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A hybrid genetic algorithm for operating room scheduling

Author

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  • Yang-Kuei Lin

    (Feng Chia University)

  • Yin-Yi Chou

    (Feng Chia University)

Abstract

In this research, we studied operating room scheduling problem of assigning a set of surgeries to several multifunctional operating rooms. The objectives are to maximize the utilization of the operating rooms, to minimize the overtime-operating cost, and to minimize the wasting cost for the unused time. To begin with, a revised mathematical model is constructed to assign surgeries to operating rooms within one week. Then, we proposed four easy-to-implement heuristics that can guarantee to find feasible solutions for the studied problem efficiently. Furthermore, we presented four local search procedures that can improve a given solution significantly. Finally, a hybrid genetic algorithm (HGA) that incorporated with initial solutions, local search procedures and elite search procedure is applied to the studied problem. Computational results show that for small problem instances, the HGA can find near optimal solutions efficiently while for large problem instances, the HGA performs significantly better than the four proposed heuristics. We concluded that surgery schedules obtained by using HGA has less wasting cost for the unused time, much higher utilization of operating rooms, and produce less overtime-operating cost.

Suggested Citation

  • Yang-Kuei Lin & Yin-Yi Chou, 2020. "A hybrid genetic algorithm for operating room scheduling," Health Care Management Science, Springer, vol. 23(2), pages 249-263, June.
    • Handle: RePEc:kap:hcarem:v:23:y:2020:i:2:d:10.1007_s10729-019-09481-5
    DOI: 10.1007/s10729-019-09481-5
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    References listed on IDEAS

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    1. Roshanaei, Vahid & Luong, Curtiss & Aleman, Dionne M. & Urbach, David, 2017. "Propagating logic-based Benders’ decomposition approaches for distributed operating room scheduling," European Journal of Operational Research, Elsevier, vol. 257(2), pages 439-455.
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    6. Vallada, Eva & Ruiz, Rubén, 2011. "A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 211(3), pages 612-622, June.
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    8. John T. Blake & Joan Donald, 2002. "Mount Sinai Hospital Uses Integer Programming to Allocate Operating Room Time," Interfaces, INFORMS, vol. 32(2), pages 63-73, April.
    9. Seyed Hossein Hashemi Doulabi & Louis-Martin Rousseau & Gilles Pesant, 2016. "A Constraint-Programming-Based Branch-and-Price-and-Cut Approach for Operating Room Planning and Scheduling," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 432-448, August.
    10. Vijayakumar, Bharathwaj & Parikh, Pratik J. & Scott, Rosalyn & Barnes, April & Gallimore, Jennie, 2013. "A dual bin-packing approach to scheduling surgical cases at a publicly-funded hospital," European Journal of Operational Research, Elsevier, vol. 224(3), pages 583-591.
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    12. 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.
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    Cited by:

    1. David D. Cho & Kurt M. Bretthauer & Jan Schoenfelder, 2023. "Patient-to-nurse ratios: Balancing quality, nurse turnover, and cost," Health Care Management Science, Springer, vol. 26(4), pages 807-826, December.
    2. Morteza Lalmazloumian & M. Fazle Baki & Majid Ahmadi, 2023. "A two-stage stochastic optimization framework to allocate operating room capacity in publicly-funded hospitals under uncertainty," Health Care Management Science, Springer, vol. 26(2), pages 238-260, June.

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