基于前景理论和属性相关的概率语言SIR多属性群决策方法及应用

doi:10.16381/j.cnki.issn1003-207x.2023.2030

Abstract

Abstract:

In real life， it’s inevitable that the multi-attribute group decision-making has a series of problems such as fuzzy information， individual preferences and attribute association， which makes it difficult for decision-makers to accurately determine which alternative is the best alternative. How to abstract these practical decision-making problems into theoretical problems， and select the best alternative is the focus of this paper. To solve such a kind of problems， a multi-attribute group decision-making SIR （superiority and inferiority ranking） method based on Choquet integral and prospect theory is proposed. Firstly， a probabilistic linguistic Choquet integral operator is used to aggregate the decision-making information， and construct the group decision-making matrix. After that， considering that the SIR method ignores the risk preferences of experts， the proposed approach introduces prospect theory into the SIR method to construct the comprehensive prospect superiority and inferiority index. Then， to address the problem of attribute association， Choquet integral and attribute comprehensive weights are used to construct a new comprehensive prospect superiority and inferiority flow that can characterize the difference of alternatives. And then， alternatives are sorted according to the sorting rules of the SIR method. Finally， the feasibility and effectiveness of the proposed approach is indicated by an example of overseas location problem for cross-border e-commerce. The conclusion of this article is as follows：（1） Decision makers' risk preferences and linguistic preferences significantly affect the ranking of the alternatives， for example， risk aversion decision makers will tend to choose conservative strategies. （2） Compared with the classic SIR method and prospect theory， the proposed method can more intuitively analyze the differences between alternatives through pairwise comparison. In a word， the proposed approach can comprehensively consider the subjective and objective uncertainties of the decision-making environment， and is a further extension of the classic SIR method.

Key words: probabilistic linguistic term set, prospect theory, attribute association, SIR method, Choquet integral

CLC Number:

F273

Jie Yang,Zhikun Cai,Zhiwen Zheng, et al. A Prospect Theory and Attribute Association Based Probabilistic Linguistic Fuzzy SIR Method for Multi-attribute Group Decision-making and Its Application[J]. Chinese Journal of Management Science, 2026, 34(4): 77-88.

Figures/Tables 5

	偏好差别函数	结果
基于各类一般性准则的偏好差别函数^[9,11]	确定准则： $P j (x i, x t) = 0, d (L t j (p), L i j (p)) ≤ 0 1, d (L t j (p), L i j (p)) > 0$	$S 1 (x 1) = 1,$ $S 1 (x 2) = 2,$ $S 1 (x 3) = 0$
	U型准则： $P j (x i, x t) = 0, d (L t j (p), L i j (p)) ≤ u d (L i j - (p), L i j + (p)) 1, d (L t j (p), L i j (p)) > u d (L i j - (p), L i j + (p))$	$S 1 (x 1) = 0,$ $S 1 (x 2) = 2,$ $S 1 (x 3) = 0$
	线性准则： $P j (x i, x t) = 0, d (L i j (p), L t j (p)) ≤ 0 d (L i j (p), L t j (p)) / θ, 0 < d (L i j (p), L t j (p)) ≤ u d (L i j - (p), L i j + (p)) 1, d (L t j (p), L i j (p)) > u d (L i j - (p), L i j + (p))$	$S 1 (x 1) = 0.6,$ $S 1 (x 2) = 2,$ $S 1 (x 3) = 0$
本文所提偏好差别函数	$P j (x i, x t) = V + (x i, x t), L i j (p) ≻ L t j (p) V - (x i, x t), L i j (p) ≺ L t j (p) 0, 其他$	$S 1 (x 1) = 0 . 3 α κ + (0.3),$ $S 1 (x 2) = (1 . 1 α + 1) κ + (0.3),$ $S 1 (x 3) = 0$

文献	方法涉及	排序结果
[7]	前景理论、概率语言术语集、属性综合权重	$x 2 ≻ x 4 ≻ x 3 ≻ x 1$
[11]	PROMETHEE、概率语言术语集	$x 4 ≻ x 2 ≻ x 3 ≻ x 1$
[30]	概率语言术语集、TODIM法	$x 4 ≻ x 2 ≻ x 3 ≻ x 1$
本文方法	概率语言术语集、前景理论、属性相关、SIR法	$x 4 ≻ x 2 ≻ x 3 ≻ x 1$

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A Prospect Theory and Attribute Association Based Probabilistic Linguistic Fuzzy SIR Method for Multi-attribute Group Decision-making and Its Application

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