Optimization models for railway traffic rescheduling in the last decade tend to develop along two main streams. One the one hand, train scheduling models strives to incorporate any relevant detail of the railway infrastructure having an impact on the feasibility and quality of the solutions from the viewpoint of operations managers. On the other hand, delay management models focus on the impact of rescheduling decisions on the quality of service perceived by the passengers. Models in the first stream are mainly microscopic, while models in the second stream are mainly macroscopic. This paper aims at merging these two streams of research by developing microscopic passenger-centric models, solution algorithms and lower bounds. Fast iterative algorithms are proposed, based on a decomposition of the problem and on the exact resolution of the subproblems. A new lower bound is proposed, consisting of the resolution of a set of min-cost flow problems with activation constraints. Computational experiments, based on a real-world Dutch railway network, show that good quality solutions and lower bounds can be found within a limited computation time.
- Train Scheduling
- Delay Management
- Passenger Routing
- Mixed-Linear Integer Programming
- Min-Cost Flow