Scheduling elective surgery patients considering time-dependent health urgency: Modeling and solution approaches

被引:18
作者
Eun, Joonyup [1 ]
Kim, Sang-Phil [2 ]
Yih, Yuehwern [3 ,4 ]
Tiwari, Vikram [1 ,5 ,6 ]
机构
[1] Vanderbilt Univ, Med Ctr, Sch Med, Dept Anesthesiol, Nashville, TN 37212 USA
[2] Winona State Univ, Coll Business, Winona, MN 55987 USA
[3] Purdue Univ, Resenstrief Ctr Healthcare Engn, W Lafayette, IN 47907 USA
[4] Purdue Univ, Sch Ind Engn, W Lafayette, IN 47907 USA
[5] Vanderbilt Univ, Med Ctr, Sch Med, Dept Biomed Informat, Nashville, TN 37212 USA
[6] Vanderbilt Univ, Owen Grad Sch Management, Nashville, TN 37212 USA
来源
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE | 2019年 / 86卷
关键词
Scheduling; Operating room planning; Patient health condition; Sample average approximation; Pairwise interchange heuristics; OPERATING-ROOM TIME; PROGRAMMING APPROACH; OPTIMAL ALLOCATION; DECISION-MAKING; SURGICAL SUITES; EFFICIENCY; DEMAND; UNCERTAINTY; QUALITY;
D O I
10.1016/j.omega.2018.07.007
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
This paper describes an operating room planning problem in which patients have different severity levels when they are diagnosed, and patient health condition deteriorates with the increase of waiting time. In addition, uncertainty in surgery durations is incorporated in this problem. A stochastic mixed integer program is proposed to optimize the assignment of surgeries considering the worst patient health condition among all patients waiting for surgeries and total overtime that exceeds the available time durations allotted for surgeries. This paper presents three solution approaches: the sample average approximation method, a fastest ascent local search, and a tabu search. These three solution approaches are evaluated in the computational study and the results show that the tabu search provides effective solutions within reasonable computation times. (C) 2018 Elsevier Ltd. All rights reserved.
引用
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页码:137 / 153
页数:17
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