Volume 54, Number 6, November-December 2020
|Page(s)||1757 - 1773|
|Published online||16 September 2020|
Robust capacity planning for accident and emergency services
Warwick Manufacturing Group, The University of Warwick, Coventry CV4 7AL, UK
* Corresponding author: firstname.lastname@example.org
Accepted: 30 November 2019
Accident and emergency departments (A&E) are the first place of contact for urgent and complex patients. These departments are subject to uncertainties due to the unplanned patient arrivals. After arrival to an A&E, patients are categorized by a triage nurse based on the urgency. The performance of an A&E is measured based on the number of patients waiting for more than a certain time to be treated. Due to the uncertainties affecting the patient flow, finding the optimum staff capacities while ensuring the performance targets is a complex problem. This paper proposes a robust-optimization based approximation for the patient waiting times in an A&E. We also develop a simulation optimization heuristic to solve this capacity planning problem. The performance of the approximation approach is then compared with that of the simulation optimization heuristic. Finally, the impact of model parameters on the performances of two approaches is investigated. The experiments show that the proposed approximation results in good enough solutions.
Mathematics Subject Classification: 49 / 90
Key words: Health-care modelling / capacity planning / accident and emergency services / queuing theory / simulation optimization / robust optimization
© EDP Sciences, ROADEF, SMAI 2020
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