A hesitant fuzzy multiple attribute group decision making approach based on TOPSIS for parts supplier selection

This paper investigates multiple attribute group decision making (MAGDM) with hesitant fuzzy preference information, which is a significantly import issue to be deeply studied in management and industrial engineering. Firstly, simultaneously considering optimistic and pessimistic attitudinal preference information, an improved distance measure for hesitant fuzzy set is defined. Then, utilizing the newly defined distance measure, a hesitant fuzzy multiple attribute group decision making approach based on TOPSIS method is constructed, which can effectively avoid high complexity of aggregating hesitant fuzzy information in traditional methods. Further, an application study on parts supplier selection has verified the practically and effectiveness of developed methods.