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arXiv · 2002.12362

Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach

Sandra Benítez-Peña·Peter Bogetoft·Dolores Romero Morales
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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.

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Sandra Benítez-Peña, Peter Bogetoft, Dolores Romero Morales. 2020-02-27. Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach. https://doi.org/10.1016/j.omega.2019.05.004

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