Fusing multi-granular unbalanced hesitant fuzzy linguistic information in group decision making

Abstract

The hesitant fuzzy linguistic term set (HFLTS) is a useful tool for a decision maker to elicit hesitant fuzzy linguistic information in decision making problems. In this paper, it is proposed the concept of unbalanced HFLTS based on the unbalanced linguistic term set. To fuse unbalanced HFLTSs in decision making, the unbalanced hesitant fuzzy linguistic weighted averaging operator and the unbalanced hesitant fuzzy linguistic ordered weighted averaging operator are developed, which follow the paradigm of computing with words and aggregate a collection of unbalanced HFLTSs into an unbalanced linguistic distribution assessment to provide interpretable results for decision makers. The proposed aggregation operators are further extended to fuse multi-granular unbalanced HFLTSs and applied to deal with multi-attribute group decision making problems. Eventually, an example for investment alternative selection is provided to demonstrate the proposed aggregation operators and the decision making approach.