Two-Stage DEA with Fuzzy Data

Data envelopment analysis is a nonparametric method evaluating efficiency of DMUs using mathematical programming. In most standard DEA models, the status of each measure is clearly known as either input or output. Kao and Hwang (2008) introduce a DEA approach for evaluating the efficiency of DMUs with two stages. The first stage uses inputs to produce outputs which become the inputs to the second stage. The first stage outputs named as intermediate measures. The second stage then uses these intermediate measures to produce outputs. In the standard DEA models all the data are crisp but there are many problems in the real life that can be uncertain. Thus, in this paper, two-stage fuzzy DEA model with a symmetrical triangular fuzzy number is presented. The basic idea is to change the fuzzy model into crisp linear programming by using α-cut approach. Finally, a numerical example is presented to highlight the application of this method.