轴辐式应急救援网络规划

马昌喜; 石褚巍; 杜波

doi:10.19818/j.cnki.1671-1637.2023.03.015

轴辐式应急救援网络规划

doi: 10.19818/j.cnki.1671-1637.2023.03.015

马昌喜^{1, 2,},
石褚巍^{1, 3, ,},
杜波⁴

1.
兰州交通大学交通运输学院，甘肃兰州 730070
2.
兰州交通大学高原铁路运输智慧管控铁路行业重点实验室，甘肃兰州 730070
3.
兰州财经大学信息工程学院，甘肃兰州 730020
4.
伍伦贡大学智能基础设施研究中心，新南威尔士伍伦贡 2522

基金项目:

国家自然科学基金项目 52062027

甘肃省"双一流"科研重点项目 GSSYLXM-04

兰州财经大学科研项目 Lzufe2020D-003

甘肃省基础研究计划 22JR4ZA035

甘肃省省级科技计划项目 22ZD6GA010

兰州交通大学基础拔尖计划项目 2022JC02

详细信息

作者简介:
马昌喜(1979-)，男，湖北汉川人，兰州交通大学教授，工学博士，从事交通运输系统优化与设计研究

通讯作者:
石禇巍(1992-)，男，甘肃合作人，兰州财经大学讲师，兰州交通大学管理学博士研究生

中图分类号: U113
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出版历程
- 收稿日期: 2022-12-19
- 网络出版日期: 2023-07-07
- 刊出日期: 2023-06-25

Hub-and-spoke emergency rescue network planning

MA Chang-xi^{1, 2
,},
SHI Chu-wei^{1, 3
, ,},
DU Bo⁴

1.
School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China
2.
Key Laboratory of Railway lndustry on Plateau Railway Transportation Intelligent Management and Control, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China
3.
School of Information Engineering, Lanzhou University of Finance and Economics, Lanzhou 730020, Gansu, China
4.
SMART Infrastructure Facility, University of Wollongong, Wollongong 2522, New South Wales, Australia

Funds:

National Natural Science Foundation of China 52062027

"Double-First Class" Major Research Programs of Gansu Province GSSYLXM-04

Scientific Research Project of Lanzhou University of Finance and Economics Lzufe2020D-003

Gansu Basic Research Plan 22JR4ZA035

Provincial Science and Technology Project of Gansu Province 22ZD6GA010

Basic Research Top Talents Training Program of Lanzhou Jiaotong University 2022JC02

More Information

Author Bio:
MA Chang-xi(1979-), male, professor, PhD, machangxi@mail.lzjtu.cn

SHI Chu-wei(1992-), male, assistant prefessor, doctoral student, 13220008@stu.lzjtu.edu.cn

摘要

摘要: 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。
- 交通规划 /
- 轴辐式应急救援网络 /
- 多目标规划 /
- 应急救援站 /
- 应急救援通道 /
- 平均救援时间 /
- 小生境Pareto遗传算法
Abstract: 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.
- transportation planning /
- hub-and-spoke emergency rescue network /
- multi-objective planning /
- emergency rescue station /
- emergency rescue channel /
- average rescue time /
- niche Pareto genetic algorithm

HTML全文

图 1 三级轴辐式应急救援网络

Figure 1. Three-level hub-and-spoke emergency rescue network

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图 2 受灾节点被救援

Figure 2. Disaster-stricken node being rescued

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图 3 染色体编码示例

Figure 3. Chromosome encoding example

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图 4 算法流程

Figure 4. Flow of algorithm

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图 5 初始种群分布

Figure 5. Initial population distribution

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图 6 进化300代后种群分布

Figure 6. Population distribution after 300 evolution generations

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图 7 Pareto解2对应的轴辐式应急救援网络

Figure 7. Hub-and-spoke emergency rescue network of Pareto solution 2

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表 1 城市间距离

Table 1. Distances between cities km

节点城市	兰州	嘉峪关	金昌	白银	天水	武威	张掖	平凉	酒泉	庆阳	定西	陇南	临夏州	甘南州
兰州	0.0	735.7	369.5	80.4	307.0	274.4	507.5	317.5	711.6	478.5	106.4	548.8	140.1	230.1
嘉峪关		0.0	442.6	761.2	1 028.2	464.2	225.9	1 039.0	21.6	1 200.2	827.5	1 369.9	856.3	947.2
金昌			0.0	400.9	667.9	97.5	219.1	678.3	423.1	848.1	467.2	903.6	496.0	586.8
白银				0.0	378.3	304.9	538.4	388.5	742.1	574.4	177.8	613.8	213.6	304.4
天水					0.0	572.1	805.3	241.3	1 009.3	400.1	204.3	249.3	342.0	432.8
武威						0.0	240.5	591.1	444.6	754.2	371.4	807.8	400.2	491.1
张掖							0.0	815.5	207.2	985.0	604.4	1 046.7	633.2	724.0
平凉								0.0	1019.5	163.3	228.9	468.5	441.7	532.5
酒泉									0.0	1 189.4	808.7	1 251.1	837.6	928.4
庆阳										0.0	389.9	615.2	602.5	693.3
定西											0.0	445.2	230.8	321.6
陇南												0.0	566.0	354.0
临夏州													0.0	103.8
甘南州														0.0

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表 2 三组Pareto解的目标函数值

Table 2. Objective function values of 3 sets of Pareto solutions

目标值	Pareto解1	Pareto解2	Pareto解3
网络平均救援时间/h	131.7	137.7	180.2
应急救援站建设成本/亿元	17.5	16.5	15.5

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表 3 两种应急救援网络的最优方案对比

Table 3. Comparison of optimal schemes of two emergency rescue networks

目标值	三级轴辐式应急救援网络最优方案	传统三级应急救援网络最优方案
网络平均救援时间/h	137.7	141.2
应急救援站建设成本/亿元	16.5	18.0

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