Train Operation Adjustment Optimization Considering Transfer Under Influence of Railway Line Fault
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摘要:
针对线路故障影响下考虑转线换乘的列车运行调整问题，以线路故障触发的列车连带总晚点时间最短与转线换乘失败客流数最少为双重目标，构建铁路线路故障影响下的列车运行调整优化模型；鉴于模型为大规模混合整数规划模型，设计基于高斯游走的改进粒子群求解策略；以京广高铁上行方向部分区段和郑徐高铁下行方向部分区段构成的路网构建测试场景，并运用IPS&GW算法对不同列车运行恢复策略下（策略Ⅰ～策略Ⅳ）的列车运行调整优化模型进行求解. 结果表明：相较策略Ⅰ，故障扰动时长在10～30 min之间波动时，策略Ⅱ、Ⅲ、Ⅳ所产生的列车连带晚点时间分别下降82.5%～86.6%、70.5%～81.49%、55.8%～58.7%，滞留旅客总数分别下降28.3%～39.1%、57.3%～61.9%、88.4%～89.4%；且在不同扰动情景下均能通过增加一定的列车总晚点时间来换取换乘失败旅客数量的明显减少. 将本文所提出的IPS&GW算法与传统PSO （particle swarm optimization）算法进行对比，前者在目标函数收敛速度方面表现出优势，且能够达到恢复列车图定运行要求、减少换乘枢纽站滞留旅客数量.
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关键词:
- 连带晚点 /
- 铁路运输 /
- 旅客转线换乘 /
- 列车运行调整；启发式算法
Abstract:Because of the train operation adjustment considering transfer under the railway line faults, minimizing the total train knock-on delay time and the number of passengers failing to transfer caused by railway line faults was taken as two objectives, and an optimization model for train operation adjustment under the influence of railway line faults was constructed. In light of the model as a large-scale hybrid integer programming model, an improved particle swarm based on Gaussian walk (IPS&GW) was designed. Road network composed of some upward-direction sections of the Beijing–Guangzhou Railway and downward-direction sections of the Zhengzhou–Xuzhou Railway was used to form a testing scenario. The proposed IPS&GW algorithm was used to solve the optimization model for train operation adjustment based on different train operation recovery strategies (strategy Ⅰ–strategy Ⅳ). The results show that compared to strategy Ⅰ, when the disturbance duration of railway line fault ranges from 10 to 30 minutes, the decreasing ratio of train knock-on delay time based on strategies Ⅱ, Ⅲ, and Ⅳ is respectively in the range from 82.5% to 86.6%, from 70.5% to 81.49%, and from 55.8% to 58.7%. The decreasing ratio of the total number of stranded passengers is respectively in the range from 28.3% to 39.1%, from 57.3% to 61.9%, and from 88.4% to 89.4%. Under different disturbance scenarios, a significant decrease in the number of passengers failing to transfer can be achieved by increasing the total train delay time by a certain amount. Finally, the proposed IPS&GW algorithm is compared with the traditional particle swarm optimization (PSO) algorithm. The former shows an advantage in the convergence speed of the objective function, so that the scheduled operation requirements for the train can be met, and the number of stranded passengers in the transfer hub stations is reduced.
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图 1 基于前程线路故障扰动的旅客转线换乘机制
Figure 1. Passenger transfer mechanism based on disturbance of previous line faults
图 3 京广高铁衡阳东—邯郸东区段的图定列车运行线
Figure 3. Scheduled operation line of Hengyang East–Handan east section of Beijing–Guangzhou high-speed railway
图 4 郑徐高铁郑州东—徐州东区段的图定列车运行线
Figure 4. Scheduled operation line of Zhengzhou East–Xuzhou East section of Zhengzhou–Xuzhou high-speed railway
图 5 4种列车运行恢复策略下的沿途车站晚点时间
Figure 5. Histogram of station delay times along route under four train operation recovery strategies
图 6 4种列车运行恢复策略下的换乘失败客流数
Figure 6. Histogram of number of passengers failing to transfer under four train operation recovery strategies
图 7 不同故障扰动时长下列车总晚点时间的变化趋势
Figure 7. Variation trend in total train delay time under different fault disturbance durations
图 8 不同故障扰动时长下换乘失败客流数的变化趋势
Figure 8. Variation trend in number of passengers failing to transfer under faalt different fault disturbance durations
图 9 2种算法对基于策略Ⅲ的列车运行调整模型求解得到的目标函数值收敛曲线
Figure 9. Convergence curves of objective function values obtained from solving train operation adjustment model by two algorithms based on strategy Ⅲ
图 10 2种算法对基于策略Ⅳ的列车运行调整模型求解得到的目标函数值收敛曲线
Figure 10. Convergence curves of objective function values obtained from train operation adjustment model by two algorithms based on strategy Ⅳ
表 1 衡阳东—邯郸东区段和郑州东—徐州东区段相关数据
Table 1. Relevant data for Hengyang East–Handan East section and Zhengzhou East–Xuzhou East section
区段 站点 到发线
数量/条区间距离/
km区间纯运行
时分/min京广高铁 衡阳东站 5 株洲西站 6 125 21 长沙南站 1 52 10 岳阳东站 2 147 29 赤壁北站 1 87 16 咸宁北站 2 43 8 武汉站 6 85 16 孝感北站 3 126 21 信阳东站 6 73 17 驻马店西站 2 118 20 漯河西站 3 64 15 许昌东站 4 64 16 郑州东站 12 91 20 新乡东站 4 67 16 鹤壁东站 1 64 15 安阳东站 3 46 9 邯郸东站 4 60 15 郑徐高铁 郑州东站 12 开封北站 4 52 12 兰考南站 4 53 12 商丘站 7 85 20 砀山南站 4 62 15 萧县北站 6 67 16 徐州东站 13 41 10 
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表 2 不同故障扰动情景下列车总晚点时间与换乘失败客流数的结果分析
Table 2. Result analysis of total train delay time and number of passengers failing to transfer under different fault disturbance scenarios
故障情景 扰动时长/min 列车晚点总时间/min 换乘失败客流数/人 策略Ⅰ 策略Ⅱ 策略Ⅲ 策略Ⅳ 策略Ⅰ 策略Ⅱ 策略Ⅲ 策略 Ⅳ 情景 1 10 5100 684 1096 2187 302 184 129 35 20 6500 982 1203 2876 396 288 153 42 30 7800 1363 2301 3223 489 315 186 54 情景 2 10 1920 410 812 1324 204 122 101 12 20 3450 781 1060 2209 298 200 126 23 30 5430 1145 1687 2535 365 261 163 39 情景 3 10 1260 366 708 1051 119 86 71 8 20 2190 571 953 1404 177 153 96 17 30 3810 958 1390 1922 228 184 137 28
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