Efficient operating theatre (OT) planning and scheduling contributes substantially to better utilization of a hospitalgh2019;s expensive resources and superior management of its complex operations. This study investigates the OT planning and scheduling problem at both tactical and operational decision levels to meet the hospital administration’s expectations and patients’ satisfaction simultaneously. The main goal is to concurrently allocate surgical specialties to operating rooms by developing a master surgery schedule (MSS), and solve the surgical case assignment problem (SCAP), which assigns a particular surgery day and time block to each elective patient. To minimize the total patients’ clinical condition deterioration, we propose two dynamic programming based heuristic algorithms, a mixed integer programming model (MIP), and an iterated local search (ILS) approach. We perform extensive computational experiments with 1500 instances. The results demonstrate the efficacy of our heuristic algorithms as well as the proposed ILS, which generates high quality solutions across all problem instances with an average optimality gap of 1.51%.
History
Pagination
2373-2380
Location
Canberra, Australian Capital Territory
Start date
2020-12-01
End date
2020-12-04
ISBN-13
9781728125473
Language
eng
Publication classification
E1 Full written paper - refereed
Title of proceedings
SSCI 2020 : Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence
Event
Computational Intelligence. Symposium (2020 : Canberra, Australian Capital Territory)