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铁路专用线取送车问题的帕累托前沿分析

郑亚晶,  张德坤

郑亚晶, 张德坤. 铁路专用线取送车问题的帕累托前沿分析[J]. 西南交通大学学报. doi: 10.3969/j.issn.0258-2724.20240464
引用本文: 郑亚晶, 张德坤. 铁路专用线取送车问题的帕累托前沿分析[J]. 西南交通大学学报. doi: 10.3969/j.issn.0258-2724.20240464
ZHENG Yajing, ZHANG Dekun. Pareto Frontier Analysis of Placing-in and Taking-out Wagons on Railway Sidings[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20240464
Citation: ZHENG Yajing, ZHANG Dekun. Pareto Frontier Analysis of Placing-in and Taking-out Wagons on Railway Sidings[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20240464

铁路专用线取送车问题的帕累托前沿分析

doi: 10.3969/j.issn.0258-2724.20240464
基金项目: 国家自然科学基金项目(52072128)
详细信息
    作者简介:

    郑亚晶(1982—),男,博士,讲师,研究方向为轨道交通运输组织优化. E-mail:ctyjzheng@scut.edu.cn

  • 中图分类号: U292.2

Pareto Frontier Analysis of Placing-in and Taking-out Wagons on Railway Sidings

Funds: Supported by the National Natural Science Foundation of China(52072128)
  • 摘要:

    为兼顾铁路专用线取车、送车和调移作业中的多目标优化需求,并为取送车作业方案选择提供决策依据,构建以混合型布置形式专用线为对象的两层级优化模型,第一层级最小化调机走行总时间,第二层级在保证第一层级最优的前提下,同时最小化专用线入线车小时消耗和走行车辆公里数. 为求解该模型,设计多目标模拟退火算法:首先,利用单目标模拟退火算法求解仅覆盖调移需求装卸站的最短路径;然后,依据混合型专用线分层特性构造插入算子,将剩余取送车需求装卸站插入最短路径,形成满足调机走行总时间最小的初始方案;最后,将道岔及货运站视为根节点、顺次经过的节点视为子树,提出交换同一根下子树访问顺序的邻域变换方法. 算例结果表明:算法获得的帕累托前沿由5个非劣解构成,各方案的调机走行总时间均为304 min,入线车小时消耗为6219~6317 min,走行车辆公里数为1443.1~1481.5 km;超体积(HV)值在降温约40次后达到最大,验证了算法具有良好的收敛性能,可有效获得铁路专用线取送车问题的帕累托前沿.

     

  • 图 1  混合型专用线

    Figure 1.  Hybrid sidings

    图 2  初始取送车方案的编码解码示意

    Figure 2.  Diagram illustrating the encoding and decoding of the initial placing-in and taking-out wagons plan

    图 3  编码示意

    Figure 3.  Encoding diagram

    图 4  $ {f}_{1} $解码及计算示意

    Figure 4.  Diagram illustrating the decoding and computation of $ {f}_{1} $

    图 5  $ {f}_{21} $解码及计算示意

    Figure 5.  Diagram illustrating the decoding and computation of $ {f}_{21} $

    图 6  $ {f}_{22} $解码及计算示意

    Figure 6.  Diagram illustrating the decoding and computation of $ {f}_{22} $

    图 7  $ {f}_{31} $解码及计算示意

    Figure 7.  Diagram illustrating the decoding and computation of $ {f}_{31} $

    图 8  $ {f}_{32} $解码及计算示意

    Figure 8.  Diagram illustrating the decoding and computation of $ {f}_{32} $

    图 9  $ {f}_{33} $解码及计算示意

    Figure 9.  Diagram illustrating the decoding and computation of $ {f}_{33} $

    图 10  邻域变换示意

    Figure 10.  Neighborhood transformation illustration

    图 11  算法流程

    Figure 11.  Algorithm flow chart

    图 13  帕累托前沿

    Figure 13.  Pareto front

    图 14  算法进化过程

    Figure 14.  Algorithm evolution process diagram

    表  1  道岔分层结果

    Table  1.   Hierarchical result

    放射枝装卸站
    放射枝112、3
    23
    放射枝24
    放射枝356
    放射枝4117、8、9、10
    78、9、10
    89、10
    910
    下载: 导出CSV

    表  2  调机在各段上的走行时间及走行距离

    Table  2.   Running time and running distance on each section for shunting locomotive

    专用线 走行时间/min 距离/km 专用线 走行时间/min 距离/km 专用线 走行时间/min 距离/km
    O-A 7 3.0 O-C 10 4.2 E-F 12 5.0
    A-1 11 4.6 C-5 15 6.3 E-7 6 2.5
    A-B 5 2.1 C-6 6 2.5 F-G 4 1.7
    B-2 4 1.7 O-D 3 1.3 F-8 14 5.8
    B-3 8 3.3 D-11 7 2.9 G-9 7 2.9
    O-4 16 6.7 D-E 9 3.8 G-10 8 3.3
    下载: 导出CSV

    表  3  各装卸站待送车辆数与待取车辆数

    Table  3.   Number of vehicles waiting to be delivered and picked up at each loading station 辆

    装卸站 待送车辆数 待取车辆数
    1 1 1
    2 3 4
    3 4 3
    4 2 5
    5 5 2
    6 3 4
    7 2 1
    8 1 3
    9 4 2
    10 3 5
    11 2 2
    下载: 导出CSV

    表  4  调移需求

    Table  4.   Transfer demand

    调移起始站 调移目标站 调移车辆数/辆 是否位于同一枝
    1 2 2 是
    1 8 3 否
    2 4 1 否
    4 7 3 否
    7 10 3 是
    下载: 导出CSV

    表  5  算例结果

    Table  5.   Example result

    取送车方案 $ {f}_{1} $/min $ {f}_{2} $/min $ {f}_{3} $/km
    0→1→2→3→0→4→0→7→10→9→8→11→0→6→5→0 304 6219 1481.5
    0→1→2→3→0→4→0→7→9→10→8→11→0→6→5→0 304 6239 1474.1
    0→1→2→3→0→4→0→7→10→9→8→11→0→5→6→0 304 6249 1453.9
    0→1→2→3→0→4→0→7→9→10→8→11→0→5→6→0 304 6269 1446.5
    0→1→3→2→0→4→0→7→9→10→8→11→0→5→6→0 304 6317 1443.1
    下载: 导出CSV
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  • 收稿日期:  2024-09-13
  • 修回日期:  2025-04-26
  • 网络出版日期:  2026-11-09

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