基于多粒度概率语言和双参照点的应急决策方法

doi:10.16381/j.cnki.issn1003-207x.2023.0990

Abstract

Abstract:

In order to promote the comprehensive development of economy， over-exploitation of various resources have increased， resulting in various emergencies such as natural disasters and accidents. It is of great significance to study how to improve the effectiveness of decision-making under the imperfect and complex scenarios. The main problems are uncertainties and risk issues in the procedures， which are difficult to be effectively addressed. For reflecting the uncertainty of decision information and limited rationality of decision-makers in an effective way， a new emergency response decision-making based on multi-granularity probabilistic linguistic and double reference points is presented. Firstly， multi-granularity probabilistic linguistic variables are used to express the decision-makers’ evaluation of each key risk factor， and the weights of key risk factors are determined based on an improved method to address multi-granularity probabilistic linguistic information. Secondly， the cumulative prospect theory， which can embody the characteristic of loss-aversion of decision-makers， is applied to the multi-granularity probabilistic linguistic environment， then， the perceived values of each feasible alternative’s estimated effect are calculated by the certain double reference points. Thirdly， the earn perceived weight and loss perceived weight of each feasible alternative’s estimated probability is determined， on this basis， the ultimate perceived value of each alternative is obtained by combining the weights of key risk factors， and the best alternatives can be determined. Finally， the response to forest fire illustrates the effectiveness of the proposed method， and verifies the superiority by comparative analysis. The proposed integrated model based on multi-granularity probabilistic linguistic and double reference points not only represent the imprecise and vague information more effectively， but also consider the decision makers’ bounded rationality under risk comprehensively， and then provide some clues for the effective processing of information theories in emergency decision-making process.

Key words: emergency events, emergency decision-making, multi-granularity probabilisticlinguistic, cumulative prospect theory, double reference points

CLC Number:

C934

Zengqiang Wang,Yun Pu. An Emergency Decision-Making Method Based on Multi-granularity Probabilistic Linguistic Terms and Double Reference Points[J]. Chinese Journal of Management Science, 2026, 34(2): 195-206.

Figures/Tables 10

决策成员	$A 1$	$A 2$	$A 3$	$A 4$	$A 5$
$A 1$	--	$s 4 / 3 4$	$s 4 / 3 4$	$s 34$	$s 1 / 3 4$
$A 2$	$s 14$	--	$s 04$	$s 34$	$s 04$
$A 3$	$s 34$	$s 4 / 3 4$	--	$s 4 / 3 4$	$s 4 / 3 4$
$A 4$	$s 1 / 3 4$	$s 34$	$s 1 / 3 4$	--	$s 4 / 3 4$
$A 5$	$s 3 / 2 4$	$s 34$	$s 34$	$s 04$	--

决策成员	$d 1$	$d 2$	$d 3$	$d 4$	$d 5$	$d 6$
$A 1$	$s 4 / 3 4 1$	$s 34 1$	$s 1 / 3 4 0.4, s 4 / 3 4 0.6$	$s 1 / 3 4 1$	$s 4 / 3 4 1$	$s 34 1$
$A 2$	$s 14 0.7, s 34 0.3$	$s 14 1$	$s 14 1$	$s 14 1$	$s 04 1$	$s 14 0.4, s 34 0.6$
$A 3$	$s 34 1$	$s 4 / 3 4 0.3, s 34 0.7$	$s 1 / 3 4 0.3, s 4 / 3 4 0.7$	$s 1 / 3 4 1$	$s 4 / 3 4 1$	$s 4 / 3 4 0.3, s 34 0.7$
$A 4$	$s 4 / 3 4 1$	$s 4 / 3 4 0.2, s 34 0.8$	$s 1 / 3 4 0.4, s 4 / 3 4 0.6$	$s 1 / 3 4 1$	$s 4 / 3 4 1$	$s 34 1$
$A 5$	$s 3 / 2 4 0.4, s 34 0.6$	$s 3 / 2 4 0.4, s 34 0.6$	$s 3 / 2 4 1$	$s 3 / 4 4 1$	$s 3 / 4 4 1$	$s 3 / 2 4 0.4, s 34 0.6$

$d 1$	$d 2$	$d 3$	$d 4$	$d 5$	$d 6$
$1.923,0.306,0.017$	$2.307,0.197,0.011$	$1.08,0.106,0.006$	$0.7,0, 0$	$1.1,0, 0$	$2.62,0.331,0.017$

