基于“库前移”模式的铁路商品车物流基地分层动态选址优化研究

发布时间：2018-04-29 18:26

本文选题：商品车物流 + 物流基地　；参考：《铁道学报》2017年09期

【摘要】：铁路商品车物流基地选址问题对于拓展铁路商品车运输业务具有重要意义。本文结合商品车运输"库前移"模式的运作特点,提出由商品车主机制造厂、区域物流基地、地区物流基地、客户构成的四级物流网络。以该网络为研究对象,构建铁路商品车物流基地分层级、多周期动态选址的0-1混合整数规划模型。该模型将铁路客户的变化状态作为多周期的划分依据,以降低成本、提高既有资源利用率为优化目标。在求解方法上,设计遗传-禁忌算法求解单周期静态选址模型,并将多周期动态选址问题转化为最短路问题进行求解。通过9-152-152-293四级物流网络的实际数据,验证模型的合理性及算法在求解大规模问题的有效性。
[Abstract]:The location of railway commercial vehicle logistics base is of great significance to the expansion of railway commercial vehicle transportation business. Combined with the operation characteristics of the "storehouse forward" mode of commercial vehicle transportation, this paper puts forward a four-level logistics network composed of the main machine manufacturer, the regional logistics base, the regional logistics base and the customer. Taking the network as the research object, the 0-1 mixed integer programming model of railway commercial vehicle logistics base is constructed, which is hierarchical and multi-period dynamic location selection. The model takes the changing state of railway customers as the basis of multi-cycle division, in order to reduce the cost and improve the utilization of existing resources as the optimization goal. In order to solve the problem, a genetic Tabu algorithm is designed to solve the single-period static location model, and the multi-period dynamic location problem is transformed into the shortest path problem. Through the actual data of 9-152-152-293 four-level logistics network, the rationality of the model and the validity of the algorithm in solving large-scale problems are verified.
【作者单位】：北京交通大学交通运输学院;中国铁路总公司运输局;
【基金】：中国铁路总公司科技研究开发计划(2014X009-B,2016X007-B) 国家质量监督检验检疫总局质检公益性行业科研专项项目(201510210-03)
【分类号】：U291.51

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