A deterministic (2−2/(k+1))n algorithm for k-SAT based on local search

A deterministic (2-2/(k+1))n algorithm for k-SAT based on local search

Deterministic Algorithms for k-SAT Based on Covering Codes and Local Search

We show that satisfiability of formulas in k-CNF can be decided deterministically in time close to (2k/(k + 1)), where n is the number of variables in the input formula. This is the best known worstcase upper bound for deterministic k-SAT algorithms. Our algorithm can be viewed as a derandomized version of Schöning’s probabilistic algorithm presented in [15]. The key point of our algorithm is t...

A local search algorithm for SAT

We present a fairly simple and natural algorithm for SAT which can be viewed as a particular instantiation of the well known k opt heuristic We prove that for most formulas drawn from certain random and semi random distributions on satis able formulas the algorithm nds a satisfying assignment in polynomial time

Guided Search and a Faster Deterministic Algorithm for 3-SAT

Most deterministic algorithms for NP-hard problems are splitting algorithms: They split a problem instance into several smaller ones, which they solve recursively. Often, the algorithm has a choice between several splittings. For 3-SAT, we show that choosing wisely which splitting to apply, one can avoid encountering too many worst-case instances. This improves the currently best known determin...

A novel local search based on variable-focusing for random K-SAT

We introduce a new local search algorithm for satisfiability problems. Usual approaches focus uniformly on unsatisfied clauses. The new method works by picking uniformly random variables in unsatisfied clauses. A Variable-based Focused Metropolis Search (V-FMS) is then applied to random 3-SAT. We show that it is quite comparable in performance to the clause-based FMS. Consequences for algorithm...