Data envelopment analysis is a nonparametric technique checking efficiency of DMUs using math programming. In conventional DEA, it has been assumed that the status of each measure is clearly known as either input or output. However in some situations, a performance measure can play input role for some DMUs and output role for others. There are different models for classifying inputs and outputs, but all of these models are with crisp data. In this paper we want to classify inputs and outputs when all of the DMUs have symmetrical triangular fuzzy inputs and outputs and flexible measures. The basic idea is to transform the fuzzy model into a crisp linear programming problem by applying an α-cut approach.Finally, a numerical example is proposed to display the application of this method.

Data envelopment analysis is a nonparametric technique checking efficiency of DMUs using math programming. Current models are just working with deterministic data. The point is that how would be ranking and checking efficiency of units if data were stochastic. In this article we will represent a method to rank decision making units with stochastic data using JAM Model of "Jahanshahloo, Mehrabian, Alirezaie" Finally a numerical example will applied to check the performance of purposed method.

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