Abstract
Railway track maintenance and renewal are vital for railway safety, train punctuality, and travel comfort. Therefore, having cost-effective maintenance is critical in managing railway infrastructure assets. There has been a considerable amount of research performed on mathematical and decision support models for improving the application of railway track maintenance planning and scheduling. This article reviews the literature in decision support models for railway track maintenance planning and scheduling and transforms the results into a problem taxonomy. Furthermore, the article discusses current approaches in optimising maintenance planning and scheduling, research trends, and possible gaps in the related decision-making models.
Highlights
Railway track is a crucial civil infrastructure
We propose a taxonomy for railway track maintenance planning and scheduling (RTMP&S) decision sup port models, separating the planning and scheduling decision areas in railway, discussing the optimisation frameworks, and analysing the research trends and gaps
We found an inconsistency between the planning time horizon for RTMP&S problems generally found in the literature and the defined planning horizon range in the Liden [6] classification
Summary
Railway track is a crucial civil infrastructure. A reliable railway track is vital for safety, train punctuality, travel comfort, and costeffectiveness of maintenance and renewal activities. Railways require maintenance to ensure an acceptable level of operating conditions. In 2018, railway maintenance expenditure in the European Union (EU27) was estimated at 20,6 billion Euros, accounting for more than half of the total rail infrastructure expenditure [1]. Railways are amongst the longest-lasting and most capital-intensive assets, and even minor improvements in maintenance cost and efficiency can have sig nificant effects on the total life cycle costs [2]. A maintenance management system is necessary to ensure the infrastructure system’s availability [3]. Planning and scheduling processes are at the core of improving maintenance management performance [4]. Railway infra structure owners and maintenance contractors need decision-making tools and models to plan resources efficiently and maintain the track by effective scheduling
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