Optimization Research on the Scheduling of Beijing-Shanghai High-Speed Railway Maintenance Equipment Based on Big Data Analysis

DOI

10.2991/978-94-6463-736-6_27How to use a DOI?

Keywords

Multi-objective Optimization; Maintenance Management; Big Data; Genetic Algorithm; Green Development

Abstract

This paper explores optimization issues in the operation and maintenance (O&M) management of the Beijing-Shanghai High-Speed Railway (BSR). A multi-objective optimization method is used to balance factors such as equipment usage, maintenance expenses, and carbon emissions, aiming to improve overall operational efficiency. Through genetic algorithm (GA) optimization, the study yields the following results: a 15% reduction in O&M costs, a 12% decrease in carbon emissions, and an 8% improvement in equipment utilization. The optimization strategy efficiently allocates equipment and adjusts maintenance schedules, reducing the use of expensive and high-emission equipment to ensure better resource utilization. Unlike traditional scheduling methods that often rely on heuristic or rule-based approaches, this research leverages a data-driven optimization model, demonstrating superior performance through comparative analysis. The study uses real-world operational and maintenance data collected from the BSR’s central management system, integrating historical performance logs, equipment failure reports, and maintenance cost records. This approach ensures the model’s transparency, reproducibility, and practical applicability. The findings provide novel optimization strategies for high-speed railway O&M management, promoting green and sustainable development.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ruina Yang
AU  - Ruixue Zhang
PY  - 2025
DA  - 2025/05/22
TI  - Optimization Research on the Scheduling of Beijing-Shanghai High-Speed Railway Maintenance Equipment Based on Big Data Analysis
BT  - Proceedings of the 2025 4th International Conference on Engineering Management and Information Science (EMIS 2025)
PB  - Atlantis Press
SP  - 232
EP  - 238
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-736-6_27
DO  - 10.2991/978-94-6463-736-6_27
ID  - Yang2025
ER  -