Abstract The light rail is gaining relevance within cities’ transportation networks due to its adequate balance among sustainability, economic and safety factors. Nevertheless, there is still a gap for improvement in those factors through the optimisation of rolling stock maintenance strategies. The development of new and more flexible maintenance strategies at proper indenture levels will aid to improve the reliability and availability of the light rail during the operation phase, as well as to reduce its life cycle cost. Accordingly, the present research develops a multi-objective maintenance model that adopts a novel reliability-based advanced maintenance policy; whose aim is to consistently evaluate short-term information to enhance both traditional maintenance and organisational key performance indicators. The proposed multi-objective mathematical model is solved through a simulation-based optimisation (SBO), which by means of iteration evaluates different maintenance strategies according to the non-dominated sorting genetic algorithm (NSGA II). Empirical results, based on real data obtained from a light rail fleet operating in Spain, demonstrate that the proposed maintenance model for the rolling stock can significantly improve the light rail performance regarding both maintenance and organisational objectives.

中文翻译：

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基于可靠性的高级维护建模，以提高机车车辆制造商的目标

摘要 轻轨因其在可持续性、经济和安全因素之间的充分平衡而在城市交通网络中越来越重要。尽管如此，通过优化机车车辆维护策略来改善这些因素仍然存在差距。在适当的契约水平上开发新的、更灵活的维护策略将有助于提高轻轨在运营阶段的可靠性和可用性，并降低其生命周期成本。因此，本研究开发了一种多目标维护模型，该模型采用了一种新颖的基于可靠性的高级维护策略；其目的是持续评估短期信息，以提高传统维护和组织关键绩效指标。所提出的多目标数学模型是通过基于模拟的优化（SBO）求解的，它通过迭代根据非支配排序遗传算法（NSGA II）评估不同的维护策略。基于从西班牙运营的轻轨车队获得的真实数据的实证结果表明，提议的机车车辆维护模型可以显着提高轻轨在维护和组织目标方面的性能。