Optimizing rolling stock assignment and maintenance plan for passenger railway operations

• Published in: Computers & industrial engineering 2015-07, Vol.85, p.284-295
• Main Authors: Lai, Yung-Cheng, Fan, Dow-Chung, Huang, Kwei-Long
• Format: Article
• Language: English
• Subjects: Assignment problem; Decision support systems; Decision-support model; Efficiency; Heuristic; Heuristics; Maintenance; Maintenance planning; Manuals; Mathematical models; Optimization; Optimization techniques; Rail transportation; Railroads; Railway engineering; Railway networks; Railways; Rolling stock; Rolling stock assignment planning; Studies
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2015.03.016

•Assignment between rolling stock and daily utilization schedule is optimized.•Practical constraints in operations and multi-level maintenance are considered.•A heuristic process is proposed to significantly improve solution efficiency.•Our optimization process increases utilization of rolling stock by around 5%.•The empirical study shows that monthly maintenance cost reduces by 5.41%. The efficient use of railway rolling stock is an important objective pursued in a railway agency or company because of intensive capital investment in rolling stock. Daily rolling stock assignment assigns appropriate equipment to cover a given set of utilization paths in the utilization schedules while considering practical requirements, such as maintenance, depot capacity, and circulation rules. Experienced railway practitioners can generally produce a feasible assignment plan; however, this manual process is time consuming, and an optimal solution is not guaranteed. This research develops an exact optimization model to improve the efficiency in rolling stock usage with consideration of all necessary regulations and practical constraints. Compared to the manual process, a hybrid heuristic process is also developed to improve solution quality and efficiency. Empirical results demonstrate that the heuristic process can successfully increase the efficiency of rolling stock use by about 5% and significantly reduce the solution time from 3h to 11.2 s. Using this decision support tool can help railways with similar characteristics to improve the efficiency in rolling stock usage and productivity in rolling stock assignment process.