A fully ranking method in imprecise DEA with common weights

In this paper, we present a fully ranking method to evaluate Decision Making Units (DMUs) with interval data. we use common set of weights methodology in DEA with interval data for a fair and reasonable ranking of performance of DMUs. An Interval efficiency is associated with each DMU based upon the obtained Common Set of Weights (CSW). The ranking criterion is sensible for a logical assessment of performance of units under the same condition. Throughout the ranking procedure, only one linear programming is solved. Our method is implemented on a real data set and another method is also run for comparison the results.