Multi-criteria decision-making based on hesitant fuzzy linguistic term sets: An outranking approach

Hesitant fuzzy linguistic term sets (HFLTSs) are introduced to express the hesitance existing in linguistic evaluation as clearly as possible. However, most existing methods using HFLTSs simply rely on the labels or intervals of linguistic terms, which may lead to information distortion and/or loss. To avoid this problem, linguistic scale functions are employed in this paper to conduct the transformation between qualitative information and quantitative data. Moreover, the directional Hausdorff distance, which uses HFLTSs, is also proposed and the dominance relations are subsequently defined using this distance. An outranking approach, similar to the ELECTRE method, is constructed for ranking alternatives in multi-criteria decision-making (MCDM) problems, and the approach is demonstrated using a numerical example related to supply chain management. Because of the inherent features of the directional Hausdorff distance and the defined dominance relations, this approach can effectively and efficiently overcome the hidden drawbacks that may hamper the use of HFLTSs. Finally, the accuracy and effectiveness of the proposed approach is further tested through sensitivity and comparative analyses.