A simulation optimisation on the hierarchical health care delivery system patient flow based on multi-fidelity models
针对中国城市医疗系统患者流分布不匹配问题，提出一种基于多保真度优化与序变换和最优采样的模拟优化方法，通过低保真排队网络模型和高保真离散事件模拟优化系统利润，实证表明该方法能有效节省计算资源。
The mismatching patient flow distribution in the health care system in urban China is a great social issue that attracts lots of public attention. In this research, we propose a simulation-based optimisation method using the multi-fidelity optimisation with ordinal transformation (OT) and optimal sampling (OS) () algorithm to evaluate the patient flow distribution, so as to continuously improve the hierarchical health care service system. The low-fidelity model applying the queueing network theory is constructed for the OT part of the , followed by a high-fidelity but time-consuming discrete event simulation model for the OS part. An empirical study on the background of the hierarchical health care delivery system in China is presented, where the proposed method is implemented to optimise the system profit by guiding the patient flow distribution. A comparison with other widely used simulation optimisation methods sustains the efficacy of the with the evidence that acquiring effective information from the low-fidelity model indeed retrenches the computing budget used to explore the feasible domain.