A mathematical programming model to select maintenance strategies in railway networks

Claudia Fecarotti (Corresponding author), John D. Andrews, Raffaele Pesenti

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10 Citations (Scopus)
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Abstract

This paper presents a nonlinear integer programming model to support the selection of maintenance strategies to implement on different segments of a railway network. Strategies are selected which collectively minimise the impact of sections’ conditions on service, given network availability and budget constraints. Different metrics related to the network topology, sections’ availability, service frequency, performance requirements and maintenance costs, are combined into a quantitative approach with a holistic view. The main contribution is to provide a simple yet effective modelling approach and solution method which are suitable for large networks and make use of standard solvers. Both an ad hoc heuristic solution and relaxation methods are developed, the latter enabling the quality of the heuristic solution to be estimated. The availability of railway lines is computed by exploiting the analogy with series–parallel networks. By varying the model parameters, a scenario analysis is performed to give insight into the influence of the system parameters on the selection of strategies, thus enabling more informed decisions. For its simple structure, the model is versatile to address similar problems arising in the maintenance of other types of networks, such as road and bridges networks, when deciding on the strategic allocation of maintenance efforts.
Original languageEnglish
Article number107940
Number of pages13
JournalReliability Engineering and System Safety
Volume216
DOIs
Publication statusPublished - Dec 2021

Funding

John Andrews is the Network Rail Professor of Infrastructure Asset Management and Director of Lloyd's Register Foundation (Lloyd's Register Foundation supports the advancement of engineering-related education, and funds research and development that enhances safety of life at sea, on land and in the air) Resilience Engineering Research Group at the University of Nottingham. The authors gratefully acknowledge the support of these organisations.

FundersFunder number
Lloyd's Register Foundation
University of Nottingham

    Keywords

    • Availability
    • Maintenance optimisation
    • Mathematical programming
    • Railway networks

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