عنوان مقاله [English]
Data envelopment analysis measures relative efficiency of DMUs with multiple inputs and outputs, the importance of identifying efficient and inefficient DMUs and organizing inefficient DMUs have led to paying more attention to key role of data envelopment analysis, Input and output data are not always desirable and there exist a number of undesirable data which affect the efficiency. In addition, uncertainty is undeniable feature of the real world. For this purpose, in this paper, it is attempted to approach the reality by considering undesirable and fuzzy data simultaneously. Traditional DEA divides DMUs into efficient and inefficient, it is not able to rank DMUs completely, therefore, optimistic cross efficiency method is utilized to face with this defect and then the proposed multi-objective model is solved as a single-objective one applying Torabi-Hassini method. Finally, to demonstrate the efficiency and effectiveness of the model, a numerical example is used and the findings are compered.