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Documents authored by van Hentenryck, Pascal

Found 2 Possible Name Variants:

Van Hentenryck, Pascal

Document
DOI: 10.4230/LIPIcs.CP.2024.16
A New Optimization Model for Multiple-Control Toffoli Quantum Circuit Design

Authors: Jihye Jung, Kevin Dalmeijer, and Pascal Van Hentenryck

Published in: LIPIcs, Volume 307, 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)

Abstract
As quantum technology is advancing, the efficient design of quantum circuits has become an important area of research. This paper provides an introduction to the MCT quantum circuit design problem for reversible Boolean functions without assuming a prior background in quantum computing. While this is a well-studied problem, optimization models that minimize the true objective have only been explored recently. This paper introduces a new optimization model and symmetry-breaking constraints that improve solving time by up to two orders of magnitude compared to earlier work when a Constraint Programming solver is used. Experiments with up to seven qubits and using up to 15 quantum gates result in several new best-known circuits, obtained by any method, for well-known benchmarks. Finally, an extensive comparison with other approaches shows that optimization models may require more time but can provide superior circuits with optimality guarantees.
Cite as

Jihye Jung, Kevin Dalmeijer, and Pascal Van Hentenryck. A New Optimization Model for Multiple-Control Toffoli Quantum Circuit Design. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 16:1-16:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{jung_et_al:LIPIcs.CP.2024.16,
  author =	{Jung, Jihye and Dalmeijer, Kevin and Van Hentenryck, Pascal},
  title =	{{A New Optimization Model for Multiple-Control Toffoli Quantum Circuit Design}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{16:1--16:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-336-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{307},
  editor =	{Shaw, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2024.16},
  URN =		{urn:nbn:de:0030-drops-207010},
  doi =		{10.4230/LIPIcs.CP.2024.16},
  annote =	{Keywords: Constraint Programming, Quantum Circuit Design, Reversible Circuits}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.CP.2023.46
Constraint Programming to Improve Hub Utilization in Autonomous Transfer Hub Networks (Short Paper)

Authors: Chungjae Lee, Wirattawut Boonbandansook, Vahid Eghbal Akhlaghi, Kevin Dalmeijer, and Pascal Van Hentenryck

Published in: LIPIcs, Volume 280, 29th International Conference on Principles and Practice of Constraint Programming (CP 2023)

Abstract
The Autonomous Transfer Hub Network (ATHN) is one of the most promising ways to adapt self-driving trucks for the freight industry. These networks use autonomous trucks for the middle mile, while human drivers perform the first and last miles. This paper extends previous work on optimizing ATHN operations by including transfer hub capacities, which are crucial for labor planning and policy design. It presents a Constraint Programming (CP) model that shifts an initial schedule produced by a Mixed Integer Program to minimize the hub capacities. The scalability of the CP model is demonstrated on a case study at the scale of the United States, based on data provided by Ryder System, Inc. The CP model efficiently finds optimal solutions and lowers the necessary total hub capacity by 42%, saving $15.2M in annual labor costs. The results also show that the reduced capacity is close to a theoretical (optimistic) lower bound.
Cite as

Chungjae Lee, Wirattawut Boonbandansook, Vahid Eghbal Akhlaghi, Kevin Dalmeijer, and Pascal Van Hentenryck. Constraint Programming to Improve Hub Utilization in Autonomous Transfer Hub Networks (Short Paper). In 29th International Conference on Principles and Practice of Constraint Programming (CP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 280, pp. 46:1-46:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{lee_et_al:LIPIcs.CP.2023.46,
  author =	{Lee, Chungjae and Boonbandansook, Wirattawut and Akhlaghi, Vahid Eghbal and Dalmeijer, Kevin and Van Hentenryck, Pascal},
  title =	{{Constraint Programming to Improve Hub Utilization in Autonomous Transfer Hub Networks}},
  booktitle =	{29th International Conference on Principles and Practice of Constraint Programming (CP 2023)},
  pages =	{46:1--46:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-300-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{280},
  editor =	{Yap, Roland H. C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2023.46},
  URN =		{urn:nbn:de:0030-drops-190835},
  doi =		{10.4230/LIPIcs.CP.2023.46},
  annote =	{Keywords: Constraint Programming, Autonomous Trucking, Tranfer Hub Network}
}
Document
DOI: 10.4230/LIPIcs.CP.2022.19
Sequence Variables for Routing Problems

