A tour of MaxSAT

Maximum satisfiability (MaxSAT) is today a competitive approach to tackling NP-hard optimization problems in a variety of AI and industrial domains. A great majority of the modern state-of-the-art MaxSAT solvers are core-guided, relying on a SAT solver to iteratively extract unsatisfiable cores of the soft clauses in the working formula and ruling out the found cores via adding cardinality constraints into the working formula until a solution is found. In this work we propose weight-aware core extraction (WCE) as a refinement to the current common approach of core-guided solvers. WCE integrates knowledge of soft clause weights into the core extraction process, and allows for delaying the addition of cardinality constraints into the working formula. We show that WCE noticeably improves in practice the performance of PMRES, one of the recent core-guided MaxSAT algorithms using soft cardinality constraints, and explain how the approach can be integrated into other core-guided algorithms.

Maximum Satisfiability (MaxSat) solving is an active area of research motivated by numerous successful applications to solving NP-hard combinatorial optimization problems. One of the most successful approaches to solving MaxSat instances arising from real world applications is the Implicit Hitting Set (IHS) approach. IHS solvers are complete MaxSat solvers that harness the strengths of both Boolean Satisfiability (SAT) and Integer Linear Programming (IP) solvers by decoupling core-extraction and optimization. While such solvers show state-of-the-art performance on many instances, it is known that there exist MaxSat instances on which IHS solvers need to extract an exponential number of cores before terminating. Motivated by the structure of the simplest of these problematic instances, we propose a technique we call abstract cores that provides a compact representation for a potentially exponential number of regular cores. We demonstrate how to incorporate abstract core reasoning into the IHS algorithm and report on an empirical evaluation demonstrating that including abstract cores into a state-of-the-art IHS solver improves its performance enough to surpass the best performing solvers of the most recent 2019 MaxSat Evaluation.