Certifying Without Loss of Generality Reasoning in Solution-Improving Maximum Satisfiability
(2024) 30th International Conference on Principles and Practice of Constraint Programming, CP 2024 In Leibniz International Proceedings in Informatics (LIPIcs) 307.- Abstract
- Proof logging has long been the established method to certify correctness of Boolean satisfiability (SAT) solvers, but has only recently been introduced for SAT-based optimization (MaxSAT). The focus of this paper is solution-improving search (SIS), in which a SAT solver is iteratively queried for increasingly better solutions until an optimal one is found. A challenging aspect of modern SIS solvers is that they make use of complex "without loss of generality" arguments that are quite involved to understand even at a human meta-level, let alone to express in a simple, machine-verifiable proof. In this work, we develop pseudo-Boolean proof logging methods for solution-improving MaxSAT solving, and use them to produce a certifying version of... (More)
- Proof logging has long been the established method to certify correctness of Boolean satisfiability (SAT) solvers, but has only recently been introduced for SAT-based optimization (MaxSAT). The focus of this paper is solution-improving search (SIS), in which a SAT solver is iteratively queried for increasingly better solutions until an optimal one is found. A challenging aspect of modern SIS solvers is that they make use of complex "without loss of generality" arguments that are quite involved to understand even at a human meta-level, let alone to express in a simple, machine-verifiable proof. In this work, we develop pseudo-Boolean proof logging methods for solution-improving MaxSAT solving, and use them to produce a certifying version of the state-of-the-art solver Pacose with VeriPB proofs. Our experimental evaluation demonstrates that this approach works in practice. We hope that this is yet another step towards general adoption of proof logging in MaxSAT solving. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1db54cf4-755f-48c1-bc46-4086acc5891e
- author
- Berg, Jeremias
; Bogaerts, Bart
; Nordström, Jakob
LU
; Oertel, Andy
LU
; Paxian, Tobias and Vandesande, Dieter
- organization
- publishing date
- 2024-08-29
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)
- series title
- Leibniz International Proceedings in Informatics (LIPIcs)
- editor
- Shaw, Paul
- volume
- 307
- article number
- 4
- pages
- 28 pages
- publisher
- Schloss Dagstuhl - Leibniz-Zentrum für Informatik
- conference name
- 30th International Conference on Principles and Practice of Constraint Programming, CP 2024
- conference location
- Girona, Spain
- conference dates
- 2024-09-02 - 2024-09-06
- external identifiers
-
- scopus:85203681562
- ISSN
- 1868-8969
- ISBN
- 978-3-95977-336-2
- DOI
- 10.4230/LIPIcs.CP.2024.4
- language
- English
- LU publication?
- yes
- id
- 1db54cf4-755f-48c1-bc46-4086acc5891e
- date added to LUP
- 2024-09-09 10:45:25
- date last changed
- 2025-04-04 14:15:45
@inproceedings{1db54cf4-755f-48c1-bc46-4086acc5891e, abstract = {{Proof logging has long been the established method to certify correctness of Boolean satisfiability (SAT) solvers, but has only recently been introduced for SAT-based optimization (MaxSAT). The focus of this paper is solution-improving search (SIS), in which a SAT solver is iteratively queried for increasingly better solutions until an optimal one is found. A challenging aspect of modern SIS solvers is that they make use of complex "without loss of generality" arguments that are quite involved to understand even at a human meta-level, let alone to express in a simple, machine-verifiable proof. In this work, we develop pseudo-Boolean proof logging methods for solution-improving MaxSAT solving, and use them to produce a certifying version of the state-of-the-art solver Pacose with VeriPB proofs. Our experimental evaluation demonstrates that this approach works in practice. We hope that this is yet another step towards general adoption of proof logging in MaxSAT solving.}}, author = {{Berg, Jeremias and Bogaerts, Bart and Nordström, Jakob and Oertel, Andy and Paxian, Tobias and Vandesande, Dieter}}, booktitle = {{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)}}, editor = {{Shaw, Paul}}, isbn = {{978-3-95977-336-2}}, issn = {{1868-8969}}, language = {{eng}}, month = {{08}}, publisher = {{Schloss Dagstuhl - Leibniz-Zentrum für Informatik}}, series = {{Leibniz International Proceedings in Informatics (LIPIcs)}}, title = {{Certifying Without Loss of Generality Reasoning in Solution-Improving Maximum Satisfiability}}, url = {{http://dx.doi.org/10.4230/LIPIcs.CP.2024.4}}, doi = {{10.4230/LIPIcs.CP.2024.4}}, volume = {{307}}, year = {{2024}}, }