Segment-Condition-Based Railway Track Maintenance Schedule Optimization

Maintenance plans are vital for railroad train safety and improved railroad track service life. But studies on scheduling and optimization of track maintenance plans have several limitations: 1) Optimization models for maintenance scheduling operate with months rather than days as the time units; 2) They do not take account of the two-way feedback and dynamic impact between predicted condition and maintenance scheduling; 3) Strategies for on-site operation are not considered. The authors propose a new method for maintenance scheduling based on segment condition, taking into account both opportunistic and centralized maintenance methods. The authors designed a hybrid multi-objective optimization algorithm based on particle swarm optimization. In application to real-world cases, the effectiveness of the model and algorithm was verified by comparison with Multi-Objective Particle Swarm Optimization (MOPSO), Non-dominated Sorting Genetic Algorithm (NSGA-II and III), and Gurobi optimization.

• Record URL:
  http://dx.doi.org/10.1111/mice.12824
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/10939687
• Authors:
  • Chang, Yanyan
  • Liu, Rengkui
  • Tang, Yuanjie
• Publication Date: 2023-1-15

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 160-193
• Serial:
  • Computer-Aided Civil and Infrastructure Engineering
  • Volume: 38
  • Issue Number: 2
  • Publisher: Blackwell Publishing
  • ISSN: 1093-9687
  • Serial URL: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-8667

Subject/Index Terms

• TRT Terms: Maintenance management; Maintenance of way; Optimization; Planning methods; Railroad tracks
• Subject Areas: Maintenance and Preservation; Planning and Forecasting; Railroads;

Filing Info

• Accession Number: 01882210
• Record Type: Publication
• Files: TRIS
• Created Date: May 18 2023 5:08PM