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A heuristic approach to railway track maintenance scheduling

机译:铁路养护计划的启发式方法

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摘要

Travelling safely and comfortably on high speed railway lines requires excellent conditions of the whole railway infrastructure in general and of the railway track geometry in particular. The maintenance process required to achieve such excellent conditions is largely complex and expensive, demanding an increased amount of both human and technical resources. In this framework, an optimal scheduling of maintenance interventions is an issue of increased relevance. In this work a method for optimization of the tamping scheduling is presented. It is based on a heuristic algorithm, which finds a very detailed tamping schedule where each planned intervention is fully specified. The algorithm tries to maximize an objective function, which is a quantitative expression of the maintenance process's objectives defined by the railway company. It first finds an upper bound for the objective function value, and then returns the best feasible solution found. The method is validated by means of a case study based on real data of the 240 km track of a French high speed TGV line. The results presented show that the value of the best solution found is very near to the upper bound (the difference is smaller than 1%), with a calculation time of under 1 second using a standard computer, so we think the heuristic has a great performance potential.
机译:在高速铁路线上安全舒适地行驶通常需要整个铁路基础设施,特别是铁路轨道几何形状的优良条件。为了达到如此出色的条件,维护过程非常复杂且昂贵,需要增加人力和技术资源。在此框架中,维护干预措施的最佳调度是相关性增加的问题。在这项工作中,提出了一种夯实调度的优化方法。它基于启发式算法,该算法可找到非常详细的夯实计划,其中会详细说明每个计划的干预措施。该算法试图最大化目标函数,这是铁路公司定义的维护过程目标的定量表示。它首先找到目标函数值的上限,然后返回找到的最佳可行解。通过基于法国高速TGV线240公里航迹的真实数据的案例研究验证了该方法。给出的结果表明,找到的最佳解决方案的值非常接近上限(差异小于1%),使用标准计算机的计算时间不到1秒,因此我们认为启发式算法具有很大的优势。性能潜力。

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