8 Search Results for "Katsirelos, George"

Document
DOI: 10.4230/LIPIcs.CP.2026.21
End-to-End Certified Graph Colouring

Authors: Simon Dold, George Katsirelos, Wietze Koops, Magnus O. Myreen, Jakob Nordström, Andy Oertel, and Yong Kiam Tan

Published in: LIPIcs, Volume 379, 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026)

Abstract
Applied combinatorial optimization has witnessed a revolution in performance since the turn of the millennium, but the complexity of modern solvers is making bugs an ever more serious concern. The most promising remedy is to make solvers certifying, so that they use proof logging to generate machine-verifiable proofs of correctness. We present the first example of state-of-the-art certified graph colouring by equipping the solver ZykovColor with VeriPB proof logging. Combined with the formally verified CakePB checker, this provides end-to-end formally certified results. An experimental evaluation shows excellent results with only moderate overhead for proof logging and checking.
Cite as

Simon Dold, George Katsirelos, Wietze Koops, Magnus O. Myreen, Jakob Nordström, Andy Oertel, and Yong Kiam Tan. End-to-End Certified Graph Colouring. In 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 379, pp. 21:1-21:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{dold_et_al:LIPIcs.CP.2026.21,
  author =	{Dold, Simon and Katsirelos, George and Koops, Wietze and Myreen, Magnus O. and Nordstr\"{o}m, Jakob and Oertel, Andy and Tan, Yong Kiam},
  title =	{{End-to-End Certified Graph Colouring}},
  booktitle =	{32nd International Conference on Principles and Practice of Constraint Programming (CP 2026)},
  pages =	{21:1--21:27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-432-1},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{379},
  editor =	{Beldiceanu, Nicolas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2026.21},
  URN =		{urn:nbn:de:0030-drops-266546},
  doi =		{10.4230/LIPIcs.CP.2026.21},
  annote =	{Keywords: graph colouring, proof logging, certifying algorithms}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.4
Conflict Analysis Based on Cutting-Planes for Constraint Programming

Authors: Robbin Baauw, Maarten Flippo, and Emir Demirović

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

Abstract
This paper introduces a novel constraint learning mechanism for Constraint Programming (CP) solvers that integrates cutting planes reasoning into the conflict analysis procedure. Drawing inspiration from Lazy Clause Generation (LCG), our approach, named Lazy Linear Generation (LLG), can generate linear integer inequalities to prune the search space, rather than propositional clauses as in LCG. This combines the strengths of constraint programming (strong propagation through global constraints) with cutting-planes reasoning. We present linear constraint explanations for various arithmetic constraints and the element constraint. An experimental evaluation shows that the improved generality of linear constraints has a practical impact on a CP solver by reducing the number of encountered conflicts in 45% of our benchmark instances. Our analysis and prototype implementation show promising results and are an important step towards a new paradigm to make constraint programming solvers more effective.
Cite as

Robbin Baauw, Maarten Flippo, and Emir Demirović. Conflict Analysis Based on Cutting-Planes for Constraint Programming. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 4:1-4:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{baauw_et_al:LIPIcs.CP.2025.4,
  author =	{Baauw, Robbin and Flippo, Maarten and Demirovi\'{c}, Emir},
  title =	{{Conflict Analysis Based on Cutting-Planes for Constraint Programming}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{4:1--4:19},
  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.2025.4},
  URN =		{urn:nbn:de:0030-drops-238655},
  doi =		{10.4230/LIPIcs.CP.2025.4},
  annote =	{Keywords: constraint programming, learning, conflict analysis}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.8
Breaking Symmetries with Involutions

Authors: Michael Codish and Mikoláš Janota

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

Abstract
Symmetry breaking for graphs and other combinatorial objects is notoriously hard. On the one hand, complete symmetry breaks are exponential in size. On the other hand, current, state-of-the-art, partial symmetry breaks are often considered too weak to be of practical use. Recently, the concept of graph patterns has been introduced and provides a concise representation for (large) sets of non-canonical graphs, i.e. graphs that are not lex-leaders and can be excluded from search. In particular, four (specific) graph patterns apply to identify about 3/4 of the set of all non-canonical graphs. Taking this approach further, we discover that graph patterns that derive from permutations that are involutions play an important role in the construction of symmetry breaks for graphs. We take advantage of this to guide the construction of partial and complete symmetry-breaking constraints based on graph patterns. The resulting constraints are small in size and strong in the number of symmetries they break.
Cite as

