Robust capacity planning for accident and emergency services

Elvan Gokalp

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)
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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.
Original languageEnglish
Pages (from-to)1757-1773
Number of pages17
JournalRAIRO - Operations Research
Issue number6
Early online date16 Sept 2020
Publication statusPublished - 30 Nov 2020


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