Realign Existing Railway Curves without Key Parameter Information
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 8
Abstract
Railway curve realignment is critical for rectifying railway alignment deviations caused by excessive train load and repeated repairs. The existing realignment methods have limitations, such as low efficiency and precision, when considering realigning curves without key parameter information (CWI). To address the CWI issues, this study proposes a range identification and adaptive simplified particle swarm optimization (RI-ASPSO) algorithm combined with the existing principle of realigning railway curves. In this algorithm, the RI is designed to identify the range of curve parameters and is the premise of the ASPSO. Moreover, an automatic update strategy of the velocity threshold and an adaptive local random search strategy are developed in the ASPSO to efficiently and stably search the final near-optimal solution. The method is applied in real-world case studies, and the results show that the RI-ASPSO outperforms the particle swarm optimization (PSO) algorithm and coordinate method with higher accuracy, higher efficiency, and less deviation.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author on reasonable request.
Acknowledgments
This work was supported by Sichuan Science and Technology Program (Grant Nos. 2019YFG0460 and 2020YFG0049).
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 148 • Issue 8 • August 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Dec 15, 2021
Accepted: Apr 5, 2022
Published online: May 24, 2022
Published in print: Aug 1, 2022
Discussion open until: Oct 24, 2022
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