Authors: Augustin Delecluse, Pierre Schaus, and Pascal Van Hentenryck

Published in: LIPIcs, Volume 235, 28th International Conference on Principles and Practice of Constraint Programming (CP 2022)

Abstract
Constraint Programming (CP) is one of the most flexible approaches for modeling and solving vehicle routing problems (VRP). This paper proposes the sequence variable domain, that is inspired by the insertion graph introduced in [Bent and Van Hentenryck, 2004] and the subset bound domain for set variables. This domain representation, which targets VRP applications, allows for an efficient insertion-based search on a partial tour and the implementation of simple, yet efficient filtering algorithms for constraints that enforce time-windows on the visits and capacities on the vehicles. Experiment results demonstrate the efficiency and flexibility of this CP domain for solving some hard VRP problems, including the Dial-A-Ride, the Patient Transportation, and the asymmetric TSP with time windows.
Cite as

Augustin Delecluse, Pierre Schaus, and Pascal Van Hentenryck. Sequence Variables for Routing Problems. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 19:1-19:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{delecluse_et_al:LIPIcs.CP.2022.19,
  author =	{Delecluse, Augustin and Schaus, Pierre and Van Hentenryck, Pascal},
  title =	{{Sequence Variables for Routing Problems}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{19:1--19:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-240-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{235},
  editor =	{Solnon, Christine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.19},
  URN =		{urn:nbn:de:0030-drops-166485},
  doi =		{10.4230/LIPIcs.CP.2022.19},
  annote =	{Keywords: Constraint Programming, Dial-A-Ride, Patient Transportation, TSPTW, Vehicle Routing, Sequence Variables, Insertion Variables}
}
Document
DOI: 10.4230/DagRep.1.5.61
Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201)

Authors: Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, and Pascal Van Hentenryck

Published in: Dagstuhl Reports, Volume 1, Issue 5 (2011)

Abstract
This report documents the programme and the outcomes of Dagstuhl Seminar 11201 "Constraint Programming meets Machine Learning and Data Mining". Our starting point in this seminar was that machine learning and data mining have developed largely independently from constraint programming till now, but that it is increasingly becoming clear that there are many opportunities for interactions between these areas: on the one hand, data mining and machine learning can be used to improve constraint solving; on the other hand, constraint solving can be used in data mining in machine learning. This seminar brought together prominent researchers from both communities to discuss these opportunities.
Cite as

Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, and Pascal Van Hentenryck. Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201). In Dagstuhl Reports, Volume 1, Issue 5, pp. 61-83, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

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@Article{deraedt_et_al:DagRep.1.5.61,
  author =	{De Raedt, Luc and Nijssen, Siegfried and O'Sullivan, Barry and Van Hentenryck, Pascal},
  title =	{{Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201)}},
  pages =	{61--83},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2011},
  volume =	{1},
  number =	{5},
  editor =	{De Raedt, Luc and Nijssen, Siegfried and O'Sullivan, Barry and Van Hentenryck, Pascal},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.1.5.61},
  URN =		{urn:nbn:de:0030-drops-32077},
  doi =		{10.4230/DagRep.1.5.61},
  annote =	{Keywords: Machine learning, data mining, constraint programming, constraints}
}
Document
DOI: 10.4230/DagSemRep.262
Constraint Programming and Integer Programming (Dagstuhl Seminar 00031)

Authors: Krysztof Apt, Michael Jünger, Pascal van Hentenryck, and Laurence A. Wolsey

Published in: Dagstuhl Seminar Reports. Dagstuhl Seminar Reports, Volume 1 (2021)

Abstract
Cite as

Krysztof Apt, Michael Jünger, Pascal van Hentenryck, and Laurence A. Wolsey. Constraint Programming and Integer Programming (Dagstuhl Seminar 00031). Dagstuhl Seminar Report 262, pp. 1-20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2000)

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@TechReport{apt_et_al:DagSemRep.262,
  author =	{Apt, Krysztof and J\"{u}nger, Michael and van Hentenryck, Pascal and Wolsey, Laurence A.},
  title =	{{Constraint Programming and Integer Programming (Dagstuhl Seminar 00031)}},
  pages =	{1--20},
  ISSN =	{1619-0203},
  year =	{2000},
  type = 	{Dagstuhl Seminar Report},
  number =	{262},
  institution =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemRep.262},
  URN =		{urn:nbn:de:0030-drops-151477},
  doi =		{10.4230/DagSemRep.262},
}

van Hentenryck, Pascal

Document
DOI: 10.4230/LIPIcs.CP.2024.16
A New Optimization Model for Multiple-Control Toffoli Quantum Circuit Design

