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Scheduling with Testing

Author

Listed:
  • Retsef Levi

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Thomas Magnanti

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139; and Singapore University of Technology and Design, Singapore 138682)

  • Yaron Shaposhnik

    (Simon Business School, University of Rochester, Rochester, New York 14627)

Abstract

We study a new class of scheduling problems that capture common settings in service environments, in which one has to serve a collection of jobs that have a priori uncertain attributes (e.g., processing times and priorities) and the service provider has to decide how to dynamically allocate resources (e.g., people, equipment, and time) between testing (diagnosing) jobs to learn more about their respective uncertain attributes and processing jobs. The former could inform future decisions, but could delay the service time for other jobs, while the latter directly advances the processing of the jobs but requires making decisions under uncertainty. Through novel analysis we obtain surprising structural results of optimal policies that provide operational managerial insights, efficient optimal and near-optimal algorithms, and quantification of the value of testing. We believe that our approach will lead to further research to explore this important practical trade-off.

Suggested Citation

  • Retsef Levi & Thomas Magnanti & Yaron Shaposhnik, 2019. "Scheduling with Testing," Management Science, INFORMS, vol. 65(2), pages 776-793, February.
    • Handle: RePEc:inm:ormnsc:v:65:y:2019:i:2:p:776-793
    DOI: 10.1287/mnsc.2017.2973
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    References listed on IDEAS

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    Cited by:

    1. Zhankun Sun & Nilay Tanık Argon & Serhan Ziya, 2022. "When to Triage in Service Systems with Hidden Customer Class Identities?," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 172-193, January.
    2. Sanjay Jain & Jónas Oddur Jónasson & Jean Pauphilet & Kamalini Ramdas, 2023. "Robust combination testing: methods and application to COVID-19 detection," Economics Series Working Papers 1009, University of Oxford, Department of Economics.
    3. Wu, Wei & Hayashi, Takito & Haruyasu, Kato & Tang, Liang, 2023. "Exact algorithms based on a constrained shortest path model for robust serial-batch and parallel-batch scheduling problems," European Journal of Operational Research, Elsevier, vol. 307(1), pages 82-102.

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