Consensus reaching for MAGDM with multi-granular hesitant fuzzy linguistic term sets: a minimum adjustment-based approach

Due to the uncertainty of decision environment and differences of decision makers' culture and knowledge background, multi-granular HFLTSs are usually elicited by decision makers in a multi-attribute group decision making (MAGDM) problem. In this paper, a novel consensus model is developed for MAGDM based on multi-granular HFLTSs. First, it is defined the group consensus measure based on the fuzzy envelope of multi-granular HFLTSs. Afterwards, an optimization model which aims to minimize the overall adjustment amount of decision makers' preference is established. Based on the model, an iterative algorithm is devised to help decision makers reach consensus in MAGDM with multi-granular HFLTSs. Numerical results demonstrate the characteristics of the proposed consensus model.

Automated summary

A novel consensus model based on multi-granular HFLTSs is proposed in this paper, aiming to help decision makers reach consensus in multi-attribute group decision making. The model defines a consensus measure and an optimization model to minimize decision makers' preference adjustment, with numerical results demonstrating its characteristics.