A consensus model for hesitant fuzzy linguistic group decision-making in the framework of Dempster–Shafer evidence theory

Abstract

In group decision-making (GDM), a consensus building process (CRP) is necessary to improve the level of consensus within the group. This paper develops a new CRP model for GDM problems with hesitant fuzzy linguistic term sets (HFLTSs), which also considers the reliability of experts. Firstly, we present the calculation of expert reliability by measuring the hesitancy degree and similarity degree, simultaneously. Next, we propose an approach to generate group opinions based on the reliability of experts within the framework of the Dempster–Shafer evidence theory (DSET). In this way, the original individual opinions can be retained well and the discourse power of experts with higher reliability but lower weights can be strengthened. Further, the reliability is introduced to build a new feedback mechanism that provides experts with explicit advice during the consensus reaching process. Subsequently, a new CRP algorithm for hesitant fuzzy linguistic GDM (HFLGDM) problems is proposed to help the group achieve consensus. A practical case study is utilized to illustrate the application of the proposed algorithm. Finally, we conduct a comparison experiment to verify the advantages of the proposed CRP algorithm.