A novel approach to multi-attribute group decision-making: Optimistic and pessimistic three-state three-way decision models

被引:0
|
作者
Ju, Yanbing [1 ]
Xu, Yanxin [1 ,2 ]
Wang, Han [1 ,2 ]
Ju, Tian [3 ]
Li, Xia [1 ]
Herrera-Viedma, Enrique [2 ]
机构
[1] Beijing Inst Technol, Sch Management, Beijing 100081, Peoples R China
[2] Univ Granada, Andalusian Res Inst Data Sci & Computat Intelligen, Dept Comp Sci & AI, E-18071 Granada, Spain
[3] China Agr Univ, Int Coll, Beijing 100091, Peoples R China
关键词
Three-state three-way decision (TSTWD); Three-way decision (TWD); Multi-attribute group decision-making (MAGDM); Conditional probability; Relative loss function;
D O I
10.1016/j.asoc.2025.112803
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The three-state three-way decision (TSTWD) model extends the classic three-way decision (TWD) model by incorporating an uncertainty state. To properly describe decision risks inherent in multi-attribute group decision-making (MAGDM) problem, this paper proposes a novel approach employing optimistic and pessimistic TSTWD models. Firstly, the optimistic and pessimistic TSTWD models are constructed to effectively capture the diverse attitudes of decision-makers (DMs) towards different decision-making scenarios. Secondly, the relative loss functions of the proposed two TSTWD models are derived based on the attribute evaluation values, respectively, and some properties of three threshold functions are discussed in detail. Thirdly, a framework to solve the MAGDM problem is developed based on proposed optimistic and pessimistic TSTWD models, in which the conditional probabilities with respect to the three states are calculated based on the positive ideal solution, negative ideal solution, and compromise solution, respectively. Simultaneously, a loss function aggregation method is presented to determine the comprehensive losses of alternatives. Finally, the feasibility and effectiveness of the proposed method are verified through illustrative examples, sensitivity as well as comparative analysis.
引用
收藏
页数:23
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