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

  • Wenyu Yu
  • Zhen ZhangEmail author
  • Qiuyan Zhong
S.I. : Integrated Uncertainty in Knowledge Modelling & Decision Making 2018
  • 40 Downloads

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 

Notes

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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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Systems EngineeringDalian University of TechnologyDalianPeople’s Republic of China
  2. 2.School of Economics and ManagementDalian University of TechnologyDalianPeople’s Republic of China

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