Allocating fixed resources for DMUs with interval data

Conventional DEA models tend to allocate the fixed resources multiple decision-making units (DMUs) and treat allocated resource as an extra input for every single DMU. However, existing allocation (DEA-RA) methods are applicable exclusively DMUs with exact values of inputs outputs. A lack precision or output data DMUs, such interval data, would cause a failure DMUs. In order resolve this problem, three DEA-RA proposed in paper different scenarios decision-making. All based on set common weights. Finally, empirically tested validated through examples. As revealed by results, our capable providing more fair practical initial scheme decision makers.