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Documents authored by Harabor, Daniel

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.
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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/LIPIcs.CP.2021.11
Vehicle Dynamics in Pickup-And-Delivery Problems Using Electric Vehicles

Authors: Saman Ahmadi, Guido Tack, Daniel Harabor, and Philip Kilby

Published in: LIPIcs, Volume 210, 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)

Abstract
Electric Vehicles (EVs) are set to replace vehicles based on internal combustion engines. Path planning and vehicle routing for EVs need to take their specific characteristics into account, such as reduced range, long charging times, and energy recuperation. This paper investigates the importance of vehicle dynamics parameters in energy models for EV routing, particularly in the Pickup-and-Delivery Problem (PDP). We use Constraint Programming (CP) technology to develop a complete PDP model with different charger technologies. We adapt realistic instances that consider vehicle dynamics parameters such as vehicle mass, road gradient and driving speed to varying degrees. The results of our experiments show that neglecting such fundamental vehicle dynamics parameters can affect the feasibility of planned routes for EVs, and fewer/shorter charging visits will be planned if we use energy-efficient paths instead of conventional shortest paths in the underlying system model.
Cite as

Saman Ahmadi, Guido Tack, Daniel Harabor, and Philip Kilby. Vehicle Dynamics in Pickup-And-Delivery Problems Using Electric Vehicles. In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 210, pp. 11:1-11:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{ahmadi_et_al:LIPIcs.CP.2021.11,
  author =	{Ahmadi, Saman and Tack, Guido and Harabor, Daniel and Kilby, Philip},
  title =	{{Vehicle Dynamics in Pickup-And-Delivery Problems Using Electric Vehicles}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{11:1--11:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2021.11},
  URN =		{urn:nbn:de:0030-drops-153020},
  doi =		{10.4230/LIPIcs.CP.2021.11},
  annote =	{Keywords: Electric vehicle routing, pickup-and-delivery problem, vehicle dynamics}
}
Document
DOI: 10.4230/LIPIcs.ESA.2021.3
Bi-Objective Search with Bi-Directional A*

Authors: Saman Ahmadi, Guido Tack, Daniel Harabor, and Philip Kilby

Published in: LIPIcs, Volume 204, 29th Annual European Symposium on Algorithms (ESA 2021)

Abstract
Bi-objective search is a well-known algorithmic problem, concerned with finding a set of optimal solutions in a two-dimensional domain. This problem has a wide variety of applications such as planning in transport systems or optimal control in energy systems. Recently, bi-objective A*-based search (BOA*) has shown state-of-the-art performance in large networks. This paper develops a bi-directional and parallel variant of BOA*, enriched with several speed-up heuristics. Our experimental results on 1,000 benchmark cases show that our bi-directional A* algorithm for bi-objective search (BOBA*) can optimally solve all of the benchmark cases within the time limit, outperforming the state of the art BOA*, bi-objective Dijkstra and bi-directional bi-objective Dijkstra by an average runtime improvement of a factor of five over all of the benchmark instances.
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Saman Ahmadi, Guido Tack, Daniel Harabor, and Philip Kilby. Bi-Objective Search with Bi-Directional A*. In 29th Annual European Symposium on Algorithms (ESA 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 204, pp. 3:1-3:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{ahmadi_et_al:LIPIcs.ESA.2021.3,
  author =	{Ahmadi, Saman and Tack, Guido and Harabor, Daniel and Kilby, Philip},
  title =	{{Bi-Objective Search with Bi-Directional A*}},
  booktitle =	{29th Annual European Symposium on Algorithms (ESA 2021)},
  pages =	{3:1--3:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-204-4},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{204},
  editor =	{Mutzel, Petra and Pagh, Rasmus and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2021.3},
  URN =		{urn:nbn:de:0030-drops-145849},
  doi =		{10.4230/LIPIcs.ESA.2021.3},
  annote =	{Keywords: Bi-objective search, heuristic search, shortest path problem}
}
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