Presenting a Robust Network Data Envelopment Analysis Model with Undesirable Output to Evaluate Efficiency in Conditions of Uncertainty

It is important to consider the uncertainty in the data, and know how to deal with it when evaluating efficiency by using data envelopment analysis; since the presence of small deviations in the data can lead to significant changes in efficiency results. However, in the real world in many cases, the data is uncertain. The purpose of this paper is to present a robust model of network data envelopment analysis in order to measure efficiency in the presence of uncertainty. A new approach to evaluate efficiency for network data envelopment analysis is first proposed. The definitive method presented in this paper involves undesirable output and can be used for different structures in network data envelopment analysis. Next by extending, the proposed model for uncertain data a new robust network data envelopment analysis model is presented for three-stage networks with undesirable outputs. The proposed model is used to evaluate the electricity regions of Iran. These regions involve a three-step process with undesirable outputs in some stages. The results show that the proposed model achieves the efficiency of the steps and the total efficiency simultaneously. In addition, the overall network efficiency score can be a basis to rank the areas.Originality/Value: The proposed model is a new model in the field of efficiency evaluation in conditions of uncertainty and having an undesirable output.