Nowadays more and more complex railway systems can operate efficiently only if we have tools for planning their maintenance. Train accidents are mainly caused by infrastructure problems, or more specifically by track geometry failures.In this paper, we present a support decision system for forecasting the deterioration of track geometry. Two types of defects can be identified for each railway track segment. If a defect belongs to the first type, it must be repaired immediately; otherwise, the defect can be fixed after a specific time period. For resolving this problem, we first decompose the problem into two stages: prediction and classification. Both phases contain a learning phase and a testing phase. The solution technique for both stages are based on automatic programming field and its recently proposed heuristic, called variable neighborhood programming. Our new method is tested on real world problems. The results show that the proposed approach is a good and reliable tool for the preventive maintenance planning of the railway infrastructure.

如今，只有我们拥有规划维护的工具，越来越多的复杂铁路系统才能有效运行。火车事故主要是由基础设施问题引起的，或更具体地说是由轨道几何形状的故障引起的。在本文中，我们提出了一种用于预测轨道几何形状恶化的支持决策系统。对于每个铁路轨道段，可以识别出两种类型的缺陷。如果缺陷属于第一类，则必须立即修复；否则，可以在特定时间段后修复缺陷。为了解决此问题，我们首先将问题分解为两个阶段：预测和分类。这两个阶段都包含学习阶段和测试阶段。这两个阶段的解决方案技术都基于自动编程领域，并且最近提出了启发式算法，称为可变邻域编程。我们的新方法已经在现实世界中的问题上进行了测试。结果表明，该方法是铁路基础设施预防性维护计划的良好而可靠的工具。