Joint optimization of train scheduling and maintenance planning in a railway network: A heuristic algorithm using Lagrangian relaxation
•Propose a joint optimization model for train scheduling and maintenance planning in a railway network.•Develop a heuristic algorithm using Lagrangian relaxation to solve the ILP model.•Apply the proposed model and algorithm to a practical problem in the Chinese railway network. Train scheduling and...
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| Vydané v: | Transportation research. Part B: methodological Ročník 134; s. 64 - 92 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Oxford
Elsevier Ltd
01.04.2020
Elsevier Science Ltd |
| Predmet: | |
| ISSN: | 0191-2615, 1879-2367 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | •Propose a joint optimization model for train scheduling and maintenance planning in a railway network.•Develop a heuristic algorithm using Lagrangian relaxation to solve the ILP model.•Apply the proposed model and algorithm to a practical problem in the Chinese railway network.
Train scheduling and maintenance planning compete for the resources in a railway network. A commonly used way is dealing with maintenance planning first and then train scheduling, or vice versa. In this paper, we propose a joint optimization model for the two problems in a railway network with double-track, where the upstream and downstream trains are independent and a maintenance task on a section cannot be split or disrupted. In order to solve the model, a heuristic algorithm using Lagrangian relaxation is developed. Due to the large number of constraints, we use a dynamic constraint-generation technique in the iterations of the sub-gradient optimization procedure. We apply the model and algorithm to a practical problem in the Chinese railway network, in which some additional trains are inserted into a fixed existing timetable and the maintenance plan on the involved high-speed railway sections is adjusted. The computational results illustrate the effectiveness and efficiency of the proposed model and algorithm. |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0191-2615 1879-2367 |
| DOI: | 10.1016/j.trb.2020.02.008 |