A Confidence and Conflict-Based Consensus Reaching Process for Large-Scale Group Decision-Making Problems with Intuitionistic Fuzzy Representations

With the development of social democracy, the public begins to participate in large-scale group decision-making (LSGDM) events that have a significant impact on their personal interests. However, the participation of the public with insufficient expertise will cause much hesitancy in the evaluations of decision makers (DMs), which can be captured by intuitionistic fuzzy sets. Meanwhile, due to the increment in the number of DMs, the cost of consensus-reaching processes (CRPs), which are utilized to help DMs reach a consensus, is getting higher and higher. In order to improve the efficiency of the CRP, this article presents a confidence and conflict-based CRP (CC-CRP) for LSGDM events with intuitionistic fuzzy representations. In the proposed model, according to the hesitancy of the DMs' intuitionistic fuzzy evaluations, an objective method is first developed to calculate the confidence level of DMs that does not require any extra information. Then, a 3-D clustering method is designed by considering the type of conflict, the degree of conflict, and the confidence level of DMs. After this, an efficiency rate of modification is defined to select DMs who will be persuaded first to adjust their evaluations with recommendation plans generated by a specific optimal method. Finally, according to the clustering process results, different CC-CRP management methods will apply to DMs with different attributes. An illustrative example and several experiments are reported to provide evidence that the proposed model is feasible and effective.