Certifying Pareto-Optimality in Multi-Objective Maximum Satisfiability
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Abstract (arXiv)
Due to the wide employment of automated reasoning in the analysis and construction of correct systems, the results reported by automated reasoning engines must be trustworthy. For Boolean satisfiability (SAT) solvers - and more recently SAT-based maximum satisfiability (MaxSAT) solvers - trustworthiness is obtained by integrating proof logging into solvers, making solvers capable of emitting machine-verifiable proofs to certify correctness of the reasoning steps performed. In this work, we enable for the first time proof logging based on the VeriPB proof format for multi-objective MaxSAT (MO-MaxSAT) optimization techniques. Although VeriPB does not offer direct support for multi-objective problems, we detail how preorders in VeriPB can be used to provide certificates for MO-MaxSAT algorithms computing a representative solution for each element in the non-dominated set of the search space under Pareto-optimality, without extending the VeriPB format or the proof checker. By implementing VeriPB proof logging into a state-of-the-art multi-objective MaxSAT solver, we show empirically that proof logging can be made scalable for MO-MaxSAT with reasonable overhead.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 11 of its 49 references that are in the map. First posted on arXiv 29 Jan 2025.
Builds on
11 of 49 references.
References · 11
- 2018MLIC: A MaxSAT-Based framework for learning interpretable classification rulescited by 14
- 2022Certifying Parity Reasoning Efficiently Using Pseudo-Boolean Proofscited by 14
- 2016Efficient Certified RAT Verificationcited by 13
- 2022Certified Symmetry and Dominance Breaking for Combinatorial Optimisationcited by 13
- 2014Incremental Cardinality Constraints for MaxSATcited by 6
- 2015Generalized Totalizer Encoding for Pseudo-Boolean Constraintscited by 6
- 2016Efficient Certified Resolution Proof Checkingcited by 5
- 2024Certified MaxSAT Preprocessingcited by 3
- 2024Certifying MIP-based Presolve Reductions for 0-1 Integer Linear Programscited by 2
- 2022New Core-Guided and Hitting Set Algorithms for Multi-Objective Combinatorial Optimizationcited by 1
- 2024Certificates and Witnesses for Multi-Objective Queries in Markov Decision Processescited by 1
Built on by
Citing papers per year: 2025: 1; 2026: 1.
2 papers.
- 2026Towards a Certifying Grounder23 Jul 2026
- 2025Efficient and Reliable Hitting-Set Computations for the Implicit Hitting Set Approach9 Aug 2025
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