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Optimization of maintenance strategies for railway track-bed considering probabilistic degradation models and different reliability levels

机译：考虑概率降解模型和不同可靠性水平的铁路轨道床维修策略优化

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摘要

An optimization-based maintenance scheduling framework is an essential tool to plan the necessary investment to maintain the required performance of a railway line. In the present study, a methodology is proposed to minimize the present value of the life cycle maintenance costs and maximize the life cycle quality level of the track-bed considering different levels of reliability. Probabilistic degradation models are developed for predicting the evolution of the railway track condition over time. Afterwards, a Genetic Algorithm based optimization procedure is applied for obtaining a set of optimal solutions taking into account several constrains. The proposed methodology is applied to an Italian railway track-line case study. The results show that it is possible to develop a decision support system to help railway managers to schedule railway track maintenance operations based on the optimal trade-off between maintenance costs and railway track geometry condition for different levels of reliability.
机译：基于优化的维护调度框架是规划必要投资以维持铁路线所需性能的重要工具。在本研究中，提出了一种方法，以最小化生命周期维护成本的本值，并最大限度地考虑轨道床的寿命周期质量水平，考虑到不同的可靠性。开发了概率降解模型，用于预测铁路轨道条件随时间的演变。之后，应用基于遗传算法的优化过程来获取考虑若干约束的一组最佳解决方案。该方法适用于意大利铁路轨道线案例研究。结果表明，可以制定决策支持系统，帮助铁路管理人员根据维护成本与铁路轨道几何状况之间的最佳权衡来安排铁路跟踪维护运行，以实现不同程度的可靠性。

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