scholarly journals Group Decision-making Method Based on Grey Relational Analysis and Evidence Theory for XAI

Author(s):  
Decai Sun ◽  
Dang Luo

Abstract For the uncertainty and complexity ingroup decision making and the differences of decision makers’ reliabilities, a group decision making method based on grey relational analysis and evidence theory is proposed. Combining grey relational analysis with evidence theory, a novel decision-making method extracting the degree of ignorance for individual decision makers’ information and constructing the Mass function is presented based on the comprehensive grey relational analysis (CGRA) method. We should also address how AI systems make their black box decisions, which calls for research into Explainable AI (XAI) by pursuing reverse engineering and self-explainability in AI. Considering the differences of decision makers’ reliabilities, the Mass function is modified by the evidence weight, and the group decision information is fused by the Dempster’s combination rule. On this basis, the Mass function is further transformed into the probability by the Pignistic probability transformation, which issued for ranking analysis of group decision making. Finally, the proposed method is applied to the green supplier selection, and the comparative analysis is further performed to verify the rationality and effectiveness of the proposed method.

2021 ◽  
Vol 41 (2) ◽  
pp. 3783-3795
Author(s):  
Shanshan Zhang ◽  
Hui Gao ◽  
Guiwu Wei ◽  
Xudong Chen

The Multi-attribute group decision making (MAGDM) problem is an interesting everyday problem full of complexity and ambiguity. As an extended form of fuzzy sets, intuitionistic fuzzy sets (IFSs) can provide decision-makers (DMs) with a wider range of preferences for MAGDM. The grey relational analysis (GRA) is an effective method for dealing with MAGDM problems. However, in view of the incomplete and asymmetric information and the influence of DMs’ psychological factors on the decision result, we develop a new model that GRA method based on cumulative prospect theory (CPT) under the intuitionistic fuzzy environment. Moreover, the weight of attribute is calculated by entropy weight, so as to distinguish the importance level of attributes, which greatly improves the credibility of the selected scheme. simultaneously, the proposed method is used to the selection of optimal green suppliers for testifying the availability of this new model and the final comparison between this new method and the existing methods further verify the reliability. In addition, the proposed method provides some references for other selection problems.


2021 ◽  
pp. 1-15
Author(s):  
Limei Hu ◽  
Chunqiao Tan ◽  
Hepu Deng

With the changing business environment and the active participation of various stakeholders in the decision making process, it plays an increasingly important role to the weight of decision makers and the preference information given by decision makers. This paper presents a novel approach for group decision making under uncertainty with the involvement of the third-party evaluator in the decision making process. Recognizing the challenge in adequately determining the weight of decision makers in group decision making, the evidence theory is appropriately used with the involvement of the third-party evaluator. To effectively model the uncertainty and imprecision in the decision making process, fuzzy preference relations are used for better representing the subjective assessment of individual decision makers. To adequately determine the ranking of available alternatives, the logarithmic least square method is applied for appropriately aggregating the fuzzy preference relation of individual decision makers. A group consensus index is developed for facilitating consensus building in group decision making. This leads to better group decisions being made. A real-world application is presented that shows the proposed approach is effective in solving group decision making problems under uncertainty.


2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.


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