Performance optimization of electricity distribution units with random variations

This paper presents an approach based on Stochastic Data Envelopment Analysis (SDEA) for evaluating of shaping factors for performance assessment of electricity distribution units. This approach is applied to assessment of Iranian distribution units from 2001 to 2011. There are usually incomplete and stochastic data or lack of data with respect to electricity distribution companies. So, in this paper a stochastic DEA approach is used with respect to the set of comprehensive indicators to evaluate electricity distribution units. Due to lack of information about some parameters, theory of uncertainty is imported to model. The best of electricity distribution unit is selected with respect to efficiency score in an uncertainty environment. Also, SDEA model is performed for each input separately to identify the most important shaping factor by comparing the results of efficiency with SDEA model.