轴辐式应急救援网络规划

为了实现对受灾城市的快速支援，同时尽可能降低应急救援网络的建设成本，以应急救援站选址和应急救援通道布局为落脚点，研究了三级轴辐式应急救援网络的多目标规划方法；考虑轴辐式网络的多级结构及应急救援站间的连通关系特征，以三级应急救援站选址、应急救援站间的连通关系及应急救援通道等级为决策变量，以各级应急救援站的建设成本和网络平均救援时间最小为双目标函数，构建三级轴辐式应急救援网络规划模型；结合决策变量的特征为三级轴辐式应急救援网络规划模型设计了三段式编码结构的小生境Pareto遗传算法；依托甘肃省14个城市的公路网络进行应急救援网络的建模求解，验证方法的有效性，并将优化结果与传统三级应急救援网络进行了对比。研究结果表明：三段式编码结构的小生境Pareto遗传算法能够有效求解该轴辐式应急救援网络规划模型；与传统应急救援网络模型的最优解相比，选取的Pareto解方案可使三级轴辐式应急救援网络在应急救援站的建设成本上降低8.3%，在网络平均救援时间上加快了3.5 h，其优化结果可支配传统应急救援网络的最优解。
可见，提出的三级轴辐式应急救援网络规划方法能够兼顾轴辐式网络的集约特性，同时取得更短的应急救援时间。

Hub-and-spoke emergency rescue network planning

In order to achieve the rapid rescue of disaster-stricken cities and simultaneously reduce the construction cost of emergency rescue networks as much as possible, the multi-objective planning method of the three-level hub-and-spoke emergency rescue network was studied by taking the locations of emergency rescue stations and the layout of emergency rescue channels as the foothold. The multi-level structure of the hub-and-spoke network and the characteristics of connection relationship between emergency rescue stations were considered, the locations of three-level emergency rescue stations, the connection relationship between emergency rescue stations, and the level of emergency rescue channels were taken as decision variables, the minimum construction cost of emergency rescue stations at all levels and the minimum average network rescue time were taken as the two objective functions, a three-level hub-and-spoke emergency rescue network planning model was bulit. The niche Pareto genetic algorithm with a three-segment encoding structure for the three-level hub-and-spoke emergency rescue network planning model was designed by combining the characteristics of the decision variables. The emergency rescue network was modelled and solved based on the road network of 14 cities in Gansu Province. The effectiveness of the method was verified, and the optimization results were compared with the traditional three-level emergency rescue network. Research results show that the niche Pareto genetic algorithm with a three-segment encoding structure can effectively solve the hub-and-spoke emergency rescue network planning model.
Compared with the optimal solution of the traditional emergency rescue network model, the selected scheme of the Pareto solution in the three-level hub-and-spoke emergency rescue network can reduce the construction cost of emergency rescue stations by 8.3%, and accelerate the average network rescue time by 3.5 h. The optimization results can dominate the optimal solution of the traditional emergency rescue network. So, the proposed three-level hub-and-spoke emergency rescue network planning method can take into account the intensive characteristics of hub-and-spoke networks and achieve shorter emergency rescue time.