One of the most important paradigm shifts in the use of SAT solvers for solving industrial
problems has been the introduction of clause learning. Clause learning entails adding a …

MaxSAT solving is becoming a competitive generic approach for solving combinatorial
optimization problems, partly due to the development of new solving techniques that have …

This chapter gives an overview of proof complexity and connections to SAT solving, focusing
on proof systems such as resolution, Nullstellensatz, polynomial calculus, and cutting planes …

In recent years there has been an increasing interest in studying proof systems stronger than
Resolution, with the aim of building more efficient SAT solvers based on them. In defining …

Abstract Satisfaction-Driven Clause Learning (SDCL) is a recent SAT solving paradigm that
aggressively trims the search space of possible truth assignments. To determine if the SAT …

Abstract The series of MaxSAT Evaluations, organized yearly since 2006, has been the main
forum for evaluating the state of the art in solvers for the Boolean optimization paradigm of …

We study the MaxSAT Resolution (MaxRes) rule in the context of certifying unsatisfiability.
We show that it can be exponentially more powerful than tree-like resolution, and when …

Proof systems for SAT are unsound for MaxSAT because they preserve satisfiability but fail
to preserve the minimum number of unsatisfied clauses. Consequently, there has been a …

The refutation power of SAT and MaxSAT resolution is challenged by problems like the soft
and hard Pigeon Hole Problem PHP for which short refutations do not exist. In this paper we …

The paper describes the use of dual-rail MaxSAT systems to solve Boolean satisfiability
(SAT), namely to determine if a set of clauses is satisfiable. The MaxSAT problem is the …