Dual consistency-driven group decision making method based on fuzzy preference relation

Consistency testing and adjustment of preference relations are prerequisites for group decision making; the forced integration of preference relations without consensus may lead to misleading decisions. To address this issue, following the principle of minimal information loss in consensus reaching, we propose a dual consistency driven group decision making method based on the fuzzy preference relation between individuals and groups. First, a bidirectional adjustment amount is introduced in the individual consistency process to avoid unidirectional expansion or reduction of the degree of fuzzy preference. Second, considering that the adjustment of fuzzy preference information in the process of group negotiation will change the weight of expert, a goal programming based on the dual adjustment of dynamic weights and preference information is constructed, which can solve the problem of contradictory order values before and after the expert weights adjustment and improve the level of group consensus and the efficiency of group consensus reaching. Finally, the effectiveness of the proposed methodology through an analysis of case studies is verified.