A new medical staff allocation via simulation optimisation for an emergency department in Hong Kong

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

3 Scopus Citations
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Original languageEnglish
Pages (from-to)6004-6023
Journal / PublicationInternational Journal of Production Research
Issue number19
Online published16 Sep 2019
Publication statusPublished - Oct 2020


Whether triage targets can be achieved has been an imperative assessment of service qualities for an emergency department in healthcare management. In this research, we focus on triage targets and try to fully meet the target of fast emergency response for critical patients subject to triage requirements for other category patients by optimising the medical staff allocation in the emergency department. Main challenges stem from multiple stochastic constraints and the time-consuming simulation. To solve the stochastically constrained discrete optimisation via simulation problem, we develop a discrete-event simulation model and propose a simulated-annealing-based algorithm called ConSA that adopts a special searching mechanism and an efficient simulation budget allocation rule to find a high-quality configuration of medical staff. A case study based on the data from a public hospital in Hong Kong is carried out. Numerical experiments demonstrate that our algorithm leads to a 38.28% improvement in the main performance compared to the current staff allocation and dominates other algorithms in terms of computational efficiency and output accuracy. It indicates that our method is a good decision tool for hospital managers.

Research Area(s)

  • discrete optimisation via simulation, healthcare management, medical resource allocation, simulated annealing, stochastic constraint