A Theoretical Analysis of Search in GSAT

Authors:
Evgeny S. Skvortsov
Affiliations:
School of Computing Science, Simon Fraser Univerity,
Venue:
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Year:
2009

Citing 6
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Abstract

This paper is devoted to a rigorous analysis of the GSAT algorithm in the typical case for the random planted 3-SAT distribution. GSAT was the first widely appreciated practical heuristic developed for SAT that was based on the local search principles. We show that for any constant *** 0 GSAT, with high probability, solves random planted 3-SAT problems of density ρ = *** ln n . This performance is substantially better than the performance of the pure Iterative Improvement algorithm that has a phase transition at $\rho = \frac{7}{6} \ln n$ and fails for problems of smaller density.