基于最大网络流方法的货运列车组队和过境班次-日规划

A. Shabunin, A. Takmazian, A. Esakov
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引用次数: 0

摘要

通过在专门设计的网络图上搜索最优流程,实现列车编队和通行的班次-日规划自动化。节点是列车时刻表平面上的事件——以距离-时间坐标表示。图中的资源流单位是汽车。图边是资源生命周期的各个阶段:例如在车站空转的车厢,作为火车一部分的车厢的运动,等等。采用Goldberg预流推法进行优化。该算法被修改为可区分的流单元,适用于车站列车和汽车的形成和解散任务。考虑了列车局部运行环境的各种场景及其处理方法。该算法在跨贝加尔湖公路模型上进行了成功的测试。
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A Shift-Daily Planning of Freight Trains Composition and Transit Using Maximum Network Flow Approach
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.
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