Efficiency Evaluation and Ranking DMUs in the Presence of Interval Data with Stochastic Bounds

Due to the existence of uncertainty, DEA sometimes faces the situation of imprecise data, especially when a set of DMUs contain missing data, ordinal data, interval data, stochasticdata, or fuzzy data. Therefore, how to evaluate the efficiency of a set of DMUs in interval environments is a problem worth studying. In this paper, we discussed the new method forevaluation and ranking interval data with stochastic bounds. The approach is illustrated by several numerical examples.

Keywords:

Data envelopment analysis (DEA) , Decision making unit (DMU) , Efficiency , Ranking , Interval data , stochastic bounds