  This paper proposes an integrative approach to feature (input and output)
selection in Data Envelopment Analysis (DEA). The DEA model is enriched with
zero-one decision variables modelling the selection of features, yielding a
Mixed Integer Linear Programming formulation. This single-model approach can
handle different objective functions as well as constraints to incorporate
desirable properties from the real-world application. Our approach is
illustrated on the benchmarking of electricity Distribution System Operators
(DSOs). The numerical results highlight the advantages of our single-model
approach provide to the user, in terms of making the choice of the number of
features, as well as modeling their costs and their nature.
