CNF Encodings of Cardinality Constraints Based on Comparator Networks
Micha{\l} Karpi\'nski

TL;DR
This paper introduces new methods for encoding Boolean cardinality constraints into CNF formulas to improve the efficiency of SAT solving in practical applications like scheduling and verification.
Contribution
It proposes novel encoding techniques based on comparator networks that produce smaller CNF formulas, enhancing SAT solver performance for cardinality constraints.
Findings
New encoding methods reduce CNF size
Improved SAT solver runtimes observed
Enhanced applicability to real-world problems
Abstract
Boolean Satisfiability Problem (SAT) is one of the core problems in computer science. As one of the fundamental NP-complete problems, it can be used - by known reductions - to represent instances of variety of hard decision problems. Additionally, those representations can be passed to a program for finding satisfying assignments to Boolean formulas, for example, to a program called MiniSat. Those programs (called SAT-solvers) have been intensively developed for many years and - despite their worst-case exponential time complexity - are able to solve a multitude of hard practical instances. A drawback of this approach is that clauses are neither expressive, nor compact, and using them to describe decision problems can pose a big challenge on its own. We can improve this by using high-level constraints as a bridge between a problem at hand and SAT. Such constraints are then…
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Taxonomy
TopicsFormal Methods in Verification · Complexity and Algorithms in Graphs · Constraint Satisfaction and Optimization
