Ranking of DMUs on Interval Data by Imposing a Minimum Weight Restriction in DEA

In this paper, we present a method for ranking decision making units (DMUs) with interval data in data envelopment analysis that is different from the other methods. In this method we use a new pair of interval DEA models that are constructed on the basis of interval arithmetic, which differ from the existing DEA models that work with interval data in fact it is a linear CCR model without a need for extra variable alternations and uses a fixed and unified production frontier (i.e. the same constraint set) to measure the efficiencies of decision making units (DMUs) with interval input and output data. This methodology exerts an appropriate minimum weight restriction on all input and output weights which is called maxmin weight. New linear programming (LP) model constructs proportion with each efficient unit for determining maximin weight. Choosing a maxmin weight, all efficient units put in order as fully or partially. One numerical example is inspected using the proposed ranking methodology to illustrate its ability in discriminating between DEA efficient unit with interval data.