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A robust approach for scheduling in hospitals using multiple objectives

Author

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  • Sebastian Rachuba

    (Ruhr University Bochum, Bochum, Germany)

  • Brigitte Werners

    (Ruhr University Bochum, Bochum, Germany)

Abstract

Scheduling in hospitals is a challenging task and stochastic influences have a major impact on the final schedule. Therefore, uncertainties of treatment durations and of emergency arrivals have to be taken into account explicitly. In order to avoid re-scheduling we integrate information on stochastic parameters into a scenario-based mixed-integer optimization model. Besides, we focus on different stakeholders’ objectives that are simultaneously considered within a multi-criteria optimization model. Individually optimal solutions are likely to differ and the overall aim is to identify a good and acceptable compromise solution. The presented approach is based on fuzzy sets and merges the interests of several stakeholders. Different schedules are calculated and later on evaluated with randomly generated scenarios for surgery times and emergencies. The resulting objective function values are close to the individually optimal solutions. Finally, the schedules lead to a high rate of utilization and a low amount of overtime.

Suggested Citation

  • Sebastian Rachuba & Brigitte Werners, 2014. "A robust approach for scheduling in hospitals using multiple objectives," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(4), pages 546-556, April.
    • Handle: RePEc:pal:jorsoc:v:65:y:2014:i:4:p:546-556
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    Citations

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    Cited by:

    1. Freeman, Nickolas & Zhao, Ming & Melouk, Sharif, 2018. "An iterative approach for case mix planning under uncertainty," Omega, Elsevier, vol. 76(C), pages 160-173.
    2. Yuan Gao & Qian Zhang & Chun Kit Lau & Bhagwat Ram, 2022. "Robust Appointment Scheduling in Healthcare," Mathematics, MDPI, vol. 10(22), pages 1-15, November.
    3. Paola Cappanera & Filippo Visintin & Carlo Banditori, 2018. "Addressing conflicting stakeholders’ priorities in surgical scheduling by goal programming," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 252-271, June.
    4. 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.
    5. Jian-Jun Wang & Zongli Dai & Wenxuan Zhang & Jim Junmin Shi, 2023. "Operating room scheduling for non-operating room anesthesia with emergency uncertainty," Annals of Operations Research, Springer, vol. 321(1), pages 565-588, February.
    6. Michael Samudra & Erik Demeulemeester & Brecht Cardoen & Nancy Vansteenkiste & Frank E. Rademakers, 2017. "Due time driven surgery scheduling," Health Care Management Science, Springer, vol. 20(3), pages 326-352, September.
    7. Inês Marques & M. Captivo & Margarida Vaz Pato, 2015. "A bicriteria heuristic for an elective surgery scheduling problem," Health Care Management Science, Springer, vol. 18(3), pages 251-266, September.
    8. Nickolas K. Freeman & Sharif H. Melouk & John Mittenthal, 2016. "A Scenario-Based Approach for Operating Theater Scheduling Under Uncertainty," Manufacturing & Service Operations Management, INFORMS, vol. 18(2), pages 245-261, May.
    9. Marques, Inês & Captivo, M. Eugénia, 2017. "Different stakeholders’ perspectives for a surgical case assignment problem: Deterministic and robust approaches," European Journal of Operational Research, Elsevier, vol. 261(1), pages 260-278.
    10. Sebastian Rachuba & Brigitte Werners, 2017. "A fuzzy multi-criteria approach for robust operating room schedules," Annals of Operations Research, Springer, vol. 251(1), pages 325-350, April.
    11. Koppka, Lisa & Wiesche, Lara & Schacht, Matthias & Werners, Brigitte, 2018. "Optimal distribution of operating hours over operating rooms using probabilities," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1156-1171.

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