Solving SAT with mixed parallel execution

The satisfiability problem (SAT) is a famous NP-complete problem, which in general requires a lot of time to solve as the problem size becomes large. We have proposed a neural network called LPPH for the SAT, together with a parallel execution of LPPHs. In this paper, we propose a mixed parallel execution of LPPHs and local search algorithms. Results of experiments show that the mixed parallel execution is more efficient than the non-mixed parallel execution of LPPHs or GSATs in many problems.