Consensus reaching process with noncooperative behaviors in large-scale group social network environment

Abstract

Large-scale group decision-making (LSGDM) problems have drawn general attention from scholars. The distribution linguistic preference relation (DLPR) is a flexible and practical tool to describe the preferences of decision makers (DMs) in the decision-making process. Opinion conflict is inevitable among large-scale DMs due to self-interest and individual perception. Thus, it is essential to establish a consensus reaching process (CRP), but there may be non-cooperative behaviors for DMs when they are required to accept the opinions adjustment. As the social network becomes more ubiquitous, moreover, the trust relationship among decision members has implications for the consensus reaching process. Hence, this study proposes a new consensus model that manages non-cooperative behaviors from the cooperative degree, trust relationship, and individual self-confidence level three aspects, and discusses the specific influence of these factors on the penalty for non-cooperative behaviors. In addition, hesitancy-based similarity measure of linguistic distributed assessment is proposed for clustering and measuring consensus level. Finally, a numerical example of a price hearing system demonstrates the feasibility and efficacy of the proposed method, and a comparative analysis illustrates its features and advantages.