Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 137-153 |
| Number of pages | 17 |
| Journal | Omega (United Kingdom) |
| Volume | 86 |
| DOIs | |
| Publication status | Published - 2019 Jul 1 |
| Externally published | Yes |
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Keywords
- Operating room planning
- Pairwise interchange heuristics
- Patient health condition
- Sample average approximation
- Scheduling
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Information Systems and Management
Cite this
Scheduling elective surgery patients considering time-dependent health urgency : Modeling and solution approaches. / Eun, Joonyup; Kim, Sang Phil; Yih, Yuehwern; Tiwari, Vikram.
In: Omega (United Kingdom), Vol. 86, 01.07.2019, p. 137-153.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Scheduling elective surgery patients considering time-dependent health urgency
T2 - Modeling and solution approaches
AU - Eun, Joonyup
AU - Kim, Sang Phil
AU - Yih, Yuehwern
AU - Tiwari, Vikram
PY - 2019/7/1
Y1 - 2019/7/1
N2 - 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.
AB - 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.
KW - Operating room planning
KW - Pairwise interchange heuristics
KW - Patient health condition
KW - Sample average approximation
KW - Scheduling
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UR - http://www.scopus.com/inward/citedby.url?scp=85050987413&partnerID=8YFLogxK
U2 - 10.1016/j.omega.2018.07.007
DO - 10.1016/j.omega.2018.07.007
M3 - Article
AN - SCOPUS:85050987413
VL - 86
SP - 137
EP - 153
JO - Omega (United Kingdom)
JF - Omega (United Kingdom)
SN - 0305-0483
ER -