突发事件下公路应急物资调度优化

都雪静; 王爱辉; 孙菲菲

doi:10.3963/j.jssn.1674-4861.2021.04.007

突发事件下公路应急物资调度优化

doi: 10.3963/j.jssn.1674-4861.2021.04.007

1.
东北林业大学交通学院哈尔滨 150040
2.
中国重汽集团济南卡车股份有限公司济南 250000

基金项目:

国家重点研发计划项目 2017YFC0803901

国家自然科学基金项目 51108068

详细信息

通讯作者:
都雪静(1975—), 博士, 教授.研究方向: 交通环境与安全技术.E-mail: duxuejing99@163.com

中图分类号: U116
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出版历程
- 收稿日期: 2021-01-30

The Optimized Scheduling of Emergency Supplies in Highways Under Emergencies

1.
School of Transportation, Northeast Forestry University, Harbin 150040, China
2.
China Heavy-truck Jinan Company Limited, Jinan, 250000, China

摘要

摘要: 为了减少突发事件造成的人身伤亡和财产损失, 考虑事故发生后道路被破坏、应急物资需求量不确定和各事故点需求紧迫度不同的情况, 研究突发事件下公路应急物资调度优化。根据事故后道路破坏状态, 确定救援车辆修正后的行驶速度; 利用三角模糊理论, 将事故点的模糊应急物资需求量转化为确定值; 在传统TOPSIS法的基础上, 利用主客观方法相结合的方法来确定指标的权重, 并且采用B型关联度来客观描述评价对象与正、负理想解之间的距离, 利用改进的TOPSIS法通过以上方法得到各事故点的需求紧迫系数, 以保证配送的公平性。在此基础上, 针对三级调运网络, 建立多目标应急物资调度优化模型, 结合雅安地震实例, 利用带精英策略的快速非支配排序遗传算法(NSGA-Ⅱ)求解模型。研究结果表明: 重大突发事件下, 引入需求紧迫度的公路应急物资调度, 不仅能实现对需求紧迫度较高的事故点优先配送, 而且得到的应急物资调度方案使配送时间节省了21%, 车辆运输成本减少了25%, 物资需求满足度达到100%;同时考虑灾后道路破坏和模糊需求的情况, 使得应急物资调度优化更加符合现实情况。
- 交通安全 /
- 应急物资调度 /
- 多目标决策 /
- 突发事件 /
- 需求紧迫度
Abstract: The optimized scheduling of emergency supplies in highways is studied to reduce personal injury and property loss caused by emergencies. This paper considers the situations of road damage after accidents, uncertain demand for emergency supplies, and different demand urgency of each accident point. According to the states of road damage after an accident, the revised driving speed of the rescue vehicle is determined. The fuzzy emergency supplies demand of the accident spots is transformed into a determined value using triangular fuzzy theory. Based on the traditional TOPSIS method, subjective and objective methods are used to determine the weight of indicators. The type-B correlation degree is used to objectively describe the distance between the evaluation object and ideal solutions. The demand urgency coefficients of each accident point are obtained by the above method to ensure the fairness of scheduling. On this basis, a multi-objective optimization model of emergency supplies schedule is established for the threelevel dispatching network. Taking Ya'an Earthquake as a case study, the fast non-dominant sequential genetic algorithm with the elite strategy(NSGA-Ⅱ)is used to solve the model. The results show that introducing demand urgency into the emergency supplies schedule can realize the priority distribution of accident points with high demand urgency.The emergency supplies scheduling scheme saves the delivery time by 21%, reduces the vehicle transportation cost by 25%, and meets the supplies demand by 100%. Considering the post-disaster road damage and fuzzy demand, the schedule optimization of emergency supplies is more consistent with the actual situation.
- traffic safety /
- emergency supplies schedule /
- multi-objective decision /
- emergency /
- demand urgency

HTML全文

图 1 NSGA-II流程图

Figure 1. NSGA-II flow

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表 1 需求紧迫系数的评价指标体系

Table 1. Evaluation indicators system of the critical ratios of demands

一级指标	二级指标	二级指标类型
环境因素	建筑物破坏程度	模糊型
环境因素	道路破坏程度	模糊型
物资因素	物资短缺程度	模糊型
物资因素	物资调运困难程度	模糊型
人口因素	受伤人数	确定型
	受灾人数	确定型
	人口密度	确定型

