IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v73y2025i5p2375-2395.html
   My bibliography  Save this article

D-Optimal Orienteering for Post-Earthquake Reconnaissance Planning

Author

Listed:
  • Jiaqi Wang

    (Mathematics, University of Maryland, College Park, Maryland 20742)

  • Weijun Xie

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Ilya O. Ryzhov

    (Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742)

  • Nikola Marković

    (Civil and Environmental Engineering, University of Utah, Salt Lake City, Utah 84112)

  • Ge Ou

    (Civil and Coastal Engineering, University of Florida, Gainesville, Florida 32611)

Abstract

Immediately following a major earthquake, reconnaissance surveys seek to assess structural damage throughout the region with the help of a limited number of on-ground inspections. The goal is to collect informative and representative data that will guide subsequent relief efforts. We formulate a new type of vehicle routing problem, in which vehicles are tasked with data collection, and the objective function measures data quality using a nonlinear, nonseparable experimental design criterion. We create novel exact methods for this problem and demonstrate their practical potential in a realistic case study using a state-of-the-art earthquake simulator.

Suggested Citation

  • Jiaqi Wang & Weijun Xie & Ilya O. Ryzhov & Nikola Marković & Ge Ou, 2025. "D-Optimal Orienteering for Post-Earthquake Reconnaissance Planning," Operations Research, INFORMS, vol. 73(5), pages 2375-2395, September.
    • Handle: RePEc:inm:oropre:v:73:y:2025:i:5:p:2375-2395
    DOI: 10.1287/opre.2023.0470
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.2023.0470
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.2023.0470?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

    ;

    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:oropre:v:73:y:2025:i:5:p:2375-2395. 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.