Distance-Based Multi-Criteria Group Decision-Making Approaches with Multi-Hesitant Fuzzy Linguistic Information

Jing Wang, Jian-Qiang Wang, Hong-Yu Zhang () and Xiao-Hong Chen ()
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Jing Wang: School of Business, Central South University, Changsha 410083, P. R. China†International College, Central South University of Forestry and Technology, Changsha 410004, P. R. China
Jian-Qiang Wang: School of Business, Central South University, Changsha 410083, P. R. China
Hong-Yu Zhang: School of Business, Central South University, Changsha 410083, P. R. China
Xiao-Hong Chen: School of Business, Central South University, Changsha 410083, P. R. China

International Journal of Information Technology & Decision Making (IJITDM), 2017, vol. 16, issue 04, 1069-1099

Abstract: In this paper, the distance-based multi-criteria group decision-making (MCGDM) approaches using multi-hesitant fuzzy linguistic term sets (MHFLTSs) are proposed. MHFLTSs can contain nonconsecutive and repetitive linguistic terms, so as to deal with repeated linguistic values in group decision-making. A multi-hesitant fuzzy linguistic term element (MHFLTE) can be produced by collecting the evaluation values of several decision-makers or given by one person who has uncertainty in evaluation. The corresponding set operations and comparison rules are defined and the generalized hesitant fuzzy linguistic distance for MHFLTEs is given based on the linguistic scale function. Then this distance is embedded into the TOPSIS, VIKOR and TODIM approaches for the purpose of solving multi-criteria decision-making (MCDM) problems in the context of multi-hesitant fuzzy linguistic information. With increasing concerns about deterioration in environment, organizations are obliged to carry out more environmental sustainable activities than before, such as progressive practices in green supply chain management (GSCM). Therefore, with respect to the application of MHFLTSs in GSCM, two illustrations for evaluating the related alternatives are finally provided, together with the sensitivity and comparison analysis, to show the validity and effectiveness of our proposal.

Keywords: Multi-hesitant fuzzy linguistic term sets; generalized hesitant fuzzy linguistic distance; linguistic decision-making; green supply chain management (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0219622017500213

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