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Tackling Train Routing via Multi-agent Pathfinding and Constraint-based Scheduling

Publication at Faculty of Mathematics and Physics |
2022

Abstract

The train routing problem deals with allocating railway tracks to trains so that the trains follow their timetables and there are no collisions among the trains (all safety rules are followed). This paper studies the train routing problem from the multi-agent pathfinding (MAPF) perspective, which proved very efficient for collision-free path planning of multiple agents in a shared environment.

Specifically, we modify a reduction-based MAPF model to cover the peculiarities of the train routing problem (various train lengths, in particular), and we also propose a new constraint-based scheduling model with optional activities. We compare the two models both theoretically and empirically.