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

Sara Bressi, Santos, João and Massimo Losa

Reliability Engineering and System Safety, 2021, vol. 207, issue C

Abstract: 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.

Keywords: Track management system; Markov chain; Genetic algorithm; Multi-objective optimization; Railway; Maintenance (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:207:y:2021:i:c:s0951832020308498

DOI: 10.1016/j.ress.2020.107359

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