GENERATION OF DISPATCHING SOLUTIONS IN A ROLLING TIME HORIZON FRAMEWORK WITH THE AID OF TABU SEARCH
GENERATION OF DISPATCHING SOLUTIONS IN A ROLLING TIME HORIZON FRAMEWORK WITH THE AID OF TABU SEARCH
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DOI：
10.2495/cr200091
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发表时间：
2020-08
期刊：
影响因子：
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通讯作者：
U. Martin;Markus Tideman;Weiting Zhao
中科院分区：
文献类型：
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作者：
U. Martin;Markus Tideman;Weiting Zhao
为了提高铁路运营的稳健性，斯图加特大学铁路与运输工程研究所(IEV)开发了一种主动调度算法。首先，根据特定的运营风险指标对铁路网中的闭塞区段进行自动分类。因此，基于蒙特卡罗方案中产生的随机扰动来修改多个时刻表，然后在RailSys®软件中对修改后的时刻表进行仿真，最后计算所研究网络中产生的等待时间，以获得运营风险图。考虑到这一运营风险图，在滚动的时间范围框架内生成接近最优的调度解决方案。为此，调查时间跨度被划分为所谓的预测范围(PH)，而预测范围又被划分为所谓的调度间隔(DI)。根据风险图，在每个DI开始时，列车运行被人为地延长。然后，在当前PH的持续时间内检查是否发生冲突(闭塞区段中的至少两个不同列车的阻塞时间重叠)。如果检测到的冲突很小，则通过对受影响的列车运行重新计时来解决这些冲突。然而，如果发生重大冲突，列车运行必须重新排序。这是在禁忌搜索的帮助下实现的。文中不仅描述了该算法的功能，而且根据IEV用于算法开发的实际参考实例进行了演示。在此背景下，特别强调了几个与调度相关的重要参数，以确定它们对调度过程的一般影响。参考算例表明，与其他调度原则相比，所提出的调度算法对运行质量有持续的影响。
To increase the robustness of railway operation, at the Institute of Railway and Transportation Engineering (IEV) of the University of Stuttgart, a proactive dispatching algorithm has been developed. At the beginning, the block sections of a railway network are classified automatically depending on their specific operational risk index. Therefore, numerous timetables are modified based on random disturbances generated in a Monte Carlo scheme, then the modified timetables are simulated in RailSys ® software and, finally, the resulting waiting times in the studied network are calculated to obtain an operational risk map. Considering this operational risk map, near-optimal dispatching solutions are generated within a rolling time horizon framework. To this, the investigation time span is divided into so-called prediction horizons (PH), which, on their part, are divided into so-called dispatching intervals (DI). At the start of each DI the train runs are artificially prolonged according to the risk map. Then, it is checked for the duration of the current PH whether conflicts (overlap of blocking times of at least two different trains in a block section) occur or not. If the detected conflicts are slight, they are solved by retiming of the affected train runs. However, in case of significant conflicts, the train runs have to be reordered. This is achieved with the aid of Tabu Search. In this paper, the functionality of the proposed algorithm is not only described but also demonstrated according to a realistic reference example that is standardly used at the IEV for algorithm development. In this context, special emphasis is placed on several important dispatching-related parameters to determine their general influence on the dispatching process. In the light of the reference example, it is shown that the proposed dispatching algorithm has a sustainable impact on the operation quality, particularly in comparison to other dispatching principles.