Abstract: An uncertainty of and a sudden increase in large-scale emergencies can easily lead to the inability to effectively control some areas, and bring great challenges to the distribution of emergency supplies and medical rescue. Multi-stage coverage optimization of location selection for mobile emergency facilities facing large-scale emergencies requires rapid response, effective disposal and loss reduction before the occurrence of emergencies. A comprehensive coverage of disaster-affected areas can be achieved by deploying mobile emergency facilities reasonably at multiple sites in the disaster-affected areas in advance.
This paper explores a mathematical model and location heuristic algorithm of mobile emergency facilities location for large-scale emergencies, which can provide new ideas and methods for the research of related fields. When facing emergencies, a reasonable location and effective deployment of mobile emergency facilities can improve the efficiency of emergency handling and response ability. Therefore, this study has relatively important theoretical and practical significance, which can provide theoretical support and methodological guidance for the research in related fields and the solution of practical problems.
The model in this paper aims to maximize coverage and discusses how to reasonably deploy a certain number of mobile emergency facilities to cover multiple demand points under the condition that mobile emergency facilities fully cover demand points. The location allocation heuristic algorithm is usually more suitable for emergencies such as large-scale natural disasters, and each demand point only needs to be served by a nearby facility, and can provide a good solution in a relatively short computing time. Therefore, the solution steps of the location allocation heuristic algorithm are formed: (1)Select an initial location for each facility. (2)Determine the optimal demand points for facility location allocation. (3)Each group divides the demand points into subgroups with a facility as the center, and deploys the optimal facility location for each subgroup. (4) If any position changes, repeat (2) and (3); if not, stop doing so.
This paper takes Xi’an city in the COVID-19 epidemic as the background, and carries out a site selection for emergency facilities based on population density under the conventional epidemic prevention policy. According to the population density, the centroid of each census area is regarded as representing the total population of the area, and 452 eligible alternative points are selected. The population distribution data of Xi’an city is obtained from GPW-V4. The locations of alternative points are derived from Shaanxi Provincial Health Commission, and the actual distances of alternative points are obtained through DataMap and Amap. The number of initial deployment facilities has a significant impact on the coverage rate of emergency facilities. Policy makers should complete a certain amount of initial deployment of emergency facilities as soon as possible in order to achieve a coverage of areas with high population density as soon as possible. In response to large-scale emergencies, cross-regional coordinated emergency response can often improve the deployment rate of emergency facilities. The follow-up research can focus on how to divide the service demand of mobile facilities more reasonably, and carry out the optimization of emergency service route, so as to further improve the quality of emergency services in large-scale emergencies.

Key words: mobile emergency response, multilevel site selection, incremental facility location, large-scale emergencies

摘要： 大规模突发事件的不确定性和突发性骤增容易导致部分区域无法进行有效管控,同时会对应急物资分配、医疗救援带来极大的挑战。本文以人口密度量化应急需求水平,考虑应急设施的移动变化及应急覆盖范围随设施部署变化情况,构建覆盖范围最大化的应急设施多级选址模型,并通过改进分配定位启发式算法对模型加以求解。实验表明,在资源有限情况下为了提高覆盖范围,可通过允许设施与需求点多级响应来扩大覆盖范围并提高覆盖质量,且在处理大规模突发事件时,移动应急设施的投入数量能明显增加覆盖范围,采取启发式部署相对更为合理。

关键词: 移动应急, 多级选址, 增长性选址, 大规模突发事件