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Microscopic Resource Assignment Model and Lagrangian Relaxation Based Algorithm for Train Operation Scheduling in Railway Station

机译:基于微观资源分配模型和拉格朗日放松算法在火车站列车运行调度算法

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The quality of train operation plan in large railway stations is "critical" for the efficiency of the whole railway network. We present a novel optimization approach for operation scheduling problem in railway station. The model is based on microscopic devices of railway infrastructure, such as tracks, switches and crosses. The scheduling decisions are based on discretizedresource-time network; we introduce Lagrangian relaxation based heuristic method to compute the maximum total profit of operation plan without any operation conflicts. The approach has been testedon a real worldhigh speed railway case with one hour realistic data. The results investigate the quality of the proposed model and algorithm.
机译:大型铁路车站的火车运行计划质量为“批判”,以实现整个铁路网络的效率。我们提出了一种新的火车站运作调度问题的新优化方法。该模型基于铁路基础设施的微观设备,例如轨道,开关和交叉。调度决策是基于分离的资源时间网络;我们介绍拉格朗日放松的启发式方法,在没有任何运行冲突的情况下计算运营计划的最大溢利。该方法已经测试了一个真正的世界高速铁路箱,具有一小时的现实数据。结果研究了所提出的模型和算法的质量。

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