A Data Envelopment Analysis Model with Interval Data Using TOPSIS Technique

Data envelopment analysis (DEA) is a methodology for assessing the performances of a group of decision-making units (DMUs) that utilize multiple inputs to produce multiple outputs. This paper introduces two virtual DMUs called ideal DMU and anti-ideal DMU into the interval DEA. The resultant interval DEA models are, respectively, referred to as the interval DEA with ideal and anti-ideal DMUs. One evaluates DMUs from the viewpoint of the optimistic efficiency, while the other evaluates them from the perspective of the pessimistic efficiency. The two distinctive interval efficiencies are combined to form a comprehensive index called the relative closeness to the ideal DMU just like the well-known technique for order preference by similarity to ideal solution approach in multiple attribute decision making. The relative closeness index is then used as the evidence of overall assessment of each DMU, based on which an overall ranking for all the DMUs can be obtained. We also present an example on evaluating the performance of twenty bank branches which shows that the proposed interval DEA approach is a simple, efficient, and practical method for performance measurement in real-life situations.