4 Search Results for "Maróti, Gábor"

Document
DOI: 10.4230/LIPIcs.CP.2025.33
Constraint-Based In-Station Train Dispatching

Authors: Andreas Schutt, Matteo Cardellini, Jip J. Dekker, Daniel Harabor, Marco Maratea, and Mauro Vallati

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
In-station dispatching is the problem of planning the movements of scheduled trains inside a railway station. Effective solutions for in-station dispatching are important for maximising the utilisation of railway infrastructure and for mitigating the impact of incidents and delays in the broader network. In this paper, we explore a constraint-based approach to perform in-station train dispatching. Our extensive empirical analysis of multiple modelling, search strategy, and solver choices, performed over synthetically generated, yet realistic, data, shows that our method outperforms the existing planning-based state-of-the-art approach. In addition, we present different optimisation criteria, which can be effortless defined thanks to the constraint-based approach.
Cite as

Andreas Schutt, Matteo Cardellini, Jip J. Dekker, Daniel Harabor, Marco Maratea, and Mauro Vallati. Constraint-Based In-Station Train Dispatching. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 33:1-33:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{schutt_et_al:LIPIcs.CP.2025.33,
  author =	{Schutt, Andreas and Cardellini, Matteo and Dekker, Jip J. and Harabor, Daniel and Maratea, Marco and Vallati, Mauro},
  title =	{{Constraint-Based In-Station Train Dispatching}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{33:1--33:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.33},
  URN =		{urn:nbn:de:0030-drops-238941},
  doi =		{10.4230/LIPIcs.CP.2025.33},
  annote =	{Keywords: in-station train dispatching, train scheduling, railway scheduling, constraint programming, mixed-integer programming}
}
Document
DOI: 10.4230/OASIcs.ATMOS.2019.1
A Cut Separation Approach for the Rolling Stock Rotation Problem with Vehicle Maintenance

Authors: Boris Grimm, Ralf Borndörfer, Markus Reuther, and Thomas Schlechte

Published in: OASIcs, Volume 75, 19th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2019)

Abstract
For providing railway services the company’s railway rolling stock is one if not the most important ingredient. It decides about the number of passenger or cargo trips the company can offer, about the quality a passenger experiences the train ride and it is often related to the image of the company itself. Thus, it is highly desired to have the available rolling stock in the best shape possible. Moreover, in many countries, as Germany where our industrial partner DB Fernverkehr AG (DBF) is located, laws enforce regular vehicle inspections to ensure the safety of the passengers. This leads to rolling stock optimization problems with complex rules for vehicle maintenance. This problem is well studied in the literature for example see [Maróti and Kroon, 2005; Gábor Maróti and Leo G. Kroon, 2007], or [Cordeau et al., 2001] for applications including vehicle maintenance. The contribution of this paper is a new algorithmic approach to solve the Rolling Stock Rotation Problem for the ICE high speed train fleet of DBF with included vehicle maintenance. It is based on a relaxation of a mixed integer linear programming model with an iterative cut generation to enforce the feasibility of a solution of the relaxation in the solution space of the original problem. The resulting mixed integer linear programming model is based on a hypergraph approach presented in [Ralf Borndörfer et al., 2015]. The new approach is tested on real world instances modeling different scenarios for the ICE high speed train network in Germany and compared to the approaches of [Reuther, 2017] that are in operation at DB Fernverkehr AG. The approach shows a significant reduction of the run time to produce solutions with comparable or even better objective function values.
Cite as

Boris Grimm, Ralf Borndörfer, Markus Reuther, and Thomas Schlechte. A Cut Separation Approach for the Rolling Stock Rotation Problem with Vehicle Maintenance. In 19th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2019). Open Access Series in Informatics (OASIcs), Volume 75, pp. 1:1-1:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{grimm_et_al:OASIcs.ATMOS.2019.1,
  author =	{Grimm, Boris and Bornd\"{o}rfer, Ralf and Reuther, Markus and Schlechte, Thomas},
  title =	{{A Cut Separation Approach for the Rolling Stock Rotation Problem with Vehicle Maintenance}},
  booktitle =	{19th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2019)},
  pages =	{1:1--1:12},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-128-3},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{75},
  editor =	{Cacchiani, Valentina and Marchetti-Spaccamela, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2019.1},
  URN =		{urn:nbn:de:0030-drops-114136},
  doi =		{10.4230/OASIcs.ATMOS.2019.1},
  annote =	{Keywords: Railway Operations Research, Integer Programming, Infeasible Path Cuts, Cut Separation, Rolling Stock Rotation Problem}
}
Document
DOI: 10.4230/OASIcs.ATMOS.2010.24
Robust Train Routing and Online Re-scheduling

