IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v51y2021i5p329-331.html
   My bibliography  Save this article

Introduction: 2020 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research

Author

Listed:
  • Mary E. Helander

    (Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, New York 13244)

  • Lawrence D. Stone

    (Metron, Reston, Virginia 20190)

Abstract

The judges for the 2020 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research selected the five finalist papers featured in this special issue of the INFORMS Journal on Applied Analytics ( IJAA ). The prestigious Wagner Prize—awarded for achievement in implemented operations research, management science, and advanced analytics—emphasizes the quality and originality of mathematical models along with clarity of written and oral exposition. This year’s winning application is a system for optimally managing Dow Agrosciences’ (now Corteva) seed corn portfolio, which includes seeds for several hundred varieties of corn and is valued at more than $1 billion. The model employs Bayesian analytic methods to estimate crop yields from expert judgement. Stochastic optimization is then used to determine backup production in South America while dealing with yield uncertainty in North America. The remaining four papers include an efficient mixed-integer program used by Birchbox to determine individualized subscriber product sets; a scheduling system for Argentina’s premier soccer league; an incentive system for encouraging Lyft drivers to reposition to provide improved service; and a system for optimizing the electric bus network design in Rotterdam.

Suggested Citation

  • Mary E. Helander & Lawrence D. Stone, 2021. "Introduction: 2020 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research," Interfaces, INFORMS, vol. 51(5), pages 329-331, September.
    • Handle: RePEc:inm:orinte:v:51:y:2021:i:5:p:329-331
    DOI: 10.1287/inte.2021.1094
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2021.1094
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.2021.1094?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
    ---><---

    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:51:y:2021:i:5:p:329-331. 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.