The classification of decision making units applying DEA-Maxmin Method with supporting Relative Closeness to Ideal Decision Making Units index

Although data envelopment analysis (DEA) is a linear programming method used for classifying decision making units (DMUs), it is less practical to compare DMUs on the same scale. In this paper, we present common weights for DMUs by applying Maxmin as one of multi criteria decision making (MCDM) techniques, thereby we will deal with improving discrimination power for selecting the efficient DMUs. Finally, via a previously reported numerical example the proposed data envelopment analysis-Maxmin (DEA-Maxmin) model is compared with that obtained by the DEA-AHP. This method supports the validity of classification based on DEA-GP which was done through that example and an index called the relative closeness (RC) to the ideal DMU (IDMU) supports both of them.