摘要
新冠肺炎疫情爆发后,全国各地大量的医护人员驰援武汉,对于收治新冠肺炎患者的各个医院来说,提前预测其每个阶段医护人员与患者对食物方面的需求并及时送达,是有效开展应急救援工作的基本保障。本文通过建立SEIRD系统动力学模型对疫情的变化趋势进行刻画,进而预测出相应的应急物资需求;在此基础上,提出并设计以应急时效性为目标的动态多周期应急物流网络优化模型并运用遗传算法进行求解,从而确定每个周期内最优的应急设施选址,以解决应急救援过程中对医院医护人员与患者的食物配送问题。研究结果表明,应急设施选址需结合疫情的变化进行动态调整,这样更有利于减少不必要的资源浪费,同时又能保证应急救援的效率。
As a result of the COVID-19 outbreak,a large number of medical workers from all over the country to support Wuhan.For the hospitals receiving COVID-19 patients,predicting the food requirements of medical workers and patients previously and delivering them in time is the basic guarantee for effective emergency rescue.In this paper,the SEIRD dynamics model was established to predict the variation trend of the epidemic,and further to forecast of demand for emergency supplies.Then we put forward a multi-cycle optimization model for emergency timeliness as the goal of the dynamic emergency logistics network to determine the optimal emergency facilities in each decision-cycle.The model is solved by genetic algorithm.The process of emergency rescue for food delivery of hospital medical staff and patients can be solved.The test result demonstrates that the site selection of emergency facilities is dynamically adjusted with the variety of the COVID-19 epidemic,which is more conducive to reducing the waste of resources and ensuring the efficiency of emergency rescue.
作者
刘明
连靖萱
LIU Ming;LIAN Jingxuan(School of Economics and Management,Nanjing University of Science and Technology,Nanjing,Jiangsu,210094)
出处
《南京理工大学学报（社会科学版）》
2020年第5期57-64,共8页
Journal of Nanjing University of Science and Technology：Social Sciences
基金
国家自然科学基金项目“基于数据驱动的突发疫情应急物资在线实时调度优化理论方法研究”(项目编号:71771120)
教育部人文社科基金项目“数据驱动环境下的突发疫情应急物资在线智能调度建模与优化研究”(项目编号:17YJA630058)
中央高校基本科研业务费专项资金资助项目“数据驱动的新冠肺炎疫情扩散规律分析及应急管控政策研究”(项目编号:30920010019)。
