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

  • S.I. : Integrated Uncertainty in Knowledge Modelling & Decision Making 2018
  • Published:
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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.

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Acknowledgements

This work was partly supported by the National Natural Science Foundation of China (NSFC) under Grant 71971039, Grant 71501023 and Grant 71771034, the Funds for Creative Research Groups of China under Grant 71421001, the Key Program of the NSFC under Grant 71731003, the Scientific and Technological Innovation Foundation of Dalian under Grant 2018J11CY009 and Grant 2018JQ69, and the Research Funds for Young Scholars from the Education Department of Liaoning Province under Grant LN2017QN027 and the Fundamental Research Funds for the Central Universities under Grant DUT17RC(4)11.

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Authors and Affiliations

  1. Institute of Systems Engineering, Dalian University of Technology, Dalian, 116024, Liaoning, People’s Republic of China

    Zhen Zhang

  2. School of Economics and Management, Dalian University of Technology, Dalian, 116024, People’s Republic of China

    Wenyu Yu & Qiuyan Zhong

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  1. Wenyu Yu
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  2. Zhen Zhang
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Correspondence to Zhen Zhang.

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Yu, W., Zhang, Z. & Zhong, Q. Consensus reaching for MAGDM with multi-granular hesitant fuzzy linguistic term sets: a minimum adjustment-based approach. Ann Oper Res 300, 443–466 (2021). https://doi.org/10.1007/s10479-019-03432-7

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