A two-step stochastic approach for operating rooms scheduling in multi-resource environment

被引:13
|
作者
Atighehchian, Arezoo [1 ]
Sepehri, Mohammad Mehdi [2 ]
Shadpour, Pejman [3 ]
Kianfar, Kamran [4 ]
机构
[1] Univ Isfahan, Fac Adm Sci & Econ, Dept Management, Esfahan 8174673441, Iran
[2] Tarbiat Modares Univ, Dept Ind Engn, Tehran 1411713114, Iran
[3] Iran Univ Med Sci, Hosp Management Res Ctr, Hasheminejad Kidney Ctr, Tehran, Iran
[4] Univ Isfahan, Fac Engn, Esfahan 8174673441, Iran
关键词
Operating room; Scheduling; Two-stage stochastic programming; L-shaped algorithm; DEMAND;
D O I
10.1007/s10479-019-03353-5
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Planning and scheduling of operating rooms (ORs) is important for hospitals to improve efficiency and achieve high quality of service. Due to significant uncertainty in surgery durations, scheduling of ORs can be very challenging. In this paper, surgical case scheduling problem with uncertain duration of surgeries in multi resource environment is investigated. We present a two-stage stochastic mixed-integer programming model, named SOS, with the objective of total ORs idle time and overtime. Also, in this paper a two-step approach is proposed for solving the model based on the L-shaped algorithm. Proposing the model in a multi resources environment with considering real-life limitations in academic hospitals and developing an approach for solving this stochastic model efficiently form the main contributions of this paper. The model is evaluated through several numerical experiments based on real data from Hasheminejad Kidney Center (HKC) in Iran. The solutions of SOS are compared with the deterministic solutions in several real instances. Numerical results show that SOS enjoys a better performance in 97% of the cases. Furthermore, the results of comparing with actual schedules applied in HKC reveal a notable reduction of OR idle time and over time which illustrate the efficiency of the proposed model in practice.
引用
收藏
页码:191 / 214
页数:24
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