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Large-scale group hierarchical DEMATEL method with automatic consensus reaching.

Authors :
Du, Yuan-Wei
Shen, Xin-Lu
Source :
Information Fusion. Aug2024, Vol. 108, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

• BPA function is used to extract experts' opinions at different levels of subsystems. • Experts are divided into clusters to coordinate different expert opinions. • Intrasubgroup and intersubgroup consensus are designed in hierarchical DEMATEL. • Automatic correction mechanism is used to enhance the efficiency of consensus-reaching. • Large-scale group hierarchical DEMATEL method with consensus reaching are proposed. Decision-making trial and evaluation laboratory (DEMATEL) is widely used because of its ability to effectively analyze nonlinear relationships between factors in complex systems. With the increasing complexity of decision-making problems, large-scale group decision-making (LSGDM) has become the norm. Most existing DEMATEL methods are only suitable for small-scale groups and simple systems. This study, therefore, proposes a large-scale group hierarchical DEMATEL method that considers consensus reaching. The DEMATEL method for LSGDM faces three challenges: large differences in knowledge structures, difficulty coordinating expert opinions, and slow group-consensus convergence. To address these challenges, first, we use hierarchical decomposition to decompose the complex system into simple systems with different levels to reduce the difficulty of decision-making in complex systems. Second, considering the limitations of expert knowledge and experience, we use the basic probability assignment function to extract the opinions of experts at different levels of subsystems and factors. Third, we divide experts into different clusters using K-means clustering to solve the problem of difficult expert-opinion coordination. Fourth, we design two types of consensuses (intrasubgroup and intersubgroup consensus) and an efficient new type of opinion autocorrection mechanism to solve the problem of the slow convergence of intragroup consensus and improve the efficiency of consensus reaching. Finally, we demonstrate the superiority of the proposed method through data analysis and method comparison. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15662535
Volume :
108
Database :
Academic Search Index
Journal :
Information Fusion
Publication Type :
Academic Journal
Accession number :
176811367
Full Text :
https://doi.org/10.1016/j.inffus.2024.102411