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Optimization methods for a stochastic surgery planning problem

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  • Lamiri, Mehdi
  • Grimaud, Frédéric
  • Xie, Xiaolan

Abstract

The purpose of this paper is to propose and compare several optimization methods for elective surgery planning when operating room (OR) capacity is shared by elective and emergency surgery. The planning problem is considered as a stochastic optimization problem in order to minimize expected overtime costs and patients' related costs. An "almost" exact method combining Monte Carlo simulation and mixed integer programming is presented, and its convergence properties are investigated. Several heuristic and meta-heuristic methods are then proposed. Numerical experimentations are conducted to compare the performance of different optimization methods.

Suggested Citation

  • Lamiri, Mehdi & Grimaud, Frédéric & Xie, Xiaolan, 2009. "Optimization methods for a stochastic surgery planning problem," International Journal of Production Economics, Elsevier, vol. 120(2), pages 400-410, August.
  • Handle: RePEc:eee:proeco:v:120:y:2009:i:2:p:400-410
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    Cited by:

    1. Freeman, Nickolas & Zhao, Ming & Melouk, Sharif, 2018. "An iterative approach for case mix planning under uncertainty," Omega, Elsevier, vol. 76(C), pages 160-173.
    2. Gartner, Daniel & Kolisch, Rainer, 2014. "Scheduling the hospital-wide flow of elective patients," European Journal of Operational Research, Elsevier, vol. 233(3), pages 689-699.
    3. Chang, Kuo-Hao & Cuckler, Robert & Lee, Song-Lin & Lee, Loo Hay, 2022. "Discrete conditional-expectation-based simulation optimization: Methodology and applications," European Journal of Operational Research, Elsevier, vol. 298(1), pages 213-228.
    4. Ben Bachouch, Rym & Guinet, Alain & Hajri-Gabouj, Sonia, 2012. "An integer linear model for hospital bed planning," International Journal of Production Economics, Elsevier, vol. 140(2), pages 833-843.
    5. 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.
    6. Cappanera, Paola & Visintin, Filippo & Banditori, Carlo, 2014. "Comparing resource balancing criteria in master surgical scheduling: A combined optimisation-simulation approach," International Journal of Production Economics, Elsevier, vol. 158(C), pages 179-196.
    7. Serhat Gul & Brian T. Denton & John W. Fowler, 2015. "A Progressive Hedging Approach for Surgery Planning Under Uncertainty," INFORMS Journal on Computing, INFORMS, vol. 27(4), pages 755-772, November.
    8. Zhang, Jian & Dridi, Mahjoub & El Moudni, Abdellah, 2019. "A two-level optimization model for elective surgery scheduling with downstream capacity constraints," European Journal of Operational Research, Elsevier, vol. 276(2), pages 602-613.
    9. 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.
    10. Saremi, Alireza & Jula, Payman & ElMekkawy, Tarek & Wang, G. Gary, 2013. "Appointment scheduling of outpatient surgical services in a multistage operating room department," International Journal of Production Economics, Elsevier, vol. 141(2), pages 646-658.
    11. Francesca Guerriero & Rosita Guido, 2011. "Operational research in the management of the operating theatre: a survey," Health Care Management Science, Springer, vol. 14(1), pages 89-114, March.
    12. 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.
    13. Gréanne Leeftink & Erwin W. Hans, 2018. "Case mix classification and a benchmark set for surgery scheduling," Journal of Scheduling, Springer, vol. 21(1), pages 17-33, February.
    14. Silva, Thiago A.O. & de Souza, Mauricio C., 2020. "Surgical scheduling under uncertainty by approximate dynamic programming," Omega, Elsevier, vol. 95(C).
    15. Mengyu Guo & Su Wu & Binfeng Li & Jie Song & Youping Rong, 2016. "Integrated scheduling of elective surgeries and surgical nurses for operating room suites," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 166-181, June.
    16. 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.
    17. Michael Samudra & Erik Demeulemeester & Brecht Cardoen & Nancy Vansteenkiste & Frank E. Rademakers, 2017. "Due time driven surgery scheduling," Health Care Management Science, Springer, vol. 20(3), pages 326-352, September.
    18. 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.
    19. Vijayakumar, Bharathwaj & Parikh, Pratik J. & Scott, Rosalyn & Barnes, April & Gallimore, Jennie, 2013. "A dual bin-packing approach to scheduling surgical cases at a publicly-funded hospital," European Journal of Operational Research, Elsevier, vol. 224(3), pages 583-591.

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