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地铁物流协同配送模型构建及验证

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为缓解城市道路交通的拥堵压力,降低汽车尾气对环境污染影响,选取"寄件—运输—取件"流程为研究对象,通过地铁与货车联运的方式实现地上、地下协同运输模式.在非高峰期时段利用地铁进行货物运输,考虑地铁与货车的最大载货量、货车的最大行驶距离、客户服务时间窗等约束条件,将运输成本与违反客户时间窗所产生的惩罚成本之和最小作为优化目标,构建基于地铁网络的物流协同配送模型.以兰州地铁 1 号线为算例,采用改进遗传算法进行求解,与货车单独配送进行对比,得到两种方式下的路径优化结果.结果表明:地铁-货车联运产生的总成本高于货车单独配送,但并不意味此种模式不可行,地铁-货车联运积极响应交通强国中的大型货车限行政策,可以改善城市道路拥堵、减少环境污染,有较强的应用价值.
Construction and validation of subway logistics collaborative distribution model
In order to alleviate the congestion pressure of urban road traffic and reduce the impact of automobile exhaust on environmental pollution,this paper selected"mail-transport-pickup"process as the research object.The coordinated transportation mode of ground and underground is realized by the combined transportation of subway and truck.In the non-traffic peak hours,the subway is used for freight transportation.Considering the maximum load of subway and truck,the maximum driving distance of truck,customer service time windows,the minimum sum of transportation cost and penalty cost caused by violating customer time window is taken as the optimization objective.A logistics collaborative distribution model based on subway network is constructed.Taking Lanzhou Rail Transmit Line 1 as an example,the adaptive genetic algorithm is used to solve the problem.Compared with the separate distribution of trucks,the path optimization results of the two methods are obtained.The results show that the total cost of subway-truck combined transportation is higher than that of individual trucks,but it does not mean that this mode is not feasible.The subway-truck combined transportation actively responds to the restriction policy of large trucks in the transportation power,which can improve urban road congestion and reduce environmental pollution,and has strong application value.

comprehensive transportationroute optimizationgenetic algorithmsubway distributiontime window

刘亚丽、吴芳、罗恕芳

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兰州交通大学 交通运输学院,兰州 730070

综合运输 路径优化 遗传算法 地铁配送 时间窗

国家自然科学基金项目

42364003

2024

交通科技与经济
黑龙江工程学院

交通科技与经济

影响因子:0.862
ISSN:1008-5696
年,卷(期):2024.26(2)
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