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集卡动态调度路径优化算法

李广儒 杨大奔 任大伟

李广儒, 杨大奔, 任大伟. 集卡动态调度路径优化算法[J]. 交通运输工程学报, 2012, 12(3): 86-91. doi: 10.19818/j.cnki.1671-1637.2012.03.013
引用本文: 李广儒, 杨大奔, 任大伟. 集卡动态调度路径优化算法[J]. 交通运输工程学报, 2012, 12(3): 86-91. doi: 10.19818/j.cnki.1671-1637.2012.03.013
LI Guang-ru, YANG Da-ben, REN Da-wei. Path optimization algorithm of dynamic scheduling for container truck[J]. Journal of Traffic and Transportation Engineering, 2012, 12(3): 86-91. doi: 10.19818/j.cnki.1671-1637.2012.03.013
Citation: LI Guang-ru, YANG Da-ben, REN Da-wei. Path optimization algorithm of dynamic scheduling for container truck[J]. Journal of Traffic and Transportation Engineering, 2012, 12(3): 86-91. doi: 10.19818/j.cnki.1671-1637.2012.03.013

集卡动态调度路径优化算法

doi: 10.19818/j.cnki.1671-1637.2012.03.013
基金项目: 

"十一五"国家科技支撑计划项目 2009BAG18B03

中央高校基本科研业务费专项资金项目 2009QN013

详细信息
    作者简介:

    李广儒(1970-), 男, 辽宁大连人, 大连海事大学副教授, 工学博士, 从事海上智能交通信息处理研究

  • 中图分类号: U691.3

Path optimization algorithm of dynamic scheduling for container truck

More Information
    Author Bio:

    LI Guang-ru (1970-), male, associate professor, PhD, +86-411-84724329, liguangru@sina.com

  • 摘要: 从整体调度的角度出发, 分析了整个码头作业面的动态调度方案, 提出了一种新的集装箱卡车(集卡)动态调度路径的自适应蚁群算法。运用码头GPRS系统, 以集卡速度、流量、位置等相关数据建立了感知链。通过判断阻塞状况和调整可行点集, 确定了信息素浓度更新策略与转移概率计算方法。针对码头路网的复杂性和蚁群算法的实时计算效率, 设计了蚁群算法的步骤。将信息熵引入到蚁群算法中, 运用MATLAB软件, 对集卡的动态调度方案进行了仿真计算。计算结果表明: 当初始集卡速度分别为50、75 km·h-1, 初始集卡流量分别为800、1 000 veh·h-1时, 集卡行驶的最短路径为4.3 km, 行驶时间为0.057 h;集卡行驶的最优路径为8.3 km, 行驶时间为0.111 h。可见, 该算法能有效缓解码头阻塞问题, 提高集卡利用率和码头作业效率。

     

  • 图  1  最优路径

    Figure  1.  Optimal path

    图  2  最短路径

    Figure  2.  Shortest path

    表  1  信息参数

    Table  1.   Information parameters

    下载: 导出CSV

    表  2  节点像素坐标

    Table  2.   Pixel coordinates of nodes

    下载: 导出CSV

    表  3  路径计算结果

    Table  3.   Calculation result of paths

    下载: 导出CSV
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出版历程
  • 收稿日期:  2012-01-09
  • 刊出日期:  2012-06-25

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