A Fuzzy Mathematical Programming Approach to DEA Models

Evaluating the performance of activities or organizations by traditional Data Envelopment Analysis (DEA) as efficiency frontier analysis models requires crisp input/output data. However, in real-world problems inputs and outputs are often imprecise. This study develops DEA models using imprecise data represented by fuzzy sets. An important outcome of assessing relative efficiencies within a group of Decision Making Units (DMUs) in fuzzy data envelopment analysis is to determine efficient DMUs. We find efficiency measures with fuzzy inputs and outputs via proposed model. An example using fuzzy data is presented for illustrative purposes. We apply this method in the application to the power generation sector of Iran.