A Fuzzy Multi-Objective Multi-Period Common Weight Network DEA Model to Measure the Environmental Efficiency of Iran's Oil Refineries

In this paper, a methodology is proposed to measure the efficiency of national energy sector in IRAN. The technical and environmental performance of the oil refineries in IRAN as a major producer of energy and fuel are evaluated based on data from years 2010 to 2013. In this study, a fuzzy multi-objective multi-period common weight network data envelopment analysis approach is proposed and customized to evaluate the performance of oil refineries. A certain scenario, called food-production in which a refinery is assumed as a decision making unit (DMU) consuming inputs to produce outputs, is considered to evaluate the technical and environmental performance in presence of undesirable outputs. The main contribution of this study are summarized as: (1) Proposing a multiobjective common weight DEA model in order to determine the weights of inputs and outputs in a single run; (2) Calculating the long term efficiency scores during a multiple-periods of planning incorporating dynamic nature of inputs and outputs; (3) Handling a compromise solution using fuzzy mathematical programming to address multi-objective mathematical programming; (4) Proposing a linear mathematical programming to achieve the global optimum solutions; (5) Enhancing the discrimination power of the DEA models; (6) Reducing the computational time of modeling and solution procedure; (7) incorporating effective criteria in the modeling procedure. The analysis of case study presents the efficacy and applicability of proposed method in comparison with existing classic models