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A Shift-Daily Planning of Freight Trains Composition and Transit Using Maximum Network Flow Approach

机译:基于最大网络流量法的货运列车编组和运输的每日班次计划

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Automation of shift-daily planning for the formation and passage of trains is carried out by searching for the optimal flow on a specially designed network graph. The nodes are events on the train schedule plane – in distance-time coordinates. The resource flow units in the graph are cars. The graph edges are the phases of the resource life cycle: such as carriage idling at a station, movement of a carriage as part of a train, etc. The optimization is carried out by the Goldberg preflow-push method. The algorithm is modified to work with distinguishable flow units, adapted for the task of forming and disbanding trains from cars at stations. Various scenarios of the local train environment of trains and methods of their processing are considered. Successful testing of the algorithm on the model of the Trans-Baikal road is performed.
机译:通过在专门设计的网络图上搜索最佳流量,可以实现列车编组和通过的每日班次计划自动化。节点是火车时间表平面上的事件-在距离-时间坐标中。图中的资源流量单位是汽车。图形的边缘是资源生命周期的各个阶段:例如,车站的车厢空转,作为火车一部分的车厢的移动等。通过Goldberg预流推方法进行优化。对该算法进行了修改,使其可与可区分的流量单位一起使用,适用于在车站从汽车上编组和解散火车的任务。考虑了火车的局部火车环境的各种情况及其处理方法。该算法已成功在贝加尔湖横贯道路模型上进行了测试。

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