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Documents authored by Van Hoeve, Willem-Jan

Document
DOI: 10.4230/LIPIcs.CP.2022.24
Heuristics for MDD Propagation in HADDOCK

Authors: Rebecca Gentzel, Laurent Michel, and Willem-Jan van Hoeve

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

Abstract
Haddock, introduced in [R. Gentzel et al., 2020], is a declarative language and architecture for the specification and the implementation of multi-valued decision diagrams. It relies on a labeled transition system to specify and compose individual constraints into a propagator with filtering capabilities that automatically deliver the expected level of filtering. Yet, the operational potency of the filtering algorithms strongly correlate with heuristics for carrying out refinements of the diagrams. This paper considers how to empower Haddock users with the ability to unobtrusively specify various such heuristics and derive the computational benefits of exerting fine-grained control over the refinement process.
Cite as

Rebecca Gentzel, Laurent Michel, and Willem-Jan van Hoeve. Heuristics for MDD Propagation in HADDOCK. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 24:1-24:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{gentzel_et_al:LIPIcs.CP.2022.24,
  author =	{Gentzel, Rebecca and Michel, Laurent and van Hoeve, Willem-Jan},
  title =	{{Heuristics for MDD Propagation in HADDOCK}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{24:1--24:17},
  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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.24},
  URN =		{urn:nbn:de:0030-drops-166534},
  doi =		{10.4230/LIPIcs.CP.2022.24},
  annote =	{Keywords: Decision Diagrams}
}
Document
DOI: 10.4230/LIPIcs.CP.2022.26
From Cliques to Colorings and Back Again

Authors: Marijn J. H. Heule, Anthony Karahalios, and Willem-Jan van Hoeve

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

Abstract
We present an exact algorithm for graph coloring and maximum clique problems based on SAT technology. It relies on four sub-algorithms that alternatingly compute cliques of larger size and colorings with fewer colors. We show how these techniques can mutually help each other: larger cliques facilitate finding smaller colorings, which in turn can boost finding larger cliques. We evaluate our approach on the DIMACS graph coloring suite. For finding maximum cliques, we show that our algorithm can improve the state-of-the-art MaxSAT-based solver IncMaxCLQ, and for the graph coloring problem, we close two open instances, decrease two upper bounds, and increase one lower bound.
Cite as

Marijn J. H. Heule, Anthony Karahalios, and Willem-Jan van Hoeve. From Cliques to Colorings and Back Again. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 26:1-26:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{heule_et_al:LIPIcs.CP.2022.26,
  author =	{Heule, Marijn J. H. and Karahalios, Anthony and van Hoeve, Willem-Jan},
  title =	{{From Cliques to Colorings and Back Again}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{26:1--26:10},
  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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.26},
  URN =		{urn:nbn:de:0030-drops-166558},
  doi =		{10.4230/LIPIcs.CP.2022.26},
  annote =	{Keywords: Graph coloring, maximum clique, Boolean satisfiability}
}
Document
DOI: 10.4230/DagRep.8.2.26
Planning and Operations Research (Dagstuhl Seminar 18071)

Authors: J. Christopher Beck, Daniele Magazzeni, Gabriele Röger, and Willem-Jan Van Hoeve

Published in: Dagstuhl Reports, Volume 8, Issue 2 (2018)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 18071 "Planning and Operations Research". The seminar brought together researchers in the areas of Artificial Intelligence (AI) Planning, Constraint Programming, and Operations Research. All three areas have in common that they deal with complex systems where a huge space of interacting options makes it almost impossible to humans to take optimal or even good decisions. From a historical perspective, operations research stems from the application of mathematical methods to (mostly) industrial applications while planning and constraint programming emerged as subfields of artificial intelligence where the emphasis was traditionally more on symbolic and logical search techniques for the intelligent selection and sequencing of actions to achieve a set of goals. Therefore operations research often focuses on the allocation of scarce resources such as transportation capacity, machine availability, production materials, or money, while planning focuses on the right choice of actions from a large space of possibilities. While this difference results in problems in different complexity classes, it is often possible to cast the same problem as an OR, CP, or planning problem. In this seminar, we investigated the commonalities and the overlap between the different areas to learn from each other's expertise, bring the communities closer together, and transfer knowledge about solution techniques that can be applied in all areas.
Cite as

J. Christopher Beck, Daniele Magazzeni, Gabriele Röger, and Willem-Jan Van Hoeve. Planning and Operations Research (Dagstuhl Seminar 18071). In Dagstuhl Reports, Volume 8, Issue 2, pp. 26-63, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@Article{beck_et_al:DagRep.8.2.26,
  author =	{Beck, J. Christopher and Magazzeni, Daniele and R\"{o}ger, Gabriele and Van Hoeve, Willem-Jan},
  title =	{{Planning and Operations Research (Dagstuhl Seminar 18071)}},
  pages =	{26--63},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2018},
  volume =	{8},
  number =	{2},
  editor =	{Beck, J. Christopher and Magazzeni, Daniele and R\"{o}ger, Gabriele and Van Hoeve, Willem-Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.8.2.26},
  URN =		{urn:nbn:de:0030-drops-92894},
  doi =		{10.4230/DagRep.8.2.26},
  annote =	{Keywords: Artificial Intelligence, Automated Planning and Scheduling, Constraint Programming, Dynamic Programming, Heuristic Search, Mixed Integer Programming, Operations Research, Optimization, Real-world Applications, Reasoning under Uncertainty}
}
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