DSmT-Based Group DEMATEL Method with Reaching Consensus
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The decision-making trial and evaluation laboratory (DEMATEL) method employs expert assessments expressed by crisp values to construct a group initial direct-relation (IDR) matrix. However, it tends to be a low-precision expression, especially in complex practical problems. Although significant efforts have been made to improve the DEMATEL method, these improvements tend to neglect individual characteristics and group consensus, resulting in unconvincing decision results. This study provides a Dezert–Smarandache theory-based group DEMATEL method with reaching consensus. In order to reasonably determine the group IDR matrix, basic belief assignment function is employed to extract expert assessments and the proportional conflict redistribution rule no.5 of DSmT is employed to make fusion to derive the temporary group IDR matrix. Moreover, the consensus measures at both expert level and pair-factors level are calculated to determine whether the acceptable consensus level has been reached or not. If the required consensus level is not reached, a feedback mechanism will be activated to help experts reach a consensus. A consensus group IDR matrix for the group DEMATEL can be obtained with the help of feedback mechanism, based on which an algorithm is summarized for the proposed method to identify major factors in a complex system. Finally, numerical comparison and discussion are introduced to verify the effectiveness and applicability of the proposed method and algorithm.
KeywordsDEMATEL Group decision making Dezert–Smarandache theory (DSmT) Consensus reaching Evidence distance Expert weight
This research was supported by the Major Program of National Social Science Foundation of China under Grant No. 18ZDA055, the Key Program of National Social Science Fund of China under Grant No. 16AJL007, the National Natural Science Foundation of China (NSFC) under Grant Nos. 71874167, 71804170, 71901199 and 71462022, and the Special Funds of Taishan Scholars Project of Shandong Province under Grant No. tsqn20171205.
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