A dynamic trust network and influence measure-based consensus model for large-scale group decision-making with incomplete intuitionistic fuzzy preference relations

The proliferation of network technology has led to the focus on large-scale group decision-making (LSGDM).This study establishes a consensus model by constructing dynamic trust networks to address LSGDM problems in an incomplete intuitionistic fuzzy environment. More specifically, an approach to measuring the influence of decision-makers (DMs) is presented by combining opinion similarity and trust relationships among DMs. Subsequently, an estimation method for missing values in incomplete intuitionistic fuzzy preference relations (IFPRs) is given by considering the reference risk. With these discussions, a dynamic update method of the trust network is proposed to determine the real-time weights of DMs and subgroups. In addition, a two-stage feedback adjustment mechanism for individuals and subgroups is designed. In the end, a numerical example and comparative analysis are provided to illustrate the feasibility and superiority of the proposed method.