Multiscale Group Consensus With Heterogeneous Preference Structures Based on Fuzzy Social Networks and Prospect-Regret Theory

In group decision making (GDM), multiscale information systems (MSISs) and fuzzy social networks have strong applications. In addition, decision makers (DMs) can reveal their preference information by heterogeneous preference structures (HPSs) (e.g., utility values, preference orderings, fuzzy preference relations, and multiplicative preference relations). This article aims to provide a clear perspective on the fusion process with HPSs and MSISs in GDM. Specifically, a cosine similarity measure is introduced to justify the consensus level of the opinions of DMs with various preference structures. To enhance the applicability of the proposed method, multiscale trust relations are constructed, which provide evolutionary directions for the adjustment of DMs' opinions. In addition, in order to fully consider the influence of psychological behaviors in the consensus reaching process, the minimum regret model is developed in the consensus feedback mechanism. Finally, a specific useful example is used to validate the method introduced in this article.