Multiobjective Optimization of Ballasted Track Maintenance Scheduling
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 1
Abstract
This paper proposes a multiobjective optimization approach for a preventive maintenance scheduling problem. To model this problem, an optimization model was developed by considering two objective functions: minimizing maintenance cost associated with the preventive tamping cost, machine preparation cost, and possession cost during time scheduling, as well as minimizing the total loss of remaining useful life (LRUL) over a given planning horizon. The applicability of the model was tested with the strength Pareto evolutionary algorithm II (SPEA-II) and multiobjective particle swarm optimization (MOPSO) algorithms in a case study on a section of Tehran-Mashhad line in Iran for the planning horizon of three years. Finally, a sensitivity analysis was performed on the possession cost and maximum permitted train speed. The results showed that by increasing the maintenance budget up to 47.32%, the track capacity could be increased by 25% due to increased permitted speed. Moreover, by increasing the cost associated with track possession, the preparation cost was reduced by considering the opportunistic maintenance policy through the grouping track segments.
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Data Availability Statement
Some data, models, or code generated or used during the study are available from the corresponding author by request.
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Journal of Transportation Engineering, Part A: Systems
Volume 148 • Issue 1 • January 2022
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© 2021 American Society of Civil Engineers.
History
Received: Dec 25, 2020
Accepted: Jun 30, 2021
Published online: Oct 30, 2021
Published in print: Jan 1, 2022
Discussion open until: Mar 30, 2022
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