Artificial Intelligence
Symmetry Breaking for Maximum Satisfiability
LPAR '08 Proceedings of the 15th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning
Solving (Weighted) Partial MaxSAT through Satisfiability Testing
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Exploiting Cycle Structures in Max-SAT
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Algorithms for Weighted Boolean Optimization
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Within-problem learning for efficient lower bound computation in Max-SAT solving
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
MiniMaxSAT: a new weighted Max-SAT solver
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
Towards more effective unsatisfiability-based maximum satisfiability algorithms
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
Solving MAXSAT by solving a sequence of simpler SAT instances
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
Mapping problems with finite-domain variables to problems with boolean variables
SAT'04 Proceedings of the 7th international conference on Theory and Applications of Satisfiability Testing
Boolean lexicographic optimization: algorithms & applications
Annals of Mathematics and Artificial Intelligence
On solving the partial MAX-SAT problem
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Artificial Intelligence
Exploiting the power of MIP solvers in MAXSAT
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
Community-Based partitioning for MaxSAT solving
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
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In the last few years, there has been a significant effort in designing and developing efficient Weighted MaxSAT solvers. We study in detail the WPM1 algorithm identifying some weaknesses and proposing solutions to mitigate them. Basically, WPM1 is based on iteratively calling a SAT solver and adding blocking variables and cardinality constraints to relax the unsatisfiable cores returned by the SAT solver. We firstly identify and study how to break the symmetries introduced by the blocking variables and cardinality constraints. Secondly, we study how to prioritize the discovery of higher quality cores. We present an extensive experimental investigation comparing the new algorithm with state-of-the-art solvers showing that our approach makes WPM1 much more competitive.