Abstract
Flexibility in selecting the weights of inputs and outputs in data envelopment analysis models and uncertainty associated with the data might lead to unreliable efficiency scores. In this paper, to avoid these problems, first, we discuss robust Charnes, Cooper, Rhodes (CCR) model under Bertsimas and Sim approach. Then, the robust CCR solutions are used to find robust common set of weights under norm-1 and Bertsimas and Sim approach. Finally, on two numerical real-world examples, the performance of the proposed approach is compared by a similar recent approach from the literature to show the advantages of the new method and its applicability.