Quantum mechanics

Algorithm

Linguistics

Philosophy

Theory of computation

Statistics

Telecommunications

Envelope (radar)

Data mining

Computer science

Physics

Operations research

Preference

Mathematics

Political science

Fuzzy logic

Group decision-making

Artificial intelligence

Measure (data warehouse)

Term (time)

Radar

Annals of Operations Research

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.

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