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

Jiří Švancara, Roman Barták

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.

Paper Citation

in Harvard Style

Švancara J. and Barták R. (2022). Tackling Train Routing via Multi-agent Pathfinding and Constraint-based Scheduling. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-547-0, pages 306-313. DOI: 10.5220/0010869700003116

in Bibtex Style

@conference{icaart22,
author={Jiří Švancara and Roman Barták},
title={Tackling Train Routing via Multi-agent Pathfinding and Constraint-based Scheduling},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2022},
pages={306-313},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010869700003116},
isbn={978-989-758-547-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Tackling Train Routing via Multi-agent Pathfinding and Constraint-based Scheduling
SN - 978-989-758-547-0
AU - Švancara J.
AU - Barták R.
PY - 2022
SP - 306
EP - 313
DO - 10.5220/0010869700003116