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Article Dans Une Revue European Journal of Operational Research Année : 2024

Explainable Analytics for Operational Research

K. de Bock
K. Coussement
  • Fonction : Auteur
A. de Caigny
  • Fonction : Auteur

Résumé

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.
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Dates et versions

hal-04571846 , version 1 (28-05-2024)

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Citer

K. de Bock, K. Coussement, A. de Caigny. Explainable Analytics for Operational Research. European Journal of Operational Research, 2024, 317 (2), ⟨10.1016/j.ejor.2024.04.015⟩. ⟨hal-04571846⟩

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