Michael Codish and Mikoláš Janota. Breaking Symmetries with Involutions. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 8:1-8:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{codish_et_al:LIPIcs.CP.2025.8,
  author =	{Codish, Michael and Janota, Mikol\'{a}\v{s}},
  title =	{{Breaking Symmetries with Involutions}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{8:1--8:17},
  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.2025.8},
  URN =		{urn:nbn:de:0030-drops-238699},
  doi =		{10.4230/LIPIcs.CP.2025.8},
  annote =	{Keywords: graph symmetry, patterns, permutation, Ramsey graphs, greedy, CEGAR}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.13
Disjunctive Scheduling in Tempo

Authors: Emmanuel Hebrard

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

Abstract
In this paper we introduce a constraint programming lazy clause and literal generation solver embarking ideas from SAT Modulo theories. A key aspect of the solver are Boolean variables with an associated semantic in difference logic, i.e., systems of binary numeric difference constraints or edges, making it particularly adapted to scheduling and other temporal problems. We apply this solver to disjunctive scheduling problems, where edges are used as branching variables, can be inferred via the edge finding rule as well as by transitivity reasoning, and can in turn strengthen propagation via temporal graph reasoning. Our experiments on job-shop scheduling show that a deep integration of these techniques makes our solver competitive with state-of-the-art approaches on these problems.
Cite as

Emmanuel Hebrard. Disjunctive Scheduling in Tempo. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 13:1-13:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{hebrard:LIPIcs.CP.2025.13,
  author =	{Hebrard, Emmanuel},
  title =	{{Disjunctive Scheduling in Tempo}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{13:1--13:22},
  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.2025.13},
  URN =		{urn:nbn:de:0030-drops-238746},
  doi =		{10.4230/LIPIcs.CP.2025.13},
  annote =	{Keywords: Scheduling, Constraint solvers, Clause-learning}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.17
Core-Guided Linear Programming-Based Maximum Satisfiability

Authors: George Katsirelos

Published in: LIPIcs, Volume 341, 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)

Abstract
The core-guided algorithm OLL is the basis of some of the most successful algorithms for MaxSAT in recent evaluations. It works by iteratively finding cores of the formula and transforming it so that it exhibits a higher lower bound. It has recently been shown to implicitly discover cores of the original formula, as well as a compact representation of its reasoning within a linear program. In this paper, we use and extend these results to design a practical MaxSAT solver. We show an explicit linear program which matches and usually exceeds the bound computed by OLL. We show that OLL can be restated as an algorithm that explicitly computes a feasible dual solution of this linear program. This restated algorithm naturally works with an arbitrary dual solution. It can in fact be used to improve any LP representation of the MaxSAT instance. This presents a large increase of the potential design space for such algorithms. We describe some potential improvements from this insight and show that an implementation outperforms the state of the art algorithms on the set of instances from the latest MaxSAT evaluation.
Cite as

George Katsirelos. Core-Guided Linear Programming-Based Maximum Satisfiability. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 17:1-17:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{katsirelos:LIPIcs.SAT.2025.17,
  author =	{Katsirelos, George},
  title =	{{Core-Guided Linear Programming-Based Maximum Satisfiability}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{17:1--17:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-381-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{341},
  editor =	{Berg, Jeremias and Nordstr\"{o}m, Jakob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2025.17},
  URN =		{urn:nbn:de:0030-drops-237513},
  doi =		{10.4230/LIPIcs.SAT.2025.17},
  annote =	{Keywords: maximum satisfiability, core-guided solvers, linear programming}
}
Document
DOI: 10.4230/LIPIcs.SAT.2023.12
An Analysis of Core-Guided Maximum Satisfiability Solvers Using Linear Programming

Authors: George Katsirelos

Published in: LIPIcs, Volume 271, 26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023)

Abstract
Many current complete MaxSAT algorithms fall into two categories: core-guided or implicit hitting set. The two kinds of algorithms seem to have complementary strengths in practice, so that each kind of solver is better able to handle different families of instances. This suggests that a hybrid might match and outperform either, but the techniques used seem incompatible. In this paper, we focus on PMRES and OLL, two core-guided algorithms based on max resolution and soft cardinality constraints, respectively. We show that these algorithms implicitly discover cores of the original formula, as has been previously shown for PM1. Moreover, we show that in some cases, including unweighted instances, they compute the optimum hitting set of these cores at each iteration. We also give compact integer linear programs for each which encode this hitting set problem. Importantly, their continuous relaxation has an optimum that matches the bound computed by the respective algorithms. This goes some way towards resolving the incompatibility of implicit hitting set and core-guided algorithms, since solvers based on the implicit hitting set algorithm typically solve the problem by encoding it as a linear program.
Cite as

