A new uncertain DEA model for evaluation of scientific research personnel

Data envelopment analysis (DEA) has become an accepted tool for assessing efficiency in a wide range of cases since it was first proposed in 1978. However, traditional DEA models need accurate inputs and outputs, which can't be obtained or measured in many practical cases. This paper will apply DEA into uncertain environment, and propose a new DEA model with uncertain inputs and outputs based on uncertain theory. Furthermore, the uncertainty theory is utilized to convert the new uncertain DEA model into an equivalent deterministic model for simplification. Finally, this new uncertain DEA model is applied to the evaluation of scientific research personnel to illustrate the effectiveness.