A New Hesitant Fuzzy Linguistic ORESTE Method for Hybrid Multicriteria Decision Making

The hesitant fuzzy linguistic term set (HFLTS) is an effective tool to express the experts' subjective evaluations in the processes of decision making. To solve the problem with both qualitative and quantitative criteria in the context of HFLTSs and the crisp weights of criteria being unknown, this paper proposes a new multicriteria decision making method. First, formulas are developed to convert the quantitative data into the hesitant fuzzy linguistic elements. Then, motivated by the ORESTE method, we develop a new global preference score function to aggregate the criterion weights and criterion values, both of which are expressed as hesitant fuzzy linguistic elements. To get the real relation between alternatives, three preference intensity formulas are proposed and a hesitant fuzzy linguistic indifference threshold is introduced. We establish a conflict test framework after detailed research on the threshold values. On these bases, a new hesitant fuzzy linguistic ORESTE method is developed and the calculation process of this method is described. A case study on supplier selection is then presented to illustrate the method. Finally, some comparative analyses with other methods are conducted to show the practicability and reliability of the proposed method.