George Katsirelos. An Analysis of Core-Guided Maximum Satisfiability Solvers Using Linear Programming. In 26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 271, pp. 12:1-12:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{katsirelos:LIPIcs.SAT.2023.12,
  author =	{Katsirelos, George},
  title =	{{An Analysis of Core-Guided Maximum Satisfiability Solvers Using Linear Programming}},
  booktitle =	{26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023)},
  pages =	{12:1--12:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-286-0},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{271},
  editor =	{Mahajan, Meena and Slivovsky, Friedrich},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2023.12},
  URN =		{urn:nbn:de:0030-drops-184745},
  doi =		{10.4230/LIPIcs.SAT.2023.12},
  annote =	{Keywords: maximum satisfiability, core-guided solvers, minimum hitting set problem, linear programming}
}
Document
DOI: 10.4230/LIPIcs.CP.2022.7
Parallel Hybrid Best-First Search

Authors: Abdelkader Beldjilali, Pierre Montalbano, David Allouche, George Katsirelos, and Simon de Givry

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

Abstract
While processor frequency has stagnated over the past two decades, the number of available cores in servers or clusters is still growing, offering the opportunity for significant speed-up in combinatorial optimization. Parallelization of exact methods remains a difficult challenge. We revisit the concept of parallel Branch-and-Bound in the framework of Cost Function Networks. We show how to adapt the anytime Hybrid Best-First Search algorithm in a Master-Worker protocol. The resulting parallel algorithm achieves good load-balancing without introducing new parameters to be tuned as is the case, for example, in Embarrassingly Parallel Search (EPS). It has also a small overhead due to its light communication messages. We performed an experimental evaluation on several benchmarks, comparing our parallel algorithm to its sequential version. We observed linear speed-up in some cases. Our approach compared favourably to the EPS approach and also to a state-of-the-art parallel exact integer programming solver.
Cite as

Abdelkader Beldjilali, Pierre Montalbano, David Allouche, George Katsirelos, and Simon de Givry. Parallel Hybrid Best-First Search. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 7:1-7:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{beldjilali_et_al:LIPIcs.CP.2022.7,
  author =	{Beldjilali, Abdelkader and Montalbano, Pierre and Allouche, David and Katsirelos, George and de Givry, Simon},
  title =	{{Parallel Hybrid Best-First Search}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{7:1--7:10},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.7},
  URN =		{urn:nbn:de:0030-drops-166362},
  doi =		{10.4230/LIPIcs.CP.2022.7},
  annote =	{Keywords: Combinatorial Optimization, Parallel Branch-and-Bound, CFN}
}
Document
DOI: 10.4230/LIPIcs.CP.2022.37
Structured Set Variable Domains in Bayesian Network Structure Learning

Authors: Fulya Trösser, Simon de Givry, and George Katsirelos

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

Abstract
Constraint programming is a state of the art technique for learning the structure of Bayesian Networks from data (Bayesian Network Structure Learning - BNSL). However, scalability both for CP and other combinatorial optimization techniques for this problem is limited by the fact that the basic decision variables are set variables with domain sizes that may grow super polynomially with the number of random variables. Usual techniques for handling set variables in CP are not useful, as they lead to poor bounds. In this paper, we propose using decision trees as a data structure for storing sets of sets to represent set variable domains. We show that relatively simple operations are sufficient to implement all propagation and bounding algorithms, and that the use of these data structures improves scalability of a state of the art CP-based solver for BNSL.
Cite as

Fulya Trösser, Simon de Givry, and George Katsirelos. Structured Set Variable Domains in Bayesian Network Structure Learning. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 37:1-37:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{trosser_et_al:LIPIcs.CP.2022.37,
  author =	{Tr\"{o}sser, Fulya and de Givry, Simon and Katsirelos, George},
  title =	{{Structured Set Variable Domains in Bayesian Network Structure Learning}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{37:1--37:9},
  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.2022.37},
  URN =		{urn:nbn:de:0030-drops-166661},
  doi =		{10.4230/LIPIcs.CP.2022.37},
  annote =	{Keywords: Combinatorial Optimization, Bayesian Networks, Decision Trees}
}
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