نازیلا آقایی

The classic overall profit needs precise information of inputs, outputs, inputs and outputs price vectors. In real word, all data are not certain. Therefore, in this case, stochastic and fuzzy methods use for measuring overall profit efficiency. These methods require more information about the data such as probability distribution function or data membership function, which in some cases may not have sufficient information to estimate them, and only we have knowledge about the parameters so that they change in a convex space that is closed and bounded. Therefore, in this paper, we consider a budget uncertainty model in the robust optimization problem that able to adjust the conservative degree. The robust model by the input and output price vectors is proposed to compute overall profit efficiency measure. To illustrate the application of the proposed method, a numerical example is presented and the results show that the robust overall efficiency of the decision making units is higher than the optimistic model.

Cross efficiency is one of the useful methods for ranking of decision making units (DMUs) in data envelopment analysis (DEA). Since the optimal solutions of inputs and outputs weights are not unique so the selection of them are not simple and the ranks of DMUs can be changed by the difference weights. Thus, in this paper, we introduce a method for ranking of DMUs which does not have a unique problem. In the real life, the outputs can be shown as desirable and undesirable outputs. So it is important to provide models for the ranking of DMUs in present of desirable and undesirable outputs. The classic DEA models deals with certain data. But, in the real word, all data are not necessarily certain. For solve of this problem, we present a new method that compute the ranks of all DMUs by uncertain data and calculate the lower and upper bounds for the ranks of DMUs. Finally, the results of a simple example are given.