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Resource Allocation in an Uncertain Environment: Application to Snowplowing Operations in Utah

Author

Listed:
  • Yinhu Wang

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

  • Ye Chen

    (Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, Virginia 23284)

  • Ilya O. Ryzhov

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

  • Xiaoyue Cathy Liu

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

  • Nikola Marković

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

Abstract

We consider a two-stage planning problem where a fleet of snowplow trucks is divided among a set of independent regions, each of which then designs routes for efficient snow removal. The central authority wishes to allocate trucks to improve service quality across the regions. Stochasticity is introduced by uncertain weather conditions and unforeseen failures of snowplow trucks. We study two versions of this problem. The first aims to minimize the maximum turnaround time (across all regions) that can be sustained with a user-specified probability. The second seeks to minimize the total expected workload that has not been completed within a user-specified time frame. We develop algorithms that solve these problems effectively and demonstrate their practical value through a case application to snowplowing operations in Utah, obtaining solutions that significantly outperform the allocation currently used in practice.

Suggested Citation

  • Yinhu Wang & Ye Chen & Ilya O. Ryzhov & Xiaoyue Cathy Liu & Nikola Marković, 2024. "Resource Allocation in an Uncertain Environment: Application to Snowplowing Operations in Utah," Transportation Science, INFORMS, vol. 58(4), pages 781-800, July.
    • Handle: RePEc:inm:ortrsc:v:58:y:2024:i:4:p:781-800
    DOI: 10.1287/trsc.2023.0024
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