Classifying Inputs and Outputs in Data Envelopment Analysis Based on TOPSIS Method and a Voting Model

In conventional data envelopment analysis, it is assumed that the input versus output status of any particular performance measure is known. In some situations, finding the status of some variables from the input or output point of view is very difficult; these variables are treated as both inputs and outputs and are called flexible measures. In this paper, using the TOPSIS method, and also using a voting model, the status of such a variable will be determined, and the results obtained will be employed to evaluate the efficiency of homogeneous decision making units. Note that all the models used in this paper are linear programming models and there is no need to solve any integer programming model. The approach is illustrated by an example.