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Solving integrated operating room planning and scheduling: Logic-based Benders decomposition versus Branch-Price-and-Cut

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  • Roshanaei, Vahid
  • Naderi, Bahman

Abstract

Integrated operating room planning and scheduling (IORPS) allocates patients optimally to different days in a planning horizon, assigns the allocated set of patients to ORs, and sequences/schedules these patients within the list of ORs and surgeons to maximize the total scheduled surgical time. The state-of-the-art model in the IORPS literature is a hybrid constraint programming (CP) and integer programming (IP) technique that is efficiently solved by a multi-featured Branch-Price-&Cut (BP&C) algorithm. We extend the IORPS literature in two ways: (i) we develop new mixed-integer programming (MIP) and CP models that improve the existing CP-IP model and (ii) we develop various combinatorial Benders decomposition algorithms that outperform the existing BP&C algorithm. Using the same dataset as used for the existing methods, we show that our MIP model achieves an average optimality gap of 3.84%, outperforming the existing CP-IP model that achieves an average optimality gap of 11.84%. Furthermore, our MIP model is 54–92 times faster than the CP-IP model in some of the optimally solved instances of the problem. We demonstrate that our best Benders decomposition approach achieves an average optimality gap of 0.88%, whereas the existing BP&C algorithm achieves an average optimality gap of 2.81%.

Suggested Citation

  • Roshanaei, Vahid & Naderi, Bahman, 2021. "Solving integrated operating room planning and scheduling: Logic-based Benders decomposition versus Branch-Price-and-Cut," European Journal of Operational Research, Elsevier, vol. 293(1), pages 65-78.
    • Handle: RePEc:eee:ejores:v:293:y:2021:i:1:p:65-78
    DOI: 10.1016/j.ejor.2020.12.004
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    References listed on IDEAS

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    Cited by:

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    2. Esmaeilbeigi, Rasul & Mak-Hau, Vicky & Yearwood, John & Nguyen, Vivian, 2022. "The multiphase course timetabling problem," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1098-1119.
    3. Guo, Penghui & Zhu, Jianjun, 2023. "Capacity reservation for humanitarian relief: A logic-based Benders decomposition method with subgradient cut," European Journal of Operational Research, Elsevier, vol. 311(3), pages 942-970.
    4. Kamran Kianfar & Arezoo Atighehchian, 2023. "A hybrid heuristic approach to master surgery scheduling with downstream resource constraints and dividable operating room blocks," Annals of Operations Research, Springer, vol. 328(1), pages 727-754, September.
    5. Naderi, Bahman & Begen, Mehmet A. & Zaric, Gregory S. & Roshanaei, Vahid, 2023. "A novel and efficient exact technique for integrated staffing, assignment, routing, and scheduling of home care services under uncertainty," Omega, Elsevier, vol. 116(C).

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