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Deep learning applications in operations research

Author

Listed:
  • Ajay Kumar

    (EM - EMLyon Business School)

  • Alexandra Brintrup

    (CAM - University of Cambridge [Cambridge, UK])

  • Eric W. T. Ngai

    (POLYU - The Hong Kong Polytechnic University [Hong Kong])

  • Ravi Shankar

    (IIT Delhi - Indian Institute of Technology Delhi)

  • Myong K. Jeong

    (Rutgers - Rutgers University System)

Abstract

Data science emerges as an inter-disciplinary field, employs scientific methods and algorithms to extract useful insights, and generate value from large datasets, benefiting individuals, firms, and society. In the big data-driven era, traditional data science is undergoing a significant transformation due to the emergence of deep learning. Deep learning, a specialized category of machine learning (ML) algorithms uses multiple layers to uncover hidden patterns, and valuable insights from the big datasets. Deep learning models have gained popularity these days due to their ability to provide superior predictive performance compared to traditional ML models, particularly when trained on large datasets (Kraus et al., 2020).

Suggested Citation

  • Ajay Kumar & Alexandra Brintrup & Eric W. T. Ngai & Ravi Shankar & Myong K. Jeong, 2026. "Deep learning applications in operations research," Working Papers hal-05531896, HAL.
  • Handle: RePEc:hal:wpaper:hal-05531896
    DOI: 10.1007/s10479-024-06102-5
    as

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