Uncertain Data Envelopment Analysis

Using the framework of robust optimization, we propose an uncertain DEA (uDEA) model for which an optimal solution determines (1) the maximum possible efficiency score of a DMU over all permissible uncertainties, and (2) the minimal amount of uncertainty that is required to achieve this efficiency score. We show that the uDEA model is a proper generalization of traditional DEA and provide a first-order algorithm to solve the uDEA model with ellipsoidal uncertainty sets. Finally, we present a case study applying uDEA to the problem of deciding efficiency of radiotherapy treatments.