A robust LP-based approach for a dynamic surgical case scheduling problem with sterilisation constraints

The purpose of this article is to investigate a practical scheduling problem in which a group of elective surgical cases are scheduled over time, while considering their unpredictable durations and potential delays in the sterilisation of surgical instruments. The primary objectives were to schedule...

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Published inInternational journal of production research Vol. 62; no. 16; pp. 5925 - 5944
Main Authors Al Hasan, H., Guéret, C., Lemoine, D., Rivreau, D.
Format Journal Article
LanguageEnglish
Published London Taylor & Francis 17.08.2024
Taylor & Francis LLC
Subjects
Computer Science
elective surgeries scheduling
Emergency medical services
Hospitals
Integer programming
Linear programming
Mixed integer
mixed-integer linear programming
Operations Research
relax-and-fix heuristic
robust scheduling
Robustness
rolling horizon approach
Scheduling
Sterilization
Surgical instruments
France
Relax-and-fix heuristic
Operations research
elective surgeries scheduling
rolling horizon approach
mixed-integer linear programming
robust scheduling
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Summary:The purpose of this article is to investigate a practical scheduling problem in which a group of elective surgical cases are scheduled over time, while considering their unpredictable durations and potential delays in the sterilisation of surgical instruments. The primary objectives were to schedule the maximum number of surgeries and decrease overtime for the surgical staff, as well as limit the number of instruments requiring emergency sterilisation. The study was conducted in collaboration with the University Hospital of Angers in France, which also contributed historical data for the experiments. We propose two robust mixed integer linear programming models, which are then solved iteratively through a rolling horizon approach, in which the objective functions are taken into account in lexicographic order. Experiments on randomly generated instances indicated which of the two approaches had better performance. Comparison of the results for a real-world scenario involving actual planning at the hospital indicated a greater than 69% decrease in overtime, and a minimum of 92% fewer stressful situations in the sterilising unit.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2024.2304018