A consensus model for large scale group decision making with hesitant fuzzy linguistic information and hierarchical feedback mechanism. (November 2022) - Li, Shengli; Rodríguez, Rosa M.; Wei, Cuiping; Shu, Ting
Abstract: Large scale group decision making (LSGDM) has become a hot research topic in the field of decision science. Reaching a consensus in LSGDM is more difficult and complex than the traditional group decision making (GDM). In this paper, we propose a consensus model with hierarchical feedback mechanism for LSGDM dealing with hesitant fuzzy linguistic information. According to the majority rule, the sub-groups with more members are the ones playing a key role in the consensus reaching process. So the sub-groups are divided into three categories including dominant influencer, medium level of influencer and non-influencer. Then, to keep as much information as possible, we use possibility distributed extended hesitant fuzzy linguistic term sets to represent the sub-group opinion. After that, we take into account the sub-group size and the level of togetherness of the sub-group preferences to obtain the weight of each sub-group. Furthermore, a new hierarchical feedback mechanism is developed to provide different identification rules and recommendation strategies for the sub-groups performing different profiles. Finally, an application example of water resource management is utilized to show the effectiveness of the proposed model. Highlights: We propose a consensus model with hierarchical feedback mechanism. The sub-groups are divided into three categories. Different identification and recommendation rules are provided for different sub-groups. We use possibility distributed HFLTSs to model the sub-group hesitation.