Recent work proposed a toolkit PySAT aiming at fast and easy prototyping with propo-sitional satisfiability (SAT) oracles in Python, which enabled one to exploit the power of the original implementations of the state-of-the-art SAT solvers in Python. Maximum sat-isfiability (MaxSAT) is a well-known optimization version of SAT, which can be solved with a series of calls to a SAT oracle. Based on this fact and motivated by the ideas underlying the PySAT toolkit, this paper describes and evaluates RC2 (stands for relaxable cardinality constraints), a new core-guided MaxSAT solver written in Python, which won both unweighted and weighted categories of the main track of MaxSAT Evaluation 2018.
CITATION STYLE
Ignatiev, A., Morgado, A., & Marques-Silva, J. (2019). RC2: an Efficient MaxSAT Solver. Journal on Satisfiability, Boolean Modeling and Computation, 11(1), 53–64. https://doi.org/10.3233/sat190116
Mendeley helps you to discover research relevant for your work.