Authors: Jihye Jung, Kevin Dalmeijer, and Pascal Van Hentenryck

Published in: LIPIcs, Volume 307, 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)

Abstract
As quantum technology is advancing, the efficient design of quantum circuits has become an important area of research. This paper provides an introduction to the MCT quantum circuit design problem for reversible Boolean functions without assuming a prior background in quantum computing. While this is a well-studied problem, optimization models that minimize the true objective have only been explored recently. This paper introduces a new optimization model and symmetry-breaking constraints that improve solving time by up to two orders of magnitude compared to earlier work when a Constraint Programming solver is used. Experiments with up to seven qubits and using up to 15 quantum gates result in several new best-known circuits, obtained by any method, for well-known benchmarks. Finally, an extensive comparison with other approaches shows that optimization models may require more time but can provide superior circuits with optimality guarantees.
Cite as

Jihye Jung, Kevin Dalmeijer, and Pascal Van Hentenryck. A New Optimization Model for Multiple-Control Toffoli Quantum Circuit Design. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 16:1-16:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{jung_et_al:LIPIcs.CP.2024.16,
  author =	{Jung, Jihye and Dalmeijer, Kevin and Van Hentenryck, Pascal},
  title =	{{A New Optimization Model for Multiple-Control Toffoli Quantum Circuit Design}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{16:1--16:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-336-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{307},
  editor =	{Shaw, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2024.16},
  URN =		{urn:nbn:de:0030-drops-207010},
  doi =		{10.4230/LIPIcs.CP.2024.16},
  annote =	{Keywords: Constraint Programming, Quantum Circuit Design, Reversible Circuits}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.CP.2023.46
Constraint Programming to Improve Hub Utilization in Autonomous Transfer Hub Networks (Short Paper)

Authors: Chungjae Lee, Wirattawut Boonbandansook, Vahid Eghbal Akhlaghi, Kevin Dalmeijer, and Pascal Van Hentenryck

Published in: LIPIcs, Volume 280, 29th International Conference on Principles and Practice of Constraint Programming (CP 2023)

Abstract
The Autonomous Transfer Hub Network (ATHN) is one of the most promising ways to adapt self-driving trucks for the freight industry. These networks use autonomous trucks for the middle mile, while human drivers perform the first and last miles. This paper extends previous work on optimizing ATHN operations by including transfer hub capacities, which are crucial for labor planning and policy design. It presents a Constraint Programming (CP) model that shifts an initial schedule produced by a Mixed Integer Program to minimize the hub capacities. The scalability of the CP model is demonstrated on a case study at the scale of the United States, based on data provided by Ryder System, Inc. The CP model efficiently finds optimal solutions and lowers the necessary total hub capacity by 42%, saving $15.2M in annual labor costs. The results also show that the reduced capacity is close to a theoretical (optimistic) lower bound.
Cite as

Chungjae Lee, Wirattawut Boonbandansook, Vahid Eghbal Akhlaghi, Kevin Dalmeijer, and Pascal Van Hentenryck. Constraint Programming to Improve Hub Utilization in Autonomous Transfer Hub Networks (Short Paper). In 29th International Conference on Principles and Practice of Constraint Programming (CP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 280, pp. 46:1-46:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{lee_et_al:LIPIcs.CP.2023.46,
  author =	{Lee, Chungjae and Boonbandansook, Wirattawut and Akhlaghi, Vahid Eghbal and Dalmeijer, Kevin and Van Hentenryck, Pascal},
  title =	{{Constraint Programming to Improve Hub Utilization in Autonomous Transfer Hub Networks}},
  booktitle =	{29th International Conference on Principles and Practice of Constraint Programming (CP 2023)},
  pages =	{46:1--46:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-300-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{280},
  editor =	{Yap, Roland H. C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2023.46},
  URN =		{urn:nbn:de:0030-drops-190835},
  doi =		{10.4230/LIPIcs.CP.2023.46},
  annote =	{Keywords: Constraint Programming, Autonomous Trucking, Tranfer Hub Network}
}
Document
DOI: 10.4230/LIPIcs.CP.2022.19
Sequence Variables for Routing Problems

Authors: Augustin Delecluse, Pierre Schaus, and Pascal Van Hentenryck

Published in: LIPIcs, Volume 235, 28th International Conference on Principles and Practice of Constraint Programming (CP 2022)

