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考虑车辆限行和装箱约束的车辆路径优化方法

徐翔斌 任晨昊

徐翔斌, 任晨昊. 考虑车辆限行和装箱约束的车辆路径优化方法[J]. 交通信息与安全, 2021, 39(3): 77-84. doi: 10.3963/j.jssn.1674-4861.2021.03.010
引用本文: 徐翔斌, 任晨昊. 考虑车辆限行和装箱约束的车辆路径优化方法[J]. 交通信息与安全, 2021, 39(3): 77-84. doi: 10.3963/j.jssn.1674-4861.2021.03.010
XU Xiangbin, REN Chenhao. An Optimization Method of Vehicle Routing Considering Vehicle Restrictions and Two-dimensional Loading Constraints[J]. Journal of Transport Information and Safety, 2021, 39(3): 77-84. doi: 10.3963/j.jssn.1674-4861.2021.03.010
Citation: XU Xiangbin, REN Chenhao. An Optimization Method of Vehicle Routing Considering Vehicle Restrictions and Two-dimensional Loading Constraints[J]. Journal of Transport Information and Safety, 2021, 39(3): 77-84. doi: 10.3963/j.jssn.1674-4861.2021.03.010

考虑车辆限行和装箱约束的车辆路径优化方法

doi: 10.3963/j.jssn.1674-4861.2021.03.010
基金项目: 

国家自然科学基金项目 71761013

江西省自然科学基金面上项目 20181BAB201010

详细信息
    通讯作者:

    徐翔斌(1975—),博士,教授.研究方向:物流与供应链管理.E-mail:xuxiangbin@ecjtu.edu.cn

  • 中图分类号: U492.3

An Optimization Method of Vehicle Routing Considering Vehicle Restrictions and Two-dimensional Loading Constraints

  • 摘要: 在实际配送过程中,考虑到部分城市道路存在限制大型配送车辆通行的现状,以及运输途中车厢内物品满足后进先出等装载约束能有效提高装卸效率的特点,将车辆限行和二维装箱约束加入到需求可拆分车辆路径问题中。同时考虑到车辆的使用成本和行驶成本,以车辆总配送成本最小为目标构建考虑车辆限行和二维装箱约束的需求可拆分车辆路径问题数学模型,设计了启发式算法来求解该模型,其中模拟退火算法确定需求拆分下的车辆配送路径,且在当前最优解判断时调用BLF算法检验物品的二维装箱约束,来减少频繁调用BLF算法的时间。数值案例验证了模型和算法的实用性,且所提出的算法的求解结果波动不大于0.8%,能在合理的时间范围内求解得到较好的配送方案,在车辆限行区域内采用双车型配送能节省15.17%~31.27%的总配送成本。

     

  • 图  1  车辆限行下的配送路径图

    Figure  1.  Distribution routes under vehicle restrictions

    图  2  车厢内物品位置示意图

    Figure  2.  Positions of items in the carriage

    图  3  算法流程图

    Figure  3.  Flow of the algorithm

    图  4  路径内邻域构造

    Figure  4.  Neighborhood structures within a path

    图  5  路径间邻域构造

    Figure  5.  Neighborhood structures between paths

    图  6  重复配送调整

    Figure  6.  Adjusting repeated distribution

    图  7  物品覆盖处理

    Figure  7.  Deal with covering items

    图  8  客户坐标位置

    Figure  8.  Coordinate position of customers

    图  9  最优路线图

    Figure  9.  Optimal route

    图  10  不同客户规模下平均求解时间

    Figure  10.  Average solving time under different customer sizes

    图  11  求解波动情况

    Figure  11.  Fluctuations of optimal solutions

    图  12  不同车型方案结果对比

    Figure  12.  Comparison of results under different vehicle models

    表  1  客户需求信息

    Table  1.   Customers' demand information

    客户编号 横坐标/m 纵坐标/m 需求量 物品宽/cm 物品长/cm 物品重量/t
    1 12.8 8.5 2 75 90 0.4
    2 18.4 3.4 2 45 165 0.2
    3 15.4 16.6 2 30 60 0.2
    4 18.9 15.2 1 75 75 0.6
    5 15.5 11.6 3 75 225 0.2
    6 3.9 10.6 2 45 90 0.4
    7 10.6 7.6 1 60 135 0.4
    8 8.6 8.4 3 75 105 0.6
    9 12.5 2.1 1 60 60 0.2
    10 13.8 5.2 4 60 165 0.4
    11 6.7 16.9 2 30 90 0.6
    12 14.8 2.6 2 45 165 0.4
    13 1.8 8.7 3 75 60 0.2
    14 17.1 11.0 1 45 105 0.2
    15 7.4 1.0 1 30 195 0.4
    16 0.2 2.8 3 45 105 0.4
    17 11.9 19.8 1 90 180 0.4
    18 13.2 15.1 4 75 75 0.4
    19 6.4 5.6 1 60 165 0.2
    20 9.6 14.8 1 45 150 0.4
    下载: 导出CSV

    表  2  车辆参数

    Table  2.   Vehicle parameters

    车型编号 发车成本/元 限载量/t 车厢宽/cm 车厢长/cm 单位行驶成本/(元/km) 单次最远里程/km
    1 200 1.8 100 200 2 50
    2 250 3 200 300 2.5 80
    下载: 导出CSV

    表  3  最优配送方案

    Table  3.   Optimal distribution plan

    路径编号 路径 路径成本/元 装载量/t 车型编号
    路径1 0—18(1)—17—11—20—0 305.25 2.4 2
    路径2 0—6—13—19—0 260.44 1.6 1
    路径3 0-18(3)-3-4-14—5—0 292.25 3 2
    路径4 0—2—12—9—15—16—0 366.52 3 2
    路径5 0—7—10—1—0 297.30 2.8 2
    路径6 0—8—0 229.93 1.8 1
    下载: 导出CSV

    表  4  测试算例求解结果

    Table  4.   Results of the test examples

    客户规模 限行区域客户数 CPLEX 本文算法
    最优解/元 求解时间/s 求解结果/元 求解时间/s
    5 0 331.74 13.45 331.74 69.08
    8 1 801.17 267.69 801.17 106.56
    11 1 894.34 152.53
    14 2 1 192.98 177.28
    下载: 导出CSV

    表  5  不同限行区域客户数下的求解结果

    Table  5.   Results under different numbers of customers in the vehicle-restricting area

    客户规模 无限行区域 限行区域客户数为1 限行区域客户数为2 限行区域客户数为3
    总成本/元 总成本/元 变化率/% 总成本/元 变化率/% 总成本/元 变化率/%
    8 656.74 801.17 21.99 811.34 23.54 867.01 32.02
    11 873.71 894.34 2.36 912.10 4.39 963.59 10.29
    14 1 180.89 1 191.15 0.87 1 192.98 1.02 1 255.37 6.31
    17 1 459.35 1 464.46 0.35 1 468.81 0.65 1 467.26 0.54
    下载: 导出CSV
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  • 收稿日期:  2020-05-23

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