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A Stochastic Surgery Sequencing Model Considering the Moral and Human Virtues

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  • Gerami Farzad
  • Saidi Mehrabad Mohammad

Abstract

In this research, we will work sequencing problem of patients demanding surgery under uncertainty in times (including the surgical time, time to prepare the operating room, patient awake time before transferring to the recovery room …). For this problem, a stochastic mixed integer programming model as Stochastic Surgery Sequencing Model (S3M) has been developed.Since this model is achance-constraint problem, which makes it very complex. This problem aims to minimize the cost of operating room personnel overtime and to reduce patient’s waiting time. In mathematical schedule models, we consider three level of patient’s priority ( ). Based on these moral and human dimensions, decision maker can prioritize patients. Restrictions on the balance the operating roomsand priorities for patients are all from the real-world constraints, are included in this issue. A branch-reduce-cut algorithm is used to solve the model.

Suggested Citation

  • Gerami Farzad & Saidi Mehrabad Mohammad, 2016. "A Stochastic Surgery Sequencing Model Considering the Moral and Human Virtues," Modern Applied Science, Canadian Center of Science and Education, vol. 10(9), pages 1-68, September.
    • Handle: RePEc:ibn:masjnl:v:10:y:2016:i:9:p:68
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    References listed on IDEAS

    as
    1. Brian Denton & James Viapiano & Andrea Vogl, 2007. "Optimization of surgery sequencing and scheduling decisions under uncertainty," Health Care Management Science, Springer, vol. 10(1), pages 13-24, February.
    2. Belien, Jeroen & Demeulemeester, Erik, 2007. "Building cyclic master surgery schedules with leveled resulting bed occupancy," European Journal of Operational Research, Elsevier, vol. 176(2), pages 1185-1204, January.
    3. Cardoen, Brecht & Demeulemeester, Erik & Beliën, Jeroen, 2010. "Operating room planning and scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 201(3), pages 921-932, March.
    4. Sakine Batun & Brian T. Denton & Todd R. Huschka & Andrew J. Schaefer, 2011. "Operating Room Pooling and Parallel Surgery Processing Under Uncertainty," INFORMS Journal on Computing, INFORMS, vol. 23(2), pages 220-237, May.
    5. 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.
    6. Belií«n, Jeroen & Demeulemeester, Erik, 2008. "A branch-and-price approach for integrating nurse and surgery scheduling," European Journal of Operational Research, Elsevier, vol. 189(3), pages 652-668, September.
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    Cited by:

    1. Masoud Eshghali & Devika Kannan & Navid Salmanzadeh-Meydani & Amir Mohammad Esmaieeli Sikaroudi, 2024. "Machine learning based integrated scheduling and rescheduling for elective and emergency patients in the operating theatre," Annals of Operations Research, Springer, vol. 332(1), pages 989-1012, January.

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    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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