首页> 外文会议>Computers in Railways X: Computer System Design and Operation in the Railway and other Transit Systems; WIT Transactions on Built Environment; vol.88 >Optimal train control at a junction in the main line rail network using a new object-oriented signalling system model
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Optimal train control at a junction in the main line rail network using a new object-oriented signalling system model

机译:使用新的面向对象的信号系统模型在干线铁路网的交汇处优化列车控制

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On a main line railway network with many junctions, the delay of a train is likely to cause delays to many other trains, especially because of conflicts at junctions. Optimising one junction, however, may have an adverse effect on other parts of the rail network because of the mixed-traffic situation of most main line railways. To approach the complicated problem of optimal re-scheduling in response to the delay of a train, an efficient algorithm must be sought.rnThe authors have taken a junction as an example, and have performed numerical optimisation on a case when the services through this junction are disrupted. The objective criterion is the weighted sum of train times. The optimisation program uses the Object-Oriented Multi-Train Simulator (OOMTS) developed by Birmingham University, as an embedded simulator. In the optimisation routine, a Genetic Algorithm (GA) was used to optimise the order of route setting.rnIn this paper, the authors give details of a model junction, and a brief explanation of the OOMTS. The authors then explain how a GA can be applied to solve this problem, especially the chromosomal expression of the problem. The results of numerical optimisations for different weighting parameters are shown based on which the authors discuss the feasibility of the proposed method.
机译:在具有许多路口的干线铁路网络中,火车的延误可能会导致许多其他火车的延误,特别是由于路口发生冲突。但是,由于大多数干线铁路的混合交通情况,优化一个路口可能会对铁路网络的其他部分产生不利影响。为了解决响应火车延误的最优重新调度的复杂问题,必须寻求一种有效的算法。作者以一个路口为例,并对通过该路口的服务进行了数值优化。被打乱了。客观标准是火车时间的加权总和。该优化程序使用由伯明翰大学开发的面向对象的多训练模拟器(OOMTS)作为嵌入式模拟器。在优化例程中,使用遗传算法(GA)来优化路线设置的顺序。在本文中,作者提供了模型连接的详细信息,并简要介绍了OOMTS。然后作者解释了如何将遗传算法应用于解决该问题,尤其是该问题的染色体表达。给出了不同加权参数的数值优化结果,在此基础上作者讨论了该方法的可行性。

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