Boolean satisfiability (SAT) solvers are at the core of efficient approaches for solving a vast
multitude of practical problems. Moreover, albeit targeting an NP-complete problem, SAT …

Recent work proposed a toolkit PySAT aiming at fast and easy prototyping with propositional
satisfiability (SAT) oracles in Python, which enabled one to exploit the power of the original …

Maximum satisfiability (MaxSAT) is an optimization version of SAT that is solved by finding
an optimal truth assignment instead of just a satisfying one. In MaxSAT the objective function …

Branch and Bound (BnB) is a powerful technique that has been successfully used to solve
many combinatorial optimization problems. However, MaxSAT is a notorious exception …

The development of practical approaches to efficiently reasoning over pseudo-Boolean
constraints has recently increasing attention as a natural generalization of Boolean …

Abstract The Maximum Satisfiability Problem, or MaxSAT, offers a suitable problem solving
formalism for combinatorial optimization problems. Nevertheless, MaxSAT solvers …

Recent developments in applying and extending Boolean satisfiability (SAT) based
techniques have resulted in new types of approaches to pseudo-Boolean optimization …

Boolean satisfiability (SAT) solvers allow for incremental computations, which is key to
efficient employment of SAT solvers iteratively for developing complex decision and …

The proof system of Dual-Rail MaxSAT (DRMaxSAT) was recently shown to be capable of
efficiently refuting families of formulas that are well-known to be hard for resolution …

MaxHS is a MaxSat solver originally developed in [6]. It was the first MaxSat solver to utilize
the Implicit Hitting Set (IHS) approach, and its core components are described in [6],[4],[5],[7] …