Abstract
Constraint Programming (CP) is one of the most flexible approaches for modeling and solving vehicle routing problems (VRP). This paper proposes the sequence variable domain, that is inspired by the insertion graph introduced in [Bent and Van Hentenryck, 2004] and the subset bound domain for set variables. This domain representation, which targets VRP applications, allows for an efficient insertion-based search on a partial tour and the implementation of simple, yet efficient filtering algorithms for constraints that enforce time-windows on the visits and capacities on the vehicles. Experiment results demonstrate the efficiency and flexibility of this CP domain for solving some hard VRP problems, including the Dial-A-Ride, the Patient Transportation, and the asymmetric TSP with time windows.
Cite as

Augustin Delecluse, Pierre Schaus, and Pascal Van Hentenryck. Sequence Variables for Routing Problems. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 19:1-19:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

Copy BibTex To Clipboard

@InProceedings{delecluse_et_al:LIPIcs.CP.2022.19,
  author =	{Delecluse, Augustin and Schaus, Pierre and Van Hentenryck, Pascal},
  title =	{{Sequence Variables for Routing Problems}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{19:1--19:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-240-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{235},
  editor =	{Solnon, Christine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.19},
  URN =		{urn:nbn:de:0030-drops-166485},
  doi =		{10.4230/LIPIcs.CP.2022.19},
  annote =	{Keywords: Constraint Programming, Dial-A-Ride, Patient Transportation, TSPTW, Vehicle Routing, Sequence Variables, Insertion Variables}
}
Document
DOI: 10.4230/DagRep.1.5.61
Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201)

Authors: Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, and Pascal Van Hentenryck

Published in: Dagstuhl Reports, Volume 1, Issue 5 (2011)

Abstract
This report documents the programme and the outcomes of Dagstuhl Seminar 11201 "Constraint Programming meets Machine Learning and Data Mining". Our starting point in this seminar was that machine learning and data mining have developed largely independently from constraint programming till now, but that it is increasingly becoming clear that there are many opportunities for interactions between these areas: on the one hand, data mining and machine learning can be used to improve constraint solving; on the other hand, constraint solving can be used in data mining in machine learning. This seminar brought together prominent researchers from both communities to discuss these opportunities.
Cite as

Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, and Pascal Van Hentenryck. Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201). In Dagstuhl Reports, Volume 1, Issue 5, pp. 61-83, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

Copy BibTex To Clipboard

@Article{deraedt_et_al:DagRep.1.5.61,
  author =	{De Raedt, Luc and Nijssen, Siegfried and O'Sullivan, Barry and Van Hentenryck, Pascal},
  title =	{{Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201)}},
  pages =	{61--83},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2011},
  volume =	{1},
  number =	{5},
  editor =	{De Raedt, Luc and Nijssen, Siegfried and O'Sullivan, Barry and Van Hentenryck, Pascal},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.1.5.61},
  URN =		{urn:nbn:de:0030-drops-32077},
  doi =		{10.4230/DagRep.1.5.61},
  annote =	{Keywords: Machine learning, data mining, constraint programming, constraints}
}
Document
DOI: 10.4230/DagSemRep.262
Constraint Programming and Integer Programming (Dagstuhl Seminar 00031)

Authors: Krysztof Apt, Michael Jünger, Pascal van Hentenryck, and Laurence A. Wolsey

Published in: Dagstuhl Seminar Reports. Dagstuhl Seminar Reports, Volume 1 (2021)

Abstract
Cite as

Krysztof Apt, Michael Jünger, Pascal van Hentenryck, and Laurence A. Wolsey. Constraint Programming and Integer Programming (Dagstuhl Seminar 00031). Dagstuhl Seminar Report 262, pp. 1-20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2000)

Copy BibTex To Clipboard

@TechReport{apt_et_al:DagSemRep.262,
  author =	{Apt, Krysztof and J\"{u}nger, Michael and van Hentenryck, Pascal and Wolsey, Laurence A.},
  title =	{{Constraint Programming and Integer Programming (Dagstuhl Seminar 00031)}},
  pages =	{1--20},
  ISSN =	{1619-0203},
  year =	{2000},
  type = 	{Dagstuhl Seminar Report},
  number =	{262},
  institution =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemRep.262},
  URN =		{urn:nbn:de:0030-drops-151477},
  doi =		{10.4230/DagSemRep.262},
}
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