Authors: Alberto Caprara, Laura Galli, Leo Kroon, Gábor Maróti, and Paolo Toth

Published in: OASIcs, Volume 14, 10th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS'10) (2010)

Abstract
Train Routing is a problem that arises in the early phase of the passenger railway planning process, usually several months before operating the trains. The main goal is to assign each train a stopping platform and the corresponding arrival/departure paths through a railway station. It is also called Train Platforming when referring to the platform assignment task. Railway stations often represent bottlenecks and train delays can easily disrupt the routing schedule. Thereby railway stations are responsible for a large part of the delay propagation in the whole network. In this research we present different models to compute robust routing schedules and we study their power in an online context together with different re-scheduling strategies. We also design a simulation framework and use it to evaluate and compare the effectiveness of the proposed robust models and re-scheduling algorithms using real-world data from Rete Ferroviaria Italiana, the main Italian Railway Infrastructure Manager.
Cite as

Alberto Caprara, Laura Galli, Leo Kroon, Gábor Maróti, and Paolo Toth. Robust Train Routing and Online Re-scheduling. In 10th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS'10). Open Access Series in Informatics (OASIcs), Volume 14, pp. 24-33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

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@InProceedings{caprara_et_al:OASIcs.ATMOS.2010.24,
  author =	{Caprara, Alberto and Galli, Laura and Kroon, Leo and Mar\'{o}ti, G\'{a}bor and Toth, Paolo},
  title =	{{Robust Train Routing and Online Re-scheduling}},
  booktitle =	{10th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS'10)},
  pages =	{24--33},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-20-0},
  ISSN =	{2190-6807},
  year =	{2010},
  volume =	{14},
  editor =	{Erlebach, Thomas and L\"{u}bbecke, Marco},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2010.24},
  URN =		{urn:nbn:de:0030-drops-27470},
  doi =		{10.4230/OASIcs.ATMOS.2010.24},
  annote =	{Keywords: Railway optimisation, Train platforming, Robust planning, Online re-scheduling, Simulation}
}
Document
DOI: 10.4230/OASIcs.ATMOS.2008.1590
Recoverable Robustness for Railway Rolling Stock Planning

Authors: Valentina Cacchiani, Alberto Caprara, Laura Galli, Leo Kroon, and Gábor Maróti

Published in: OASIcs, Volume 9, 8th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS'08) (2008)

Abstract
In this paper we explore the possibility of applying the notions of Recoverable Robustness and Price of Recoverability (introduced by [5]) to railway rolling stock planning, being interested in recoverability measures that can be computed in practice, thereby evaluating the robustness of rolling stock schedules. In order to lower bound the Price of Recoverability for any set of recovery algorithms, we consider an "optimal" recovery algorithm and propose a Benders decomposition approach to assess the Price of Recoverability for this "optimal" algorithm. We evaluate the approach on real-life rolling stock planning problems of NS, the main operator of passenger trains in the Netherlands. The preliminary results show that, thanks to Benders decomposition, our lower bound can be computed within relatively short time for our case study.
Cite as

Valentina Cacchiani, Alberto Caprara, Laura Galli, Leo Kroon, and Gábor Maróti. Recoverable Robustness for Railway Rolling Stock Planning. In 8th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS'08). Open Access Series in Informatics (OASIcs), Volume 9, pp. 1-13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{cacchiani_et_al:OASIcs.ATMOS.2008.1590,
  author =	{Cacchiani, Valentina and Caprara, Alberto and Galli, Laura and Kroon, Leo and Mar\'{o}ti, G\'{a}bor},
  title =	{{Recoverable Robustness for Railway Rolling Stock Planning}},
  booktitle =	{8th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS'08)},
  pages =	{1--13},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-07-1},
  ISSN =	{2190-6807},
  year =	{2008},
  volume =	{9},
  editor =	{Fischetti, Matteo and Widmayer, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2008.1590},
  URN =		{urn:nbn:de:0030-drops-15902},
  doi =		{10.4230/OASIcs.ATMOS.2008.1590},
  annote =	{Keywords: Recoverable robustness, Railway rolling stock scheduling, Benders decomposition}
}
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