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A column-generation-based heuristic algorithm for solving operating theater planning problem under stochastic demand and surgery cancellation risk

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  • Wang, Yu
  • Tang, Jiafu
  • Fung, Richard Y.K.

Abstract

This paper investigated an operating theater allocation problem with uncertain surgery duration and emergency demand. Under the consideration of surgery cancellation, a stochastic model was developed to minimize the total expected operating cost. A trade-off was sought between the total cost of opening operating rooms and the total overtime due to the overbooking of an operating theater. The sample average approximation method was used to transform the stochastic model into a deterministic one. A column-generation-based heuristic (CGBH) algorithm was developed to solve the integer programming problem. The performance of the CGBH algorithm was tested by solving randomly generated instances with given distributions. Multiple heuristic rules for branching were developed and compared from the perspectives of solution quality and efficiency. Numerical results indicated that high surgery cancellation risk helps to reduce the operating costs of hospitals and improve the OR efficiency but results in patients׳ dissatisfaction, and vice versa. This provides management insights for hospital manager to balance the operating costs and patients׳ satisfaction. The CGBH algorithm performed as well as the CPLEX in the solution quality for small-scale problems. This algorithm can obtain solutions within a 5% gap of the lower bound obtained by the linear problem for large-scale problems that cannot be solved by CPLEX.

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  • Wang, Yu & Tang, Jiafu & Fung, Richard Y.K., 2014. "A column-generation-based heuristic algorithm for solving operating theater planning problem under stochastic demand and surgery cancellation risk," International Journal of Production Economics, Elsevier, vol. 158(C), pages 28-36.
    • Handle: RePEc:eee:proeco:v:158:y:2014:i:c:p:28-36
    DOI: 10.1016/j.ijpe.2014.07.015
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    Cited by:

    1. Aida Jebali & Ali Diabat, 2015. "A stochastic model for operating room planning under capacity constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7252-7270, December.
    2. Freeman, Nickolas & Zhao, Ming & Melouk, Sharif, 2018. "An iterative approach for case mix planning under uncertainty," Omega, Elsevier, vol. 76(C), pages 160-173.
    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. Zhang, Yu & Wang, Yu & Tang, Jiafu & Lim, Andrew, 2020. "Mitigating overtime risk in tactical surgical scheduling," Omega, Elsevier, vol. 93(C).
    5. Hossein Hashemi Doulabi & Soheyl Khalilpourazari, 2023. "Stochastic weekly operating room planning with an exponential number of scenarios," Annals of Operations Research, Springer, vol. 328(1), pages 643-664, September.
    6. 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.
    7. Zhang, Jian & Dridi, Mahjoub & El Moudni, Abdellah, 2020. "Column-generation-based heuristic approaches to stochastic surgery scheduling with downstream capacity constraints," International Journal of Production Economics, Elsevier, vol. 229(C).
    8. Arezoo Atighehchian & Mohammad Mehdi Sepehri & Pejman Shadpour & Kamran Kianfar, 2020. "A two-step stochastic approach for operating rooms scheduling in multi-resource environment," Annals of Operations Research, Springer, vol. 292(1), pages 191-214, September.
    9. Jose M. Molina-Pariente & Erwin W. Hans & Jose M. Framinan, 2018. "A stochastic approach for solving the operating room scheduling problem," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 224-251, June.
    10. Ruiwei Jiang & Siqian Shen & Yiling Zhang, 2017. "Integer Programming Approaches for Appointment Scheduling with Random No-Shows and Service Durations," Operations Research, INFORMS, vol. 65(6), pages 1638-1656, December.
    11. Mahdi Noorizadegan & Abbas Seifi, 2018. "An efficient computational method for large scale surgery scheduling problems with chance constraints," Computational Optimization and Applications, Springer, vol. 69(2), pages 535-561, March.
    12. Yanbo Ma & Kaiyue Liu & Zheng Li & Xiang Chen, 2022. "Robust Operating Room Scheduling Model with Violation Probability Consideration under Uncertain Surgery Duration," IJERPH, MDPI, vol. 19(20), pages 1-20, October.
    13. 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.
    14. 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.
    15. Shao, Kaining & Fan, Wenjuan & Lan, Shaowen & Kong, Min & Yang, Shanlin, 2023. "A column generation-based heuristic for brachytherapy patient scheduling with multiple treatment sessions considering radioactive source decay and time constraints," Omega, Elsevier, vol. 118(C).
    16. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Jun Pei & Panos M. Pardalos, 2019. "Operating room planning and surgical case scheduling: a review of literature," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 757-805, April.
    17. Wang, Yu & Zhang, Yu & Tang, Jiafu, 2019. "A distributionally robust optimization approach for surgery block allocation," European Journal of Operational Research, Elsevier, vol. 273(2), pages 740-753.
    18. Hejer Khlif Hachicha & Farah Zeghal Mansour, 2018. "Two-MILP models for scheduling elective surgeries within a private healthcare facility," Health Care Management Science, Springer, vol. 21(3), pages 376-392, September.
    19. Zheng Zhang & Brian T. Denton & Xiaolan Xie, 2020. "Branch and Price for Chance-Constrained Bin Packing," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 547-564, July.
    20. Stock, Gregory N. & McDermott, Christopher & Anand, Gopesh, 2016. "Average surgeon-level volume and hospital performance," International Journal of Production Economics, Elsevier, vol. 182(C), pages 253-262.
    21. Babak Akbarzadeh & Ghasem Moslehi & Mohammad Reisi-Nafchi & Broos Maenhout, 2020. "A diving heuristic for planning and scheduling surgical cases in the operating room department with nurse re-rostering," Journal of Scheduling, Springer, vol. 23(2), pages 265-288, April.
    22. Kaining Shao & Wenjuan Fan & Zishu Yang & Shanlin Yang & Panos M. Pardalos, 2022. "A column generation approach for patient scheduling with setup time and deteriorating treatment duration," Operational Research, Springer, vol. 22(3), pages 2555-2586, July.

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