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Predictive-reactive scheduling for single surgical suite subject to random emergency surgery

Author

Listed:
  • Bing Wang

    (Shanghai University)

  • Xingbao Han

    (Shanghai University)

  • Xianxia Zhang

    (Shanghai University)

  • Shaohua Zhang

    (Shanghai University)

Abstract

This paper discusses the surgery scheduling problem for single surgical suite subject to random emergency surgery. In a surgical suite, each patient should be treated by three stages in the same order. This problem can be handled as a no-wait permutation flow-shop scheduling problem with three machines. A predictive-reactive scheduling approach is developed to accommodate the influence of surgery’s arrival on planned schedule while optimizing the objective of combining efficiency and stability. In the predictive scheduling phase, an initial schedule is generated by solely optimizing the efficiency, and then slack time is inserted in the initial schedule to generate a planned schedule based on the occurrence probability of emergency surgery. In the reactive scheduling phase, a “break-in-moment” of emergency surgery is determined to satisfy the requirement of non-preemption surgery and the no-wait constraint. A partial-rescheduling approach is used to revise the schedule of unperformed surgeries after an emergency surgery certainly breaks in the planned schedule. A computational experiment was conducted and the computational results demonstrate that comparing with traditional approaches, the predictive-reactive scheduling approach developed here could significantly improve the stability with a little sacrifice in the efficiency for all tested instances.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:jcomop:v:30:y:2015:i:4:d:10.1007_s10878-015-9861-2
    DOI: 10.1007/s10878-015-9861-2
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    References listed on IDEAS

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    2. Sean Harris & David Claudio, 2022. "Current Trends in Operating Room Scheduling 2015 to 2020: a Literature Review," SN Operations Research Forum, Springer, vol. 3(1), pages 1-42, March.
    3. Zhiguo Wang & Lufei Huang & Cici Xiao He, 2021. "A multi-objective and multi-period optimization model for urban healthcare waste’s reverse logistics network design," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 785-812, November.
    4. Duma, Davide & Aringhieri, Roberto, 2019. "The management of non-elective patients: shared vs. dedicated policies," Omega, Elsevier, vol. 83(C), pages 199-212.
    5. Samuel Davis & Nasser Fard, 2020. "Theoretical bounds and approximation of the probability mass function of future hospital bed demand," Health Care Management Science, Springer, vol. 23(1), pages 20-33, March.
    6. Hao Hao & Ji Zhang & Qian Zhang & Li Yao & Yichen Sun, 0. "Improved gray neural network model for healthcare waste recycling forecasting," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-18.
    7. Allahverdi, Ali, 2016. "A survey of scheduling problems with no-wait in process," European Journal of Operational Research, Elsevier, vol. 255(3), pages 665-686.
    8. Hao Hao & Ji Zhang & Qian Zhang & Li Yao & Yichen Sun, 2021. "Improved gray neural network model for healthcare waste recycling forecasting," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 813-830, November.
    9. Zhiguo Wang & Lufei Huang & Cici Xiao He, 0. "A multi-objective and multi-period optimization model for urban healthcare waste’s reverse logistics network design," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-28.
    10. Arne Schulz & Malte Fliedner, 2023. "Minimizing the expected waiting time of emergency jobs," Journal of Scheduling, Springer, vol. 26(2), pages 147-167, April.
    11. Belinda Spratt & Erhan Kozan, 2021. "A real-time reactive framework for the surgical case sequencing problem," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 183-211, March.
    12. Gökalp, E. & Gülpınar, N. & Doan, X.V., 2023. "Dynamic surgery management under uncertainty," European Journal of Operational Research, Elsevier, vol. 309(2), pages 832-844.

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