Management, Chongqing 400067, Peoples R China
关键词
Incomplete linear ordinal ranking; Decision field theory; Probabilistic utility set; Psychological difference; PSYCHOLOGICAL DISTANCE; AGGREGATION; ALGORITHM; SELECTION;
D O I
10.1016/j.asoc.2023.110056
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In practice, experts sometimes compare alternatives from different perspectives by rankings to express their preferences. However, it is common that the comparing information they give is incomplete, and experts' preferences are changing during the decision-making process. In this situation, it is not easy to depict experts' preferences and making appropriate decisions. Hence, to handle the problems, this paper proposes a multi-attribute group decision-making (MAGDM) method for incomplete linear ordinal ranking (ILOR) information combined with the decision field theory (DFT) from the perspective of process-oriented decision-making. Firstly, the extended preference map and information energy for ILOR are improved. Based on those, the concept of probabilistic utility set (PUS) and some basic operations are proposed to enhance the computability of ILOR, which can convert incomplete ILORs to PUS and depict the experts' preferences effectively. Then, the framework and the detailed steps of the DFT-combined MAGDM method are presented, in which the psychological difference for PUS is established. The method helps depict the distance felt by experts and the variability of the decisionmaking process. Finally, the illustrations are conducted to show the usage and features of the proposed method. The illustration shows the good interpretability and accuracy of the method.& COPY; 2023 Elsevier B.V. All rights reserved.
引用
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页数:19
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