Simulation data for paper Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy

Simulation data of patient reallocation over hospitals or regions. Research objective: determining the benefits of regional re-allocation of COVID-19 patients using stochastic approximation and stochastic programming, type of research: simulation study, method of data collection: simulations, type of data: R datasets

本数据集为面向医院或区域间患者重新调配的仿真数据。该数据集对应的研究目标为：借助随机逼近（stochastic approximation）与随机规划（stochastic programming）方法，量化评估新冠（COVID-19）患者实施区域重新调配所能带来的效益。研究类型为仿真研究；数据采集方式为仿真实验；数据类型为R数据集（R datasets）。