4 Search Results for "Matheis, Oliver"

Document
PACE Solver Description
DOI: 10.4230/LIPIcs.IPEC.2025.37
PACE Solver Description: Minimum Hitting Set Computation via Core-Guided MaxSAT Solving

Authors: André Schidler

Published in: LIPIcs, Volume 358, 20th International Symposium on Parameterized and Exact Computation (IPEC 2025)

Abstract
This paper describes our hybrid MaxSAT and mixed integer programming approach for finding minimum hitting sets as submitted to the 2025 PACE challenge. We also discuss hitting set specific challenges, lower bounds, preprocessing and design choices.
Cite as

André Schidler. PACE Solver Description: Minimum Hitting Set Computation via Core-Guided MaxSAT Solving. In 20th International Symposium on Parameterized and Exact Computation (IPEC 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 358, pp. 37:1-37:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{schidler:LIPIcs.IPEC.2025.37,
  author =	{Schidler, Andr\'{e}},
  title =	{{PACE Solver Description: Minimum Hitting Set Computation via Core-Guided MaxSAT Solving}},
  booktitle =	{20th International Symposium on Parameterized and Exact Computation (IPEC 2025)},
  pages =	{37:1--37:4},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-407-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{358},
  editor =	{Agrawal, Akanksha and van Leeuwen, Erik Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.IPEC.2025.37},
  URN =		{urn:nbn:de:0030-drops-251692},
  doi =		{10.4230/LIPIcs.IPEC.2025.37},
  annote =	{Keywords: hitting set, maxsat, core-guided}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.26
Analyzing Reformulation Performance in Core-Guided MaxSAT Solving

Authors: André Schidler and Stefan Szeider

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

Abstract
Core-guided algorithms like OLL are among the best methods for solving the Maximum Satisfiability problem (MaxSAT). Although some performance characteristics of OLL have been studied, a comprehensive experimental analysis of its reformulation behavior is still missing. In this paper, we present a large-scale study on how different reformulations of a MaxSAT instance produced by OLL affect solver performance. By representing these reformulations as a directed acyclic graph (DAG), we isolate the impact of structural features - such as the size and interconnectivity of unsatisfiable cores - on solver runtime. Our extensive experimental evaluation of over 600k solver runs reveals clear correlations between DAG properties and performance outcomes. These results suggest a new avenue for designing heuristics that steer the solver toward more tractable reformulations. All OLL DAGs and performance data from our experiments are publicly available to foster further research.
Cite as

André Schidler and Stefan Szeider. Analyzing Reformulation Performance in Core-Guided MaxSAT Solving. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 26:1-26:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{schidler_et_al:LIPIcs.SAT.2025.26,
  author =	{Schidler, Andr\'{e} and Szeider, Stefan},
  title =	{{Analyzing Reformulation Performance in Core-Guided MaxSAT Solving}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{26:1--26:18},
  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.2025.26},
  URN =		{urn:nbn:de:0030-drops-237605},
  doi =		{10.4230/LIPIcs.SAT.2025.26},
  annote =	{Keywords: maximum satisfiability, OLL, core-guided}
}
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.ICLP.2012.211
Unsatisfiability-based optimization in clasp

Authors: Benjamin Andres, Benjamin Kaufmann, Oliver Matheis, and Torsten Schaub

Published in: LIPIcs, Volume 17, Technical Communications of the 28th International Conference on Logic Programming (ICLP'12) (2012)

Abstract
Answer Set Programming (ASP) features effective optimization capacities based on branch-and-bound algorithms. Unlike this, in the area of Satisfiability Testing (SAT) the finding of minimum unsatisfiable cores was put forward as an alternative approach to solving Maximum Satisfiability (MaxSAT) problems. We explore this alternative approach to optimization in the context of ASP. To this end, we extended the ASP solver clasp with optimization components based upon the computation of minimal unsatisfiable cores. The resulting system, unclasp, is based on an extension of the well-known algorithms msu1 and msu3 and tailored to the characteristics of ASP. We evaluate our system on multi-criteria optimization problems stemming from realistic Linux package configuration problems. In fact, the ASP-based Linux configuration system aspuncud relies on unclasp and won four out of seven tracks at the 2011 MISC competition.
Cite as

Benjamin Andres, Benjamin Kaufmann, Oliver Matheis, and Torsten Schaub. Unsatisfiability-based optimization in clasp. In Technical Communications of the 28th International Conference on Logic Programming (ICLP'12). Leibniz International Proceedings in Informatics (LIPIcs), Volume 17, pp. 212-221, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{andres_et_al:LIPIcs.ICLP.2012.211,
  author =	{Andres, Benjamin and Kaufmann, Benjamin and Matheis, Oliver and Schaub, Torsten},
  title =	{{Unsatisfiability-based optimization in clasp}},
  booktitle =	{Technical Communications of the 28th International Conference on Logic Programming (ICLP'12)},
  pages =	{212--221},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-43-9},
  ISSN =	{1868-8969},
  year =	{2012},
  volume =	{17},
  editor =	{Dovier, Agostino and Santos Costa, V{\'\i}tor},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICLP.2012.211},
  URN =		{urn:nbn:de:0030-drops-36235},
  doi =		{10.4230/LIPIcs.ICLP.2012.211},
  annote =	{Keywords: answer-set-programming, solvers}
}
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