IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v48y2018i5p399-401.html
   My bibliography  Save this article

Introduction: 2017 Daniel H. Wagner Prize for Excellence in Operations Research Practice

Author

Listed:
  • Patricia Neri

    (SAS Institute Inc., Cary, North Carolina 27513)

  • Russell P. Labe

    (RPL Analytics Consulting LLC, Belle Mead, New Jersey 08512)

Abstract

Competition for the 2017 Daniel H. Wagner Prize for Excellence in Operations Research Practice provided the six finalist papers featured in this special issue of Interfaces . The prestigious Wagner Prize—awarded for achievement in implemented operations research, management science, and advanced analytics—emphasizes quality and originality of mathematical models and clarity of written and oral exposition. Researchers from Lehigh University, in collaboration with the Pennsylvania Department of Corrections, won the competition for their development of a novel hierarchical, multiobjective mixed-integer linear optimization model, which assigns inmates to correctional institutions and schedules their programs, while considering all legal restrictions and best-practice constraints. This successful project opens a rich and untouched area for the application of operations research. The new model and methodology can be utilized for the assignment of inmates in any correctional system. The remaining papers describe work on audience targeting for television advertising, optimizing railroad crew assignments, applying machine-learning models to healthcare and criminal justice, personalized treatment design for managing diabetes, and optimization in bulk tanker transport operations. Full presentation videos with slides are available in the INFORMS Video Library at https://www.informs.org/Resource-Center/Video-Library , and as electronic companions to the Interfaces articles.

Suggested Citation

  • Patricia Neri & Russell P. Labe, 2018. "Introduction: 2017 Daniel H. Wagner Prize for Excellence in Operations Research Practice," Interfaces, INFORMS, vol. 48(5), pages 399-401, October.
  • Handle: RePEc:inm:orinte:v:48:y:2018:i:5:p:399-401
    DOI: 10.1287/inte.2018.0960
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/inte.2018.0960
    Download Restriction: no

    File URL: https://libkey.io/10.1287/inte.2018.0960?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    professional; comments on;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orinte:v:48:y:2018:i:5:p:399-401. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.