4 Search Results for "Saint Pierre, Guillaume"

Document
DOI: 10.4230/LIPIcs.CP.2025.32
BFS-Based Canonical Codes for Generating Graphs with Constraint Programming

Authors: Xiao Peng and Christine Solnon

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

Abstract
We consider the problem of generating all graphs that satisfy some given additional constraints (on vertex degrees, or cycle lengths, for example). Most previous works have proposed to generate canonical codes associated with adjacency matrices. In this paper, we consider canonical codes based on Breadth First Search (BFS), and we show how to generate them with Constraint Programming (CP): we introduce a set of basic constraints that must be satisfied by all canonical codes, thus breaking many symmetries, and we introduce a global constraint to break other symmetries. We illustrate the interest of our approach on connected claw-free cubic graphs, and show that it outperforms state-of-the-art CP and SAT Modulo Theory (SMT) approaches.
Cite as

Xiao Peng and Christine Solnon. BFS-Based Canonical Codes for Generating Graphs with Constraint Programming. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 32:1-32:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{peng_et_al:LIPIcs.CP.2025.32,
  author =	{Peng, Xiao and Solnon, Christine},
  title =	{{BFS-Based Canonical Codes for Generating Graphs with Constraint Programming}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{32:1--32:16},
  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.2025.32},
  URN =		{urn:nbn:de:0030-drops-238935},
  doi =		{10.4230/LIPIcs.CP.2025.32},
  annote =	{Keywords: Graph Generation, Automorphisms, Symmetry Breaking}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.6
Modeling and Explaining an Industrial Workforce Allocation and Scheduling Problem

Authors: Ignace Bleukx, Ryma Boumazouza, Tias Guns, Nadine Laage, and Guillaume Poveda

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

Abstract
We present an industrial case on workforce allocation and scheduling in the aircraft manufacturing industry, where available teams need to be assigned to logistical operations. This application presents several challenges such as the scale of the problem, the need for fair workload distribution, and the need for methods for mitigating unforeseen disruptions due to technical malfunctions or incompatible weather conditions. We compare different Constraint Programming (CP) models for the allocation and scheduling problems, with extra focus on modeling the workload balancing component. Additionally, we investigate different techniques for explaining infeasibility of a disrupted schedule, such as conflict computation using Minimal Unsatisfiable Subsets (MUSes) and feasibility restoration using Minimal Correction Subsets (MCSes) or constraint relaxations. Our experimental results show that by using appropriate modeling techniques, the problem can be solved in reasonable time, thereby producing fair schedules. Additionally, we show how invalidated schedules can be explained and restored efficiently to help human operators in solving disruptions to the schedule.
Cite as

Ignace Bleukx, Ryma Boumazouza, Tias Guns, Nadine Laage, and Guillaume Poveda. Modeling and Explaining an Industrial Workforce Allocation and Scheduling Problem. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 6:1-6:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{bleukx_et_al:LIPIcs.CP.2025.6,
  author =	{Bleukx, Ignace and Boumazouza, Ryma and Guns, Tias and Laage, Nadine and Poveda, Guillaume},
  title =	{{Modeling and Explaining an Industrial Workforce Allocation and Scheduling Problem}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{6:1--6:24},
  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.2025.6},
  URN =		{urn:nbn:de:0030-drops-238670},
  doi =		{10.4230/LIPIcs.CP.2025.6},
  annote =	{Keywords: modeling, scheduling, fairness, explanations, feasibility restoration}
}
Document
DOI: 10.4230/LITES.8.2.4
A Hybrid Programming Language for Formal Modeling and Verification of Hybrid Systems

Authors: Eduard Kamburjan, Stefan Mitsch, and Reiner Hähnle

Published in: LITES, Volume 8, Issue 2 (2022): Special Issue on Distributed Hybrid Systems. Leibniz Transactions on Embedded Systems, Volume 8, Issue 2

Abstract
Designing and modeling complex cyber-physical systems (CPS) faces the double challenge of combined discrete-continuous dynamics and concurrent behavior. Existing formal modeling and verification languages for CPS expose the underlying proof search technology. They lack high-level structuring elements and are not efficiently executable. The ensuing modeling gap renders formal CPS models hard to understand and to validate. We propose a high-level programming-based approach to formal modeling and verification of hybrid systems as a hybrid extension of an Active Objects language. Well-structured hybrid active programs and requirements allow automatic, reachability-preserving translation into differential dynamic logic, a logic for hybrid (discrete-continuous) programs. Verification is achieved by discharging the resulting formulas with the theorem prover KeYmaera X. We demonstrate the usability of our approach with case studies.
Cite as

Eduard Kamburjan, Stefan Mitsch, and Reiner Hähnle. A Hybrid Programming Language for Formal Modeling and Verification of Hybrid Systems. In LITES, Volume 8, Issue 2 (2022): Special Issue on Distributed Hybrid Systems. Leibniz Transactions on Embedded Systems, Volume 8, Issue 2, pp. 04:1-04:34, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@Article{kamburjan_et_al:LITES.8.2.4,
  author =	{Kamburjan, Eduard and Mitsch, Stefan and H\"{a}hnle, Reiner},
  title =	{{A Hybrid Programming Language for Formal Modeling and Verification of Hybrid Systems}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{04:1--04:34},
  ISSN =	{2199-2002},
  year =	{2022},
  volume =	{8},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES.8.2.4},
  URN =		{urn:nbn:de:0030-drops-192965},
  doi =		{10.4230/LITES.8.2.4},
  annote =	{Keywords: Active Objects, Differential Dynamic Logic, Hybrid Systems}
}
Document
DOI: 10.4230/LIPIcs.GISCIENCE.2018.11
Detection and Localization of Traffic Signals with GPS Floating Car Data and Random Forest

Authors: Yann Méneroux, Hiroshi Kanasugi, Guillaume Saint Pierre, Arnaud Le Guilcher, Sébastien Mustière, Ryosuke Shibasaki, and Yugo Kato

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract
As Floating Car Data are becoming increasingly available, in recent years many research works focused on leveraging them to infer road map geometry, topology and attributes. In this paper, we present an algorithm, relying on supervised learning to detect and localize traffic signals based on the spatial distribution of vehicle stop points. Our main contribution is to provide a single framework to address both problems. The proposed method has been experimented with a one-month dataset of real-world GPS traces, collected on the road network of Mitaka (Japan). The results show that this method provides accurate results in terms of localization and performs advantageously compared to the OpenStreetMap database in exhaustivity. Among many potential applications, the output predictions may be used as a prior map and/or combined with other sources of data to guide autonomous vehicles.
Cite as

Yann Méneroux, Hiroshi Kanasugi, Guillaume Saint Pierre, Arnaud Le Guilcher, Sébastien Mustière, Ryosuke Shibasaki, and Yugo Kato. Detection and Localization of Traffic Signals with GPS Floating Car Data and Random Forest. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 11:1-11:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{meneroux_et_al:LIPIcs.GISCIENCE.2018.11,
  author =	{M\'{e}neroux, Yann and Kanasugi, Hiroshi and Saint Pierre, Guillaume and Le Guilcher, Arnaud and Musti\`{e}re, S\'{e}bastien and Shibasaki, Ryosuke and Kato, Yugo},
  title =	{{Detection and Localization of Traffic Signals with GPS Floating Car Data and Random Forest}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{11:1--11:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.11},
  URN =		{urn:nbn:de:0030-drops-93397},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.11},
  annote =	{Keywords: Map Inference, Machine Learning, GPS Traces, Traffic Signal}
}
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