Rethinking the Soft Conflict Pseudo Boolean Constraint on MaxSAT Local Search Solvers
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Abstract (arXiv)
MaxSAT is an optimization version of the famous NP-complete Satisfiability problem (SAT). Algorithms for MaxSAT mainly include complete solvers and local search incomplete solvers. In many complete solvers, once a better solution is found, a Soft conflict Pseudo Boolean (SPB) constraint will be generated to enforce the algorithm to find better solutions. In many local search algorithms, clause weighting is a key technique for effectively guiding the search directions. In this paper, we propose to transfer the SPB constraint into the clause weighting system of the local search method, leading the algorithm to better solutions. We further propose an adaptive clause weighting strategy that breaks the tradition of using constant values to adjust clause weights. Based on the above methods, we propose a new local search algorithm called SPB-MaxSAT that provides new perspectives for clause weighting on MaxSAT local search solvers. Extensive experiments demonstrate the excellent performance of the proposed methods.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 4 of its 37 references that are in the map. First posted on arXiv 19 Jan 2024.
Builds on
4 of 37 references.
References · 4
- 2021SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimizationcited by 230
- 2018Learning Features and Abstract Actions for Computing Generalized Planscited by 35
- 2018Clause Vivification by Unit Propagation in CDCL SAT Solverscited by 6
- 2021Farsighted Probabilistic Sampling: A General Strategy for Boosting Local Search MaxSAT Solverscited by 4
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Citing papers per year: 2025: 2.
2 papers.