The Multi-Period Surgical Scheduling with Capacity Constraint: A Mathematical Modelling Approach

Authors

  • Warisa Wisittipanich Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Thailand
  • Chawis Boonmee Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Thailand
  • Krit Khwanngern Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University Chiang Mai, Thailand
  • Wichai Chattinnawat Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University Chiang Mai, Thailand

DOI:

https://doi.org/10.56225/ijgoia.v1i2.21

Keywords:

mathematical model, surgical scheduling, multi-period, capacity constraint, minimization

Abstract

This research proposes a mathematical model for multi-period surgical scheduling problem with capacity constraint over a particular time horizon. The goal is to schedule a list of patients who must undergo various kinds of operations by different eligible hospitals. In particular, each operation must be performed in a particular time period and different operations of one patient can be performed by different eligible hospitals. In addition, each hospital has limited surgery capacity for each time period. The problem is formulated with a multi-objective model using the weighted sum approach of two objectives: minimization of makespan and minimization of total least preference assignment score. The experiment is executed using the simulated data according to the real treatments of cleft lip and palate patients. The results show that the model yield the correct assignment and operation sequence respected to all constraints. Thus, this proposed mathematical model can be further used as smart decision tool in surgical scheduling in hospital network.

References

Cardoen, B., Demeulemeester, E., & Beliën, J. (2010). Operating room planning and scheduling: A literature review. European Journal of Operational Research, 201(3), 921–932. https://doi.org/10.1016/j.ejor.2009.04.011

Donahue, R., Russell, D., de Riese, C., Smith, C., de Riese, W. T. W., & Medway, A. (2017). Patients willing to wait: arrival time, wait time and patient satisfaction in an ambulatory urology clinic. Urology Practice, 4(1), 1–6. https://doi.org/10.1016/j.urpr.2016.02.003

Drupsteen, J., van der Vaart, T., & van Donk, D. P. (2013). Integrative practices in hospitals and their impact on patient flow. International Journal of Operations & Production Management, 33(7), 912–933. https://doi.org/10.1108/IJOPM-12-2011-0487

Gartner, D., & Kolisch, R. (2014). Scheduling the hospital-wide flow of elective patients. European Journal of Operational Research, 233(3), 689–699. https://doi.org/10.1016/j.ejor.2013.08.026

Hamid, M., Nasiri, M. M., Werner, F., Sheikhahmadi, F., & Zhalechian, M. (2019). Operating room scheduling by considering the decision-making styles of surgical team members: a comprehensive approach. Computers & Operations Research, 108, 166–181. https://doi.org/10.1016/j.cor.2019.04.010

Jebali, A., & Diabat, A. (2015). A stochastic model for operating room planning under capacity constraints. International Journal of Production Research, 53(24), 7252–7270. https://doi.org/10.1080/00207543.2015.1033500

Langer, E. J. (1977). The psychology of chance. Journal for the Theory of Social Behaviour, 7(2), 185–207.

May, J. H., Spangler, W. E., Strum, D. P., & Vargas, L. G. (2011). The surgical scheduling problem: Current research and future opportunities. Production and Operations Management, 20(3), 392–405. https://doi.org/10.1111/j.1937-5956.2011.01221.x

Min, D., & Yih, Y. (2010). An elective surgery scheduling problem considering patient priority. Computers & Operations Research, 37(6), 1091–1099. https://doi.org/10.1016/j.cor.2009.09.016

Roberts, C. T., Semb, G., & Shaw, W. C. (1991). Strategies for the advancement of surgical methods in cleft lip and palate. The Cleft Palate-Craniofacial Journal, 28(2), 141–149. https://doi.org/10.1597/1545-1569_1991_028_0141_sftaos_2.3.co_2

Silva, T. A. O., & de Souza, M. C. (2020). Surgical scheduling under uncertainty by approximate dynamic programming. Omega, 95, 102066. https://doi.org/10.1016/j.omega.2019.05.002

Testi, A., Tanfani, E., & Torre, G. (2007). A three-phase approach for operating theatre schedules. Health Care Management Science, 10(2), 163–172. https://doi.org/10.1007/s10729-007-9011-1

Vissers, J. M. H., Adan, I. J. B. F., & Bekkers, J. A. (2005). Patient mix optimization in tactical cardiothoracic surgery planning: a case study. IMA Journal of Management Mathematics, 16(3), 281–304. https://doi.org/10.1093/imaman/dpi023

Downloads

Published

2022-06-30

How to Cite

Wisittipanich, W., Boonmee, C., Khwanngern, K., & Chattinnawat, W. (2022). The Multi-Period Surgical Scheduling with Capacity Constraint: A Mathematical Modelling Approach. International Journal of Global Optimization and Its Application, 1(2), 120–125. https://doi.org/10.56225/ijgoia.v1i2.21

Issue

Section

Articles
Abstract viewed = 111 times