Skip to main content

Advertisement

SpringerLink
Log in

Robust finite-horizon scheduling/rescheduling of operating rooms with elective and emergency surgeries under resource constraints

  • Published:
Journal of Scheduling Aims and scope Submit manuscript

Abstract

Proper planning and scheduling of activities involved in health can improve productivity in this area. In this regard, hospitals are one of the most critical components, and in hospitals, the operating room is one of the most important ones. Since the operating room is a very costly facility, the scheduling of the patients and involved resources is an important issue. In this study, the problem of scheduling and rescheduling of the operating room in a finite horizon is investigated to minimize the total waiting time and tardiness of patients. The constraints in the problem under consideration are the number of surgeons and the number of beds available. Furthermore, emergency patients as well elective patients are considered simultaneously in our proposed model. In addition to operating room scheduling in this study, rescheduling is also done to canceled patients. To further fit the model presented with reality, uncertainties in parameters such as operating time and the number of beds in the post-anesthesia care unit are also considered. In this study, robust optimization is used to deal with uncertainties in the model. After applying the Bertsimas and Sim approach, due to the complexity of the problem under investigation, the genetic algorithm is used to solve the proposed model. To validate the mentioned algorithm, the particle swarm optimization algorithm is selected according to the literature. The results of the comparison show the superiority of the proposed algorithm compared to the particle swarm optimization algorithm in terms of the objective function and running time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

Enquiries about data availability should be directed to the authors.

References

  • Abedini, A., Li, W., & Ye, H. (2017). An optimization model for operating room scheduling to reduce blocking across the perioperative process. Procedia Manufacturing, 10, 60–70.

    Article  Google Scholar 

  • Addis, B., Carello, G., Grosso, A., & Tànfani, E. (2016). Operating room scheduling and rescheduling: A rolling horizon approach. Flexible Services and Manufacturing Journal, 28(1–2), 206–232.

    Article  Google Scholar 

  • Al-Refaie, A., Judeh, M., & Chen, T. (2018). Optimal multiple-period scheduling and sequencing of operating room and intensive care unit. Operational Research, 18(3), 645–670.

    Article  Google Scholar 

  • Anjomshoa, H., Dumitrescu, I., Lustig, I., & Smith, O. J. (2018). An exact approach for tactical planning and patient selection for elective surgeries. European Journal of Operational Research, 268(2), 728–739.

    Article  Google Scholar 

  • Aragon, L. G., Cure, L., Tiong, E., & Bush, R. (2018). Modeling and analysis of short-term work planning in inpatient care settings. Operations Research for Health Care, 19, 14–25.

    Article  Google Scholar 

  • Ballestín, F., Pérez, Á., & Quintanilla, S. (2019). Scheduling and rescheduling elective patients in operating rooms to minimise the percentage of tardy patients. Journal of Scheduling, 22(1), 107–118.

    Article  Google Scholar 

  • Ben-Tal, A., & Nemirovski, A. (1998). Robust convex optimization. Mathematics of Operations Research, 23(4), 769–805.

    Article  Google Scholar 

  • Bertsimas, D., & Sim, M. (2003). Robust discrete optimization and network flows. Mathematical Programming, 98(1–3), 49–71.

    Article  Google Scholar 

  • Bertsimas, D., & Sim, M. (2004). The price of robustness. Operations Research, 52(1), 35–53.

    Article  Google Scholar 

  • Burdett, R. L., & Kozan, E. (2018). An integrated approach for scheduling health care activities in a hospital. European Journal of Operational Research, 264(2), 756–773.

    Article  Google Scholar 

  • Ceschia, S., & Schaerf, A. (2016). Dynamic patient admission scheduling with operating room constraints, flexible horizons, and patient delays. Journal of Scheduling, 19, 377–389.

    Article  Google Scholar 

  • Choi, S., & Wilhelm, W. E. (2014). An approach to optimize block surgical schedules. European Journal of Operational Research, 235(1), 138–148.

    Article  Google Scholar 

  • De Vuyst, S., Bruneel, H., & Fiems, D. (2014). Computationally efficient evaluation of appointment schedules in health care. European Journal of Operational Research, 237(3), 1142–1154.

    Article  Google Scholar 

  • Dios, M., Molina-Pariente, J. M., Fernandez-Viagas, V., Andrade-Pineda, J. L., & Framinan, J. M. (2015). A decision support system for operating room scheduling. Computers and Industrial Engineering, 88, 430–443.

    Article  Google Scholar 

  • Durán, G., Rey, P. A., & Wolff, P. (2017). Solving the operating room scheduling problem with prioritized lists of patients. Annals of Operations Research, 258(2), 395–414.

