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Ensemble learning for operations research and business analytics

Author

Listed:
  • Koen W. De Bock

    (Audencia Business School)

  • Matthias Bogaert

    (Ghent University
    FlandersMake@UGent—Corelab CVAMO)

  • Philippe Jardin

    (Edhec Business School)

Abstract

This paper introduces the special issue on Ensemble Learning for Operations Research and Business Analytics. Its main purpose is to provide summaries for the 14 contributing research papers that were accepted for inclusion in this special issue. We first define an updated and extended taxonomy of ensemble learner architectures to characterize and differentiate ensemble learning algorithms. Subsequently, we characterize the special issue contributions in two ways: with respect to the operations research (OR) application they address and contribute to, and methodologically with respect to the newly defined taxonomy. Finally, we present an ambitious agenda for future research on ensemble learning for OR and business analytics.

Suggested Citation

  • Koen W. De Bock & Matthias Bogaert & Philippe Jardin, 2025. "Ensemble learning for operations research and business analytics," Annals of Operations Research, Springer, vol. 353(2), pages 419-448, October.
    • Handle: RePEc:spr:annopr:v:353:y:2025:i:2:d:10.1007_s10479-025-06852-w
    DOI: 10.1007/s10479-025-06852-w
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