Single Model Approach to Evaluate Optimistic and Pessimistic Congestion in Fuzzy Data Envelopment Analysis

Data Envelopment Analysis (DEA) is an almost new data oriented approach for measuring the performance of series of homogenous entities named Decision Making Unit (DMU) with the ability to alter multiple inputs into multiple outputs. This article investigates the development of congestion model with regard to fuzzy input and output. Also, a new concept called as optimistic and pessimistic are introduced for congestion model. To create this concept, the upper and lower bound of efficiency, outputs and inputs are required. This concept is provided with alpha-cut approach in fuzzy data envelopment analysis (FDEA). In order to evaluate the efficiency of given models, data of some universities of Iran are applied. The results reveal the proper validity of proposed model.