风险因素	方案	$θ 1$	$θ 2$	$θ 3$	$θ 4$
$d 1$	$X 1$	$s 1.137 4 0.30$	$s 1.073 4 0.30$	$s - 0.139 4 0.25$	$s - 0.538 4 0.15$
	$X 2$	$s 0.451 4 0.25$	$s 0.728 4 0.40$	$s 0.517 4 0.20$	$s - 0.372 4 0.15$
	$X 3$	$s 1.024 4 0.35$	$s 0.918 4 0.35$	$s - 0.081 4 0.25$	$s - 0.468 4 0.05$
$d 2$	$X 1$	$s - 0.992 4 0.15$	$s 0.589 4 0.20$	$s 1.913 4 0.30$	$s - 1.081 4 0.35$
	$X 2$	$s 1.637 4 0.40$	$s 0.193 4 0.30$	$s - 0.383 4 0.20$	$s - 0.872 4 0.10$
	$X 3$	$s 1.779 4 0.35$	$s - 0.145 4 0.30$	$s - 0.423 4 0.25$	$s - 0.872 4 0.10$
$d 3$	$X 1$	$s 0.362 4 0.15$	$s 0.983 4 0.30$	$s - 1.027 4 0.45$	$s - 0.293 4 0.10$
	$X 2$	$s 0.528 4 0.20$	$s 0.645 4 0.35$	$s 0.781 4 0.35$	$s - 0.472 4 0.10$
	$X 3$	$s 0.683 4 0.25$	$s 1.293 4 0.40$	$s 0.458 4 0.30$	$s - 0.659 4 0.05$
$d 4$	$X 1$	$s - 0.621 4 0.15$	$s 0.863 4 0.25$	$s 0.998 4 0.40$	$s - 0.432 4 0.20$
	$X 2$	$s 0.453 4 0.15$	$s 0.972 4 0.35$	$s 0.792 4 0.40$	$s - 0.326 4 0.10$
	$X 3$	$s 0.581 4 0.25$	$s 1.576 4 0.40$	$s 0.527 4 0.25$	$s - 0.439 4 0.10$
$d 5$	$X 1$	$s 1.019 4 0.35$	$s 0.863 4 0.30$	$s - 0.274 4 0.20$	$s - 0.629 4 0.15$
	$X 2$	$s 0.148 4 0.20$	$s 0.826 4 0.40$	$s 0.472 4 0.30$	$s - 0.235 4 0.10$
	$X 3$	$s 0.729 4 0.45$	$s 0.632 4 0.35$	$s - 0.109 4 0.15$	$s - 0.396 4 0.05$
$d 6$	$X 1$	$s 1.386 4 0.10$	$s 0.863 4 0.30$	$s 0.381 4 0.40$	$s 1.223 4 0.40$
	$X 2$	$s 1.082 4 0.15$	$s 0.937 4 0.20$	$s 0.932 4 0.40$	$s 1.139 4 0.25$
	$X 3$	$s 0.782 4 0.25$	$s 1.035 4 0.25$	$s - 1.156 4 0.30$	$s - 0.883 4 0.20$

目标值	$d 1$	$d 2$	$d 3$	$d 4$	$d 5$	$d 6$
$ϕ i μ$	$S 1 / 3 4$	$S 04$	$S 04$	$S 1 / 3 4$	$S 04$	$S 1 / 3 4$
$ϕ i ν$	$S 04$	$S - 1 / 3 4$	$S - 1 / 3 4$	$S 04$	$S - 1 / 3 4$	$S 04$

风险因素	方案	$θ 1$	$θ 2$	$θ 3$	$θ 4$
$d 1$	$X 1$	0.775	0.775	0.741	0.808
	$X 2$	0.806	0.720	0.840	0.808
	$X 3$	0.747	0.747	0.741	0.907
$d 2$	$X 1$	0.808	0.840	0.775	0.689
	$X 2$	0.720	0.775	0.772	0.852
	$X 3$	0.747	0.714	0.741	0.852
$d 3$	$X 1$	0.876	0.775	0.647	0.852
	$X 2$	0.840	0.747	0.747	0.852
	$X 3$	0.806	0.720	0.775	0.907
$d 4$	$X 1$	0.808	0.806	0.720	0.772
	$X 2$	0.876	0.747	0.720	0.852
	$X 3$	0.806	0.720	0.806	0.852
$d 5$	$X 1$	0.747	0.775	0.772	0.808
	$X 2$	0.840	0.720	0.775	0.852
	$X 3$	0.695	0.747	0.808	0.907
$d 6$	$X 1$	0.914	0.775	0.720	0.720
	$X 2$	0.876	0.840	0.720	0.806
	$X 3$	0.806	0.806	0.714	0.772

方案	$d 1$	$d 2$	$d 3$	$d 4$	$d 5$	$d 6$
$X 1$	-1.156	-1.414	-0.390	0.639	-0.187	2.742
$X 2$	0.467	-1.466	1.089	2.113	0.790	3.066
$X 3$	0.867	-1.173	1.613	0.749	0.042	-1.189

文献	方法描述	$d 1$	$d 2$	$d 3$	$d 4$	$d 5$	$d 6$	相关系数
文献[16]	基于所定义的广义区间二元语言WAA算子，决策成员从给定的二元语言评估标度中选择偏好的语言短语，用二元语言区间值表征信息的不确定性	0.169	0.223	0.157	0.112	0.148	0.191	0.901^*
文献[17]	决策成员使用数字标度表征各项风险因素的重要度，结合给定的决策者权重确定各项风险因素的权重	0.180	0.234	0.163	0.121	0.104	0.198	0.837^*
文献[18]	基于改进的Louvain算法，决策成员从给定的概率语言评估标度中选择偏好的语言短语，结合群体意见的一致性及其社会网络关系来确定各项风险因素的权重	0.189	0.222	0.152	0.092	0.132	0.213	0.949^**
文献[19]	决策成员使用模糊数表征各项风险因素的重要度，基于改进的模糊TOPSIS结合给定的决策者权重确定各项风险因素权重	0.196	0.228	0.122	0.137	0.081	0.236	0.874^*
本文方法	决策成员从多个概率语言评估标度中选择偏好的评估标度和语言短语，基于所提出的拓展多粒度概率语言决策方法结合决策者的相对重要度和标准化信息获取风险因素的权重	0.183	0.240	0.111	0.080	0.126	0.260

		综合评价值（ $X 1$ ）	综合评价值（ $X 2$ ）	综合评价值（ $X 3$ ）	排序结果
单参照点	底线目标	0.234	0.675	0.136	$X 2 ≻ X 1 ≻ X 3$
单参照点	理想目标	-0.197	0.366	-0.524	$X 2 ≻ X 1 ≻ X 3$
期望效用理论		56.379	49.293	31.238	$X 1 ≻ X 2 ≻ X 3$
本文方法		0.146	0.920	-0.188	$X 2 ≻ X 1 ≻ X 3$

References 19

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An Emergency Decision-Making Method Based on Multi-granularity Probabilistic Linguistic Terms and Double Reference Points

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