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Minimizing the expected waiting time of emergency jobs

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  • Arne Schulz

    (Institute of Operations Management, Universität Hamburg)

  • Malte Fliedner

    (Institute of Operations Management, Universität Hamburg)

Abstract

We consider a scheduling problem where a set of known jobs needs to be assigned to a set of given parallel resources such that the expected waiting time for a set of uncertain emergency jobs is kept as small as possible. On the basis of structural insights from queuing theory, we develop deterministic scheduling policies that reserve resource capacity in order to increase the likelihood of resource availability whenever an emergency job arrives. Applications of this particular scheduling problem are, for instance, found in the field of surgical operations scheduling in hospitals, where high-priority but uncertain emergencies compete for scarce operating room capacity with elective surgeries of lower priority. We compare our approaches with other policies from the literature in a comprehensive simulation study of a surgical operations unit.

Suggested Citation

  • Arne Schulz & Malte Fliedner, 2023. "Minimizing the expected waiting time of emergency jobs," Journal of Scheduling, Springer, vol. 26(2), pages 147-167, April.
    • Handle: RePEc:spr:jsched:v:26:y:2023:i:2:d:10.1007_s10951-022-00767-1
    DOI: 10.1007/s10951-022-00767-1
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    References listed on IDEAS

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    1. Hans, Erwin & Wullink, Gerhard & van Houdenhoven, Mark & Kazemier, Geert, 2008. "Robust surgery loading," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1038-1050, March.
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    5. Vandenberghe, Mathieu & De Vuyst, Stijn & Aghezzaf, El-Houssaine & Bruneel, Herwig, 2019. "Surgery sequencing to minimize the expected maximum waiting time of emergent patients," European Journal of Operational Research, Elsevier, vol. 275(3), pages 971-982.
    6. Kyung Sung Jung & Michael Pinedo & Chelliah Sriskandarajah & Vikram Tiwari, 2019. "Scheduling Elective Surgeries with Emergency Patients at Shared Operating Rooms," Production and Operations Management, Production and Operations Management Society, vol. 28(6), pages 1407-1430, June.
    7. Yao Xiao & Reena Yoogalingam, 2021. "Reserved capacity policies for operating room scheduling," Operations Management Research, Springer, vol. 14(1), pages 107-122, June.
    8. Pham, Dinh-Nguyen & Klinkert, Andreas, 2008. "Surgical case scheduling as a generalized job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1011-1025, March.
    9. Bovim, Thomas Reiten & Christiansen, Marielle & Gullhav, Anders N. & Range, Troels Martin & Hellemo, Lars, 2020. "Stochastic master surgery scheduling," European Journal of Operational Research, Elsevier, vol. 285(2), pages 695-711.
    10. Bing Wang & Xingbao Han & Xianxia Zhang & Shaohua Zhang, 2015. "Predictive-reactive scheduling for single surgical suite subject to random emergency surgery," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 949-966, November.
    11. Cardoen, Brecht & Demeulemeester, Erik & Beliën, Jeroen, 2010. "Operating room planning and scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 201(3), pages 921-932, March.
    12. Michael Samudra & Carla Van Riet & Erik Demeulemeester & Brecht Cardoen & Nancy Vansteenkiste & Frank E. Rademakers, 2016. "Scheduling operating rooms: achievements, challenges and pitfalls," Journal of Scheduling, Springer, vol. 19(5), pages 493-525, October.
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    Cited by:

    1. Arne Schulz, 2023. "The balanced maximally diverse grouping problem with integer attribute values," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-27, July.

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