Recent advances in quantum computers are demonstrating the ability to solve problems at a
scale beyond brute force classical simulation. As such, a widespread interest in quantum …

In the last couple of decades, developments in SAT-based optimization have led to highly
efficient maximum satisfiability (MaxSAT) solvers, but in contrast to the SAT solvers on which …

The dramatic improvements in Boolean satisfiability (SAT) solving since the turn of the
millennium have made it possible to leverage state-of-the-art conflict-driven clause learning …

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

Abstract Pseudo-Boolean Optimization (PBO) can be used to model many combinatorial
optimization problems. PBO instances encoded from real-world applications are often large …

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

Maximum satisfiability (MaxSAT), employing propositional logic as the declarative language
of choice, has turned into a viable approach to solving NP-hard optimization problems …

An early approach to solve the SAT problem was to convert the disjunctions directly to
equations which create an integer programming problem with 0-1 solutions. We have …

Boolean MaxSAT, as well as generalized formulations such as Min-MaxSAT and Max-hybrid-
SAT, are fundamental optimization problems in Boolean reasoning. Existing methods for …

Model counting, a fundamental task in computer science, involves determining the number
of satisfying assignments to a Boolean formula, typically represented in conjunctive normal …