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Explainable Analytics for Operational Research

Author

Listed:
  • K. de Bock

    (Audencia Business School)

  • K. Coussement
  • A. de Caigny

Abstract

The steep rise of analytics and AI in Operational Research (OR) is reflected by its increasing number of academic publications (Hindle et al. 2020) as well as the excitement amongst commercial organizations, governments, and communities to create value from their data. In this feature cluster, we invited authors to submit high-quality contributions addressing theoretical and algorithmic developments advancing the theory and methodology of explainable analytics and AI within OR, as well as real-world innovative implementations in business and society in areas as marketing and sales, supply chain management, education, production and service operations, medicine, bioinformatics, (financial) risk, and fraud.

Suggested Citation

  • K. de Bock & K. Coussement & A. de Caigny, 2024. "Explainable Analytics for Operational Research," Post-Print hal-04571846, HAL.
    • Handle: RePEc:hal:journl:hal-04571846
    DOI: 10.1016/j.ejor.2024.04.015
    Note: View the original document on HAL open archive server: https://hal.science/hal-04571846
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