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Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach

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  • Benítez-Peña, Sandra
  • Bogetoft, Peter
  • Romero Morales, Dolores

Abstract

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.

Suggested Citation

  • Benítez-Peña, Sandra & Bogetoft, Peter & Romero Morales, Dolores, 2020. "Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach," Omega, Elsevier, vol. 96(C).
    • Handle: RePEc:eee:jomega:v:96:y:2020:i:c:s0305048318312131
    DOI: 10.1016/j.omega.2019.05.004
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