New data envelopment analysis (DEA) model to determine the most efficient decision making unit (DMU) considering imprecise data

Sohrabi and Nalchigar (1389), proposed a new data envelopment analysis (DEA) model to identify the most efficient decision making unit (DMU) considering imprecise data. In this paper it will be shown that the proposed model is not able to determine the most efficient DMU and the model randomly introduced an efficient DMU as the most efficient. It will be shown also that the proposed model to determine the most efficient DMU in the case of variable return to scale have the same drawback and also may be infeasible in some cases. To overcome the drawbacks new integrated models will be presented. In addition, to find and rank other most efficient DMUs an algorithm will be proposed. By using the presented model in the paper decision maker can find the most efficient DMU by solving only one linear integer programming. Applicability of proposed model is indicated by using imprecise data set includes specifications of 18 suppliers.