EVALUATION AND RANKING OF DMUS BY USING INTERVAL EFFICIENCIES ON FUZZY DATA

Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. Unfortunately, the existing DEA models are limited to crisp parameters. To deal with data uncertainty in real-life problems, the notion of fuzziness has been often utilizing in the context of decision sciences context such as DEA. In this paper, we propose a fuzzy DEA model where the inputs and outputs are fuzzy and we apply a linear ranking function to obtain the interval efficiency. First, we create a fuzzy anti-ideal DMU and the best relative efficiency of this virtual DMU is measured. Second, we propose a pair of the models to obtain the upper and lower bounds of the efficiency. Finally, we use a method to rank the interval efficiency of the DMUs

EVALUATION AND RANKING OF DMUS BY USING INTERVAL EFFICIENCIES ON FUZZY DATA Keywords:

Data Envelopment Analysis , Fuzzy data , Interval Efficiency