DEMATEL复杂因素分析算法最新进展综述

doi:10.3778/j.issn.1673-9418.2106089

计算机科学与探索 ›› 2022, Vol. 16 ›› Issue (3): 541-551.DOI: 10.3778/j.issn.1673-9418.2106089

DEMATEL复杂因素分析算法最新进展综述

孙永河, 黄子航⁺(), 李阳

昆明理工大学管理与经济学院,昆明 650093

收稿日期:2021-06-24 修回日期:2021-09-29 出版日期:2022-03-01 发布日期:2021-10-15
通讯作者: + E-mail: hzh1175593327@163.com
作者简介:孙永河(1978—),男,山西大同人,博士,教授,主要研究方向为复杂系统管理决策。
黄子航(1994—),女,黑龙江鹤岗人,博士研究生,主要研究方向为复杂系统管理决策。
李阳（1984—）,女,博士研究生,主要研究方向为基于组织行为学的高校科研团队管理研究。
基金资助:
国家自然科学基金(72061018);国家自然科学基金(71561015);云南省“万人计划”青年拔尖人才专项;昆明理工大学硕博生科研激励计划一般项目

Review of State of the Art on DEMATEL Algorithms for Complex Factor Analysis

SUN Yonghe, HUANG Zihang⁺(), LI Yang

Faculty of Management and Economics, Kunming University of Science and Technology, Kunming 650093, China

Received:2021-06-24 Revised:2021-09-29 Online:2022-03-01 Published:2021-10-15
About author:SUN Yonghe, born in 1978, Ph.D., professor. His research interest is management decision-making in complex system.
HUANG Zihang, born in 1994, Ph.D. candidate. Her research interest is management decision-making in complex system.
LI Yang, born in 1984, Ph.D. candidate. Her reearch interest is organizational behavior study of university’s scientific research teams.
Supported by:
National Natural Science Foundation of China(72061018);National Natural Science Foundation of China(71561015);Project of Yunnan Province “Ten Thousand People Plan” for Young Top-Notch Talents;Research Incentive Scheme Fund of Kunming University of Science and Technology for Master’s and Doctoral Students

摘要/Abstract

摘要：

当前,面对严峻复杂的国际新冠疫情和世界经济形势,管理决策所面临的问题也日趋复杂。因此,对复杂问题进行因素关联分析对于管理者认知复杂事物核心、抓住事物主要矛盾以有效解决复杂社会经济问题至关重要。决策试行与评价实验室方法（DEMATEL）作为一种对复杂系统因素间关联关系进行分析的有效工具,近年来已经受到国内外学者的广泛关注。通过系统地研究相关文献,按照DEMATEL方法运作的逻辑顺序从系统结构、评价标度、因素间的自依赖关系、中心度与原因度的指标确定、关键因素辨识五方面对其研究现状及发展动态予以综述。综合分析得出DEMATEL理论需要进一步探究的主要方向为：系统层次结构与DEMATEL分析方法的综合集成与有机契合,符合现实决策情境的多专家差异标度和复合标度,从反映系统动态性、非线性特征的因素之间的相互影响过程深入分析DEMATEL自依赖关系,以及有效解决中心度与原因度指标的内在属性关联问题,考虑群组专家交互的DEMATEL分析方法等方面。

关键词: 决策试行与评价实验室方法（DEMATEL）, 复杂系统, 因素分析

Abstract:

At present, in the face of severe and complex international COVID-19 and the world economic situation, the problems faced by management decision-making are becoming increasingly complex. Therefore, the factor correlation analysis for complex issues is essential for managers to recognize the core of complex things and grasp the main contradictions of things to solve effectively complex social and economic problems. The decision-making trial and evaluation laboratory (DEMATEL), as an effective tool for analyzing the relationship between complex system factors, has received extensive attention from scholars at home and abroad in recent years. Through a systematic study of the relevant literature, the current status and development of DEMATEL are reviewed in the logical order of its operation from five aspects: system structure, evaluation scale, self-dependence among factors, determination of indicators of centrality and causality, and identification of key factors. A comprehensive analysis shows that the main directions of DEMATEL theory needed to be further explored are: the comprehensive integration and organic fit between system hierarchy and DEMATEL analysis methods, the multi-expert differential scale and composite scale in line with the realistic decision-making situation, the in-depth analysis of DEMATEL self-dependency from the interaction process between factors reflecting the dynamic and non-linear characteristics of the system, and the effective solution of the problem of correlating the intrinsic properties of centrality and causality indicators, and the DEMATEL analysis method that considers the interaction of group experts.

Key words: decision-making trial and evaluation laboratory (DEMATEL), complex systems, factor analysis

中图分类号:

C934
TP18

孙永河, 黄子航, 李阳. DEMATEL复杂因素分析算法最新进展综述[J]. 计算机科学与探索, 2022, 16(3): 541-551.

SUN Yonghe, HUANG Zihang, LI Yang. Review of State of the Art on DEMATEL Algorithms for Complex Factor Analysis[J]. Journal of Frontiers of Computer Science and Technology, 2022, 16(3): 541-551.

图/表 3

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标度类型	定量信息表达方式	语言术语集粒度	相关典型文献
点估计值语言标度	非负整数(0, 1, 2)	3	[16]
	非负整数(0, 1, 2, 3)	4	[8]
	非负整数(0, 1, 2, 3, 4)	5	[4, 18]
	非负整数(1, 2, 3, 4, 5)	5	[33]
	非负整数(0, 1, …, N)	N+1	[28]
	区间数	5	[34]
模糊语言标度	三角模糊数	5	[9, 13, 35-36]
		6	[37]
		11	[29]
	直觉模糊数	5	[38-40]
	三元模糊数	5	[10, 41]
	三角直觉模糊数	5	[42]
	毕达哥拉斯模糊数	7	[14]
	区间值犹豫模糊数	未阐述	[25]
	区间值直觉模糊数	5	[17]
	区间二型模糊数	7	[38]
灰色语言标度	灰数	5	[5, 11, 43]
灰色语言标度	灰数	6	[5, 44]
Z-Number语言标度	Z-Numbers	(7, 5)	[45]
二维不确定语言标度	二维不确定语言评价值	(7, 5)	[45]
中智集语言标度	单值中智数	5	[24]

标度类型	定量信息表达方式	语言术语集粒度	相关典型文献
点估计值语言标度	非负整数(0, 1, 2)	3	[16]
	非负整数(0, 1, 2, 3)	4	[8]
	非负整数(0, 1, 2, 3, 4)	5	[4, 18]
	非负整数(1, 2, 3, 4, 5)	5	[33]
	非负整数(0, 1, …, N)	N+1	[28]
	区间数	5	[34]
模糊语言标度	三角模糊数	5	[9, 13, 35-36]
		6	[37]
		11	[29]
	直觉模糊数	5	[38-40]
	三元模糊数	5	[10, 41]
	三角直觉模糊数	5	[42]
	毕达哥拉斯模糊数	7	[14]
	区间值犹豫模糊数	未阐述	[25]
	区间值直觉模糊数	5	[17]
	区间二型模糊数	7	[38]
灰色语言标度	灰数	5	[5, 11, 43]
灰色语言标度	灰数	6	[5, 44]
Z-Number语言标度	Z-Numbers	(7, 5)	[45]
二维不确定语言标度	二维不确定语言评价值	(7, 5)	[45]
中智集语言标度	单值中智数	5	[24]

DEMATEL复杂因素分析算法最新进展综述

Review of State of the Art on DEMATEL Algorithms for Complex Factor Analysis

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