An integrated method for shared power bank supplier selection based on linguistic hesitant fuzzy multi-criteria group decision making

Abstract

With the increasing number of smartphone users, the potential of the shared power bank industry is increasing. The shared power bank supplier selection can be regarded as a multi-criteria group decision making (MCGDM) problem with linguistic hesitant fuzzy (LHF) sets (LHFSs). This paper proposes a linguistic hesitant fuzzy MCGDM method based on the MULITMOORA (Multi-Objective Optimization on basis of a Ratio Analysis plus the Full Multiplicative form), the BWM (best and worst method), and the prospect theory (PT). Firstly, a new comparison approach of LHFSs is proposed. We propose the LHF Bonferroni mean (BM), the LHF weighted BM and the LHF generalized weighted BM (LHFGWBM) operators. The decision makers’ weights are acquired via a tri-objective optimization model. This paper extends the BWM to obtain the subjective criteria weights and employs the entropy to acquire the objective criteria weights. The comprehensive criteria weights are generated by the Jenson-Shannon divergence. The LHFGWBM operator is used to generate the collective decision matrix. The comprehensive prospect value decision matrix is obtained. Then, we propose the PT-based MULTIMOORA method for LHF MCGDM. An example of shared power bank supplier selection is used to show the superiorities of the proposed LHF MCGDM method.