GENERALIZED FUZZY SLACKS-BASED MEASURES OF EFFICIENCY AND ITS APPLICATIONS

Data envelopment analysis (DEA) is a mathematical approach for evaluating the efficiency of decision making units (DMUs). Additionally, slacks-based measures (SBM) of efficiency are used for direct assessment of efficiency in the presence of imprecise data with slack values. Traditional DEA models assume that all input and output data are known exactly. In many situations, however, some inputs and/or outputs take fuzzy data. Fuzzy DEA (FDEA) models emerge as another class of DEA models to account for imprecise inputs and outputs for decision making units. Although several approaches for solving fuzzy DEA models have been developed, numerous deficiencies including the a-cut approaches and types of fuzzy numbers must still be improved. Moreover, a fuzzy sample DMU (SDMU) still cannot be evaluated for the FDEA model. Therefore, the present paper proposes a generalized Fuzzy SBM (GFSBM) model which can evaluate SDMU and the traditional FSBM model. A numerical experiment is used to demonstrate and show the application of the proposed GFSBM approach.