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The re-planning and scheduling of surgical cases in the operating room department after block release time with resource rescheduling

Author

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  • Akbarzadeh, Babak
  • Moslehi, Ghasem
  • Reisi-Nafchi, Mohammad
  • Maenhout, Broos

Abstract

The decisions on the strategic and tactical level contained in the operation room scheduling process are based on the expected demand. This demand is used to construct the master surgery schedule in a block booking system, which serves as a base for the planning and scheduling of surgical cases. However, in the operational phase, the actual demand may differ from the expected demand. This leads to increased waiting times, the cancellation of surgical cases and an inefficient utilisation of the operation room department for surgeons with spare capacity. In this paper, we study the Surgical Case re-Planning and Scheduling problem with resource re-scheduling that arises at block release time where the operation room planner tries to balance the capacity and the demand on the operational level. To that purpose, changes with respect to the surgeon schedule and the nurse roster are considered to adequately re-plan and schedule surgical cases. The problem under study minimises the number of changes related to the patient planning, the patient waiting time and the resource re-scheduling cost. We propose a three-phase heuristic that uses column generation to construct a high-quality feasible solution, which is further improved via local branching. Computational experiments have been conducted on an artificial dataset generated in a controlled and structured manner and on real-life data. Results demonstrate that our approach is able to produce (near-)optimal solutions and show the contribution of the different algorithmic building blocks.

Suggested Citation

  • Akbarzadeh, Babak & Moslehi, Ghasem & Reisi-Nafchi, Mohammad & Maenhout, Broos, 2019. "The re-planning and scheduling of surgical cases in the operating room department after block release time with resource rescheduling," European Journal of Operational Research, Elsevier, vol. 278(2), pages 596-614.
    • Handle: RePEc:eee:ejores:v:278:y:2019:i:2:p:596-614
    DOI: 10.1016/j.ejor.2019.04.037
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    References listed on IDEAS

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    Cited by:

    1. Akbarzadeh, Babak & Maenhout, Broos, 2024. "A study on policy decisions to embed flexibility for reactive recovery in the planning and scheduling process in operating rooms," Omega, Elsevier, vol. 126(C).
    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. Aisha Tayyab & Saif Ullah & Mohammed Fazle Baki, 2023. "An Outer Approximation Method for Scheduling Elective Surgeries with Sequence Dependent Setup Times to Multiple Operating Rooms," Mathematics, MDPI, vol. 11(11), pages 1-15, May.
    4. Tsai, Shing Chih & Yeh, Yingchieh & Kuo, Chen Yun, 2021. "Efficient optimization algorithms for surgical scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 293(2), pages 579-593.
    5. 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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