    Article  Google Scholar 

  • Guerriero, F., & Guido, R. (2011). Operational research in the management of the operating theatre: A survey. Health Care Management Science, 14(1), 89–114.

    Article  Google Scholar 

  • Guido, R., & Conforti, D. (2017). A hybrid genetic approach for solving an integrated multi-objective operating room planning and scheduling problem. Computers and Operations Research, 87, 270–282.

    Article  Google Scholar 

  • Hooshmand, F., MirHassani, S., & Akhavein, A. (2018). Adapting GA to solve a novel model for operating room scheduling problem with endogenous uncertainty. Operations Research for Health Care, 19, 26–43.

    Article  Google Scholar 

  • Jebali, A., & Diabat, A. (2017). A chance-constrained operating room planning with elective and emergency cases under downstream capacity constraints. Computers and Industrial Engineering, 114, 329–344.

    Article  Google Scholar 

  • Klassen, K. J., & Yoogalingam, R. (2019). Appointment scheduling in multi-stage outpatient clinics. Health Care Management Science, 22(2), 229–244.

    Article  Google Scholar 

  • Kroer, L. R., Foverskov, K., Vilhelmsen, C., Hansen, A. S., & Larsen, J. (2018). Planning and scheduling operating rooms for elective and emergency surgeries with uncertain duration. Operations Research for Health Care, 19, 107–119.

    Article  Google Scholar 

  • Kumar, A., Costa, A. M., Fackrell, M., & Taylor, P. G. (2018). A sequential stochastic mixed integer programming model for tactical master surgery scheduling. European Journal of Operational Research, 270(2), 734–746.

    Article  Google Scholar 

  • Landa, P., Aringhieri, R., Soriano, P., Tànfani, E., & Testi, A. (2016). A hybrid optimization algorithm for surgeries scheduling. Operations Research for Health Care, 8, 103–114.

    Article  Google Scholar 

  • Liu, H., Zhang, T., Luo, S., & Xu, D. (2018). Operating room scheduling and surgeon assignment problem under surgery durations uncertainty. Technology and Health Care, 26(2), 297–304.

    Article  Google Scholar 

  • Luo, L., Luo, Y., You, Y., Cheng, Y., Shi, Y., & Gong, R. (2016). A MIP model for rolling horizon surgery scheduling. Journal of Medical Systems, 40(5), 1–7.

    Article  Google Scholar 

  • Molina-Pariente, J. M., Hans, E. W., & Framinan, J. M. (2018). A stochastic approach for solving the operating room scheduling problem. Flexible Services and Manufacturing Journal, 30(1–2), 224–251.

    Article  Google Scholar 

  • Samudra, M., Van Riet, C., & Demeulemeester, E. (2016). Scheduling operating rooms: Achievements, challenges and pitfalls. Journal of Scheduling, 19, 493–525.

    Article  Google Scholar 

  • Soyster, A. L. (1973). Convex programming with set-inclusive constraints and applications to inexact linear programming. Operations Research, 21(5), 1154–1157.

    Article  Google Scholar 

  • Vali Siar, M. M., Gholami, S., & Ramezanian, R. (2017). Multi-period and multi-resource operating room scheduling and rescheduling using a rolling horizon approach: A case study. Journal of Industrial and Systems Engineering, 10(special issue on healthcare), 97–115.

    Google Scholar 

  • van Essen, J. T., Hans, E. W., Hurink, J. L., & Oversberg, A. (2012). Minimizing the waiting time for emergency surgery. Operations Research for Health Care, 1(2–3), 34–44.

    Article  Google Scholar 

  • Wang, Y., Tang, J., Pan, Z., & Yan, C. (2015). Particle swarm optimization-based planning and scheduling for a laminar-flow operating room with downstream resources. Soft Computing, 19(10), 2913–2926.

    Article  Google Scholar 

  • Xiang, W., Yin, J., & Lim, G. (2015). An ant colony optimization approach for solving an operating room surgery scheduling problem. Computers and Industrial Engineering, 85, 335–345.

    Article  Google Scholar 

  • Zaerpour, F., Bischak, D. P., & Menezes, M. B. (2017). Coordinated lab-clinics: A tactical assignment problem in healthcare. European Journal of Operational Research, 263(1), 283–294.

    Article  Google Scholar 

Download references

Funding

The authors have not disclosed any funding.

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran

    F. Davarian & J. Behnamian

Authors
  1. F. Davarian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Behnamian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. Behnamian.

Ethics declarations

Conflict of interest

The authors have not disclosed any competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Davarian, F., Behnamian, J. Robust finite-horizon scheduling/rescheduling of operating rooms with elective and emergency surgeries under resource constraints. J Sched 25, 625–641 (2022). https://doi.org/10.1007/s10951-022-00741-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10951-022-00741-x

Keywords

Search

Navigation