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

Wenyu Yu (), Zhen Zhang () and Qiuyan Zhong ()
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Wenyu Yu: Dalian University of Technology
Zhen Zhang: Dalian University of Technology
Qiuyan Zhong: Dalian University of Technology

Annals of Operations Research, 2021, vol. 300, issue 2, No 7, 443-466

Abstract: Abstract 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.

Keywords: Group decision making; Consensus reaching; Hesitant fuzzy linguistic term set; Multi-granular linguistic information; Minimum adjustment (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s10479-019-03432-7

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