A hierarchical consensus reaching model based on trust and uncertain degree for heterogeneous large-scale group decision making and application to product design

Nowadays, due to the fierce market competition, companies in many industries needs to constantly introduce new products. How to select an optimal product design has become a widespread problem. Due to complexity and a large number of decision makers (DMs) participating in decision-making, this paper formulates the product design selection as a type of large-scale group decision making (LSGDM). Because of the differences in occupation, purpose, and personality of DMs in LSGDM, they prefer to provide evaluations by heterogeneous representation formats. A hierarchical consensus reaching model is developed based on trust and uncertain degree for heterogeneous LSGDM. Firstly, the heterogeneous evaluations of DMs are transformed into fuzzy preference relations (FPRs) through possibility degrees. According to trust relationships and original evaluations of DMs, the trust and uncertain degrees of DMs are extracted considering the inherent personalities and psychological traits implied in the heterogeneous evaluations. Thereby, this paper (1) constructs an optimization model to determine the weights of DMs and (2) divides the feedback mechanism into four cases. Case study of product design selection is provided to illustrate the applicability of the proposed model. Several comparisons validate the advantages of the proposed model.