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Automated train scheduling system using Genetic Algorithm

机译:基于遗传算法的自动火车调度系统

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The increment of interest for transport service in rail activity stipulates higher proportion of consumed infrastructure capacity. In this system of activity stream, even minor deviations from the arranged schedule can affect its stability, and this can bring about a noteworthy diminishment of the nature of transport service. Given the way that the railroad business is as of now running without much abundance limit, better arranging and planning instruments are expected to successfully deal with the rare assets, keeping in mind the ultimate goal to adapt to the quickly expanding interest for rail route transportation. The objective of operational scheduling of trains is to safely move about each train, as fast as possible, from its origin to its destination such that the total delay of all trains can be minimized. This paper presents a (Fixed Path + Genetic Algorithm) heuristic model, an optimization-based approach for scheduling of trains. The Fixed Path model assumes that path of the trains is fixed for preparing the train schedule. The Genetic Algorithm is used for selecting the path for each train that takes minimum time to arrive at the destination. Together it presents a schedule that can minimize the travel time of each train maximizing capacity of the network. This paper proves the fact that applying the proposed model, rail traffic can be improved regarding the increase of the timetable stability and maximizing capacity subject to safety constraints.
机译:铁路运输中运输服务的兴趣增加表明消耗的基础设施容量所占的比例更高。在这种活动流系统中,即使与安排的时间表有微小的偏差也会影响其稳定性,这会导致运输服务性质的显着下降。考虑到目前铁路业务的运营方式没有太多的充裕限制,因此,希望有更好的安排和计划工具来成功处理稀有资产,同时要牢记适应快速增长的铁路运输兴趣的最终目标。列车运行调度的目的是使每列列车从起点到目的地尽可能安全地安全行驶,以使所有列车的总延误最小化。本文提出了(固定路径+遗传算法)启发式模型,这是一种基于优化的火车调度方法。固定路径模型假定火车的路径是固定的,以准备火车时刻表。遗传算法用于为每列火车选择路径,该路径花费最少的时间到达目的地。它一起提出了一个时间表,该时间表可以使每列火车的行驶时间最小化,从而使网络的容量最大化。本文证明了以下事实:应用所提出的模型,可以提高时间表的稳定性,同时提高时间表的稳定性,并在安全约束下使运力最大化。

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