On Partitioning for Maximum Satisfiability

Partitioning formulas is motivated by the expectation to identify easy to solve subformulas, even though at the cost of having more formulas to solve. In this paper we suggest to apply partitioning to Maximum Satisfiability (MaxSAT), the optimization version of the well-known Satisfiability (SAT) problem. The use of partitions can be naturally combined with unsatisfiability-based algorithms for MaxSAT that are built upon successive calls to a SAT solver, where each call identifies an unsatisfiable subformula. One of the drawbacks of these algorithms results from the SAT solver returning large unsatisfiable subformulas. However, when using partitions, the solver is more likely to identify smaller unsatisfiable subformulas. Experimental results show that the use of partitions in MaxSAT significantly improves the performance of unsatisfiability-based algorithms.

Authors

• Ruben Martins
• Vasco Manquinho
• Inês Lynce

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