NEWS    Arvind Raghunathan's publication is Featured Article in the current issue of the INFORMS Journal on Computing

Date released: May 9, 2022


  •  NEWS    Arvind Raghunathan's publication is Featured Article in the current issue of the INFORMS Journal on Computing
  • Date:

    April 1, 2022

  • Where:

    INFORMS Journal on Computing (https://pubsonline.informs.org/journal/ijoc)

  • Description:

    Arvind Raghunathan co-authored a publication titled "JANOS: An Integrated Predictive and Prescriptive Modeling Framework" which has been chosen as a Featured Article in the current issue of the INFORMS Journal on Computing. The article was co-authored with Prof. David Bergman, a collaborator of MERL and Teng Huang, a former MERL intern, among others.

    The paper describes a new software tool, JANOS, that integrates predictive modeling and discrete optimization to assist decision making. Specifically, the proposed solver takes as input user-specified pretrained predictive models and formulates optimization models directly over those predictive models by embedding them within an optimization model through linear transformations.

  • External Link:

    https://pubsonline.informs.org/doi/epdf/10.1287/ijoc.2020.1023

  • MERL Contact:
  • Research Areas:

    Artificial Intelligence, Machine Learning, Optimization

    •  Bergman, D., Huang, T., Brooks, P., Lodi, A., Raghunathan, A., "JANOS: An Integrated Predictive and Prescriptive Modeling Framework", INFORMS Journal on Computing, DOI: 10.1287/​ijoc.2020.1023, Vol. 34, No. 2, pp. 807–816, March 2021.
      BibTeX TR2021-025 PDF
      • @article{Bergman2021mar,
      • author = {Bergman, David and Huang, Teng and Brooks, Philip and Lodi, Andrea and Raghunathan, Arvind},
      • title = {{JANOS: An Integrated Predictive and Prescriptive Modeling Framework}},
      • journal = {INFORMS Journal on Computing},
      • year = 2021,
      • volume = 34,
      • number = 2,
      • pages = {807–816},
      • month = mar,
      • doi = {10.1287/ijoc.2020.1023},
      • url = {https://www.merl.com/publications/TR2021-025}
      • }