Optimization Algorithms for the Satisfiability (SAT) Problem

The satisfiability problem (SAT) is a fundamental problem in mathematical logic and computing theory. Methods to solve the satisfiability problem play an important role in the development of computing theory and systems. Traditional methods treat the SAT problem as a discrete, constrained decision problem. In this chapter, we show how to translate the SAT problem into an unconstrained optimization problem and use efficient local search and global optimization methods to solve the transformed optimization problem. This approach gives significant performance improvements for certain classes of conjunctive normal form (CNF) formulas. It offers a complementary approach to the existing SAT algorithms.1

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