Abstract
In many situations, a common revenue or benefit must be distributed amongst a set of beneficiary decision making units (DMUs) with imprecise data represented by fuzzy or stochastic data. A fair revenue distribution can certainly increase the motivation of DMUs for improving their performances. The share of each DMU must be determined according to its eligibility. To access a fair distribution, we use an optimistic–pessimistic approach of data envelopment analysis which considers both weaknesses and strengths of DMUs. This method determines the share of each DMU according to a combination of its minimum and maximum possible shares which are respectively obtained under the pessimistic and optimistic approaches.
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