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1339. INTRA-DAY OPTIMIZATION OF THE SURGICAL SUITE: ALLOCATING AND SEQUENCING SURGICAL CASES
Invited abstract in session TB-10: Surgery Scheduling and Operating Room Planning, stream OR in Health Services (ORAHS).
Tuesday, 10:30-12:00Room: 11 (building: 116)
Authors (first author is the speaker)
1. | TAHA HUZEYFE AKTAS
|
Business Analytics, Amsterdam Business School | |
2. | Alex Kuiper
|
Business Analytics, University of Amsterdam |
Abstract
Limited resources in healthcare give rise to efficient use of resources. As operating rooms (ORs) and associated resources are dominant factors in the hospital’s operational cost, our aim is to improve surgery scheduling. Considering Leeftink, G. & Hans, E.W. (2018) as our starting point – a large benchmark of surgery scheduling problems – our objective is to improve the scheduling by taking uncertainty about surgery durations into our approach. The motivation stems from the observation that in the literature, most studies tend to focus solely on specific cases of the surgery scheduling problem or operate under deterministic assumptions contrary to the problem's nature.
Note that the classical problem is twofold: first, one needs to decide which procedures are done on which OR, and second, in which order do the procedures need to be scheduled. We propose a mathematical formula that merges applied probability and mixed-integer programming to minimize overtime and idle time. We demonstrate how our solution approach can be adapted to specific cases and integrated with additional constraints. We show superior results compared to the ones that simply assumed deterministic service times, and we also contrast them to scheduling rules. This underpins the importance of taking variation into account. Furthermore, our experiments show that even with a limited degree of information about the uncertainty, the performance of the surgery schedule can be considerably improved.
Keywords
- Health Care
- Scheduling
- Stochastic Optimization
Status: accepted
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