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表 2 事故点的基础数据

Table 2. Basic data of accident spots

事故点	建筑物破坏程度	道路破坏程度	地震烈度/级	物资短缺程度	物资调运困难程度	人口密度/（万人/km²）	受伤人数/人	受灾人数/万人
M₁	很严重	很严重	9	很严重	很难	0.010 2	5 537	8.00
M₂	很严重	很严重	8	很严重	很难	0.001 9	2 500	5.80
M₃	严重	一般	8	很严重	很难	0.006 4	811	7.00
M₄	严重	一般	7	严重	难	0.045 0	607	12.50
M₅	严重	严重	7	很严重	难	0.032 6	1 109	15.00
M₆	严重	一般	7	很严重	一般	0.008 6	341	10.00
M₇	一般	轻	6	严重	一般	0.014 9	32	9.22
M₈	轻	很轻	6	严重	容易	0.045 5	152	12.43
M₉	轻	轻	6	严重	容易	0.036 3	100	7.15

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表 3 配送中心到事故点的设计速度和修正系数

Table 3. Design speed and correction coefficient from distribution centers to accident spots

事故点	设计速度/（km/h）				车道宽度修正系数				服务等级修正系数				公路破坏修正系数
事故点	P₁	P₂	P₃	P₄	P₁	P₂	P₃	P₄	P₁	P₂	P₃	P₄	P₁	P₂	P₃	P₄
M₁	100	90	60	80	1				0.815	0.818	0.811	0.811	0.35
M₂	80	80	60	70	1				0.815	0.817	0.813	0.811	0.35
M₃	100	90	70	80	1				0.857	0.857	0.857	0.859	0.70
M₄	100	90	70	70	1				0.857	0.859	0.853	0.855	0.70
M₅	70	90	70	70	1				0.840	0.847	0.849	0.847	0.45
M₆	80	90	70	60	1				0.857	0.853	0.851	0.853	0.70
M₇	80	90	50	70	1				0.869	0.862	0.862	0.865	0.90
M₈	90	80	80	40	1				0.869	0.864	0.858	0.868	1.00
M₉	70	70	80	40	1				0.869	0.869	0.869	0.869	0.90

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表 4 各事故点的应急物资需求量

Table 4. Demands for emergency supplies at each accident point

事故点	需求量/t
M₁	1 475
M₂	325
M₃	275
M₄	372
M₅	847
M₆	114
M₇	23
M₈	88
M₉	51

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表 5 供应中心和配送中心的可供应物资量

Table 5. Quantity of supplies available at supply centers and distribution centers

供应中心	供应量/t	配送中心	供应量/t
G₁	1 300	P₁	465
G₂	1 200	P₂	289
G₃	1 200	P₃	708
G₄	1 100	P₄	201

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表 6 配送中心与事故点、供应中心之间的距离

Table 6. Distances among distribution centers, accident spots, supply centers

事故点或供应中心	与配送中心距离/km
事故点或供应中心	P₁	P₂	P₃	P₄
G₁	1 031	1 044	1 239	1 055
G₂	815	827	1 055	897
G₃	1 177	1 187	1 397	1 240
G₄	930	931	682	770
M₁	145	133	159	118
M₂	175	162	189	147
M₃	144	131	158	116
M₄	99	86	152	87
M₅	109	95	145	86
M₆	149	133	108	123
M₇	207	194	48	179
M₈	54	41	200	63
M₉	86	69	205	40

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表 7 应急物资配送方案

Table 7. Emergency supplies distribution scheme

配送中心	运输量/t	事故点
P₁	301	M₁
	268	M₂
	88	M₈
	51	M₉
P₂	153	M₁
P₂	136	M₄
P₃	114	M₆
P₃	23	M₇
P₄	235	M₃
P₄	303	M₅

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表 8 应急物资调运方案

Table 8. Emergency supplies transfer scheme

供应中心	运输量/t	配送中心	运输量/t	事故点
G₁	57	P₁	57	M₂
G₁ G₂ G₃	500 400 357	P₂	1 021 236	M₁ M₄
G₄	584	P₄	40 544	M₃ M₅

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表 9 优化前后各目标函数值及比较

Table 9. Comparison before and after optimization

对比因素	配送时间/h	运输成本/万元	物资缺失度
优化前	103	76	4.3
优化后	81	57	0
优化比例/%	21	25	100

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