TY - JOUR
T1 - Comparing Lazy Constraint Selection Strategies in Train Routing with Moving Block Control
AU - Engels, Stefan
AU - Wille, Robert
N1 - Publisher Copyright:
© 2024 Polish Information Processing Society.
PY - 2024
Y1 - 2024
N2 - Railroad transportation plays a vital role in the future of sustainable mobility. Besides building new infrastructure, capacity can be improved by modern train control systems, e.g., based on moving blocks. At the same time, there is only limited work on how to optimally route trains using the potential gained by these systems. Recently, an initial approach for train routing with moving block control has been proposed to address this demand. However, detailed evaluations on so-called lazy constraints are missing, and no publicly available implementation exists. In this work, we close this gap by providing an extended approach as well as a flexible open-source implementation that can use different solving strategies. Using that, we experimentally evaluate what choices should be made when implementing a lazy constraint approach. The corresponding implementation and benchmarks are publicly available as part of the Munich Train Control Toolkit (MTCT) at https://github.com/cda-tum/mtct.
AB - Railroad transportation plays a vital role in the future of sustainable mobility. Besides building new infrastructure, capacity can be improved by modern train control systems, e.g., based on moving blocks. At the same time, there is only limited work on how to optimally route trains using the potential gained by these systems. Recently, an initial approach for train routing with moving block control has been proposed to address this demand. However, detailed evaluations on so-called lazy constraints are missing, and no publicly available implementation exists. In this work, we close this gap by providing an extended approach as well as a flexible open-source implementation that can use different solving strategies. Using that, we experimentally evaluate what choices should be made when implementing a lazy constraint approach. The corresponding implementation and benchmarks are publicly available as part of the Munich Train Control Toolkit (MTCT) at https://github.com/cda-tum/mtct.
UR - http://www.scopus.com/inward/record.url?scp=85212264309&partnerID=8YFLogxK
U2 - 10.15439/2024F3041
DO - 10.15439/2024F3041
M3 - Conference article
AN - SCOPUS:85212264309
SN - 2300-5963
SP - 585
EP - 590
JO - Annals of Computer Science and Intelligence Systems
JF - Annals of Computer Science and Intelligence Systems
IS - 2024
T2 - 19th Conference on Computer Science and Intelligence Systems, FedCSIS 2024
Y2 - 8 September 2024 through 11 September 2024
ER -