The Optimized Scheduling of Emergency Supplies in Highways Under Emergencies
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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。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.
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Key words:
- traffic safety /
- emergency supplies schedule /
- multi-objective decision /
- emergency /
- demand urgency
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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 道路破坏程度 模糊型 物资因素 物资短缺程度 模糊型 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 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 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 136 M4 P3 114 M6 23 M7 P4 235 M3 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
G3500
400
357P2 1 021
236M1
M4G4 584 P4 40
544M3
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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