مشخصات پژوهش

Data envelopment analysis (DEA) is a powerful method for measuring the efficiency of peer decision making units (DMUs). One of the drawbacks of the traditional models is the neglect of the intermediate products or internal linking activities. Network data envelopment analysis (NDEA) concerns using the DEA technique to measure the relative efficiency of a system, taking into account its internal structure. Although a key factor in the DEA studies is the use of accurate measurement of all factors, in many cases such as release of carbon dioxide or production system, inputs and outputs are very volatile. Several methods have been proposed in order to manage data variability. When there is no historic data, consider the manufacturers intend to launch a product for the first time or to evaluate the success rate in treating specific patients whose number does not provide the sample size required by the statistical methodology, the experts can be invited to model their belief degrees. In these circumstances uncertainty theory could be an appropriate method. In this paper, a basic two stage system is evaluated under uncertain condition when we have to apply expert’s opinion.