A dynamic expert contribution-based consensus model for hesitant fuzzy group decision making with an application to water resources allocation selection

This research focuses on group decision making (GDM) under hesitant fuzzy condition. All experts (decision makers) are allowed to use hesitant fuzzy preference relations (HFPRs) to express their opinions. Subsequently, a dynamically expert contribution-based consensus model is developed for GDM with HFPRs. In the proposed method, a combination of a weight update model and a preference adjustment model is applied to consensus reaching processes (CRPs). In the weight update model, we propose to dynamically update experts’ weights according to their contributions in the CRPs. In the preference adjustment model, only the preferences which are far away from the expected values are modified, aiming to retain the experts’ original information as much as possible. Finally, the proposed model is applied to water resources allocation selection to show how it works in practice. And some comparisons and discussions are given to show the advantages of the proposed method.