A Randomized Algorithm for 3-SAT

TL;DR

This paper introduces a new randomized algorithm for 3-SAT that outperforms existing methods in certain clause density ranges by combining two algorithms to maximize success probability.

Contribution

The paper presents a novel randomized algorithm for 3-SAT that outperforms previous algorithms in specific clause density regimes by combining their strengths.

Findings

Combined algorithm outperforms PPZ when average critical clauses per variable are between 1 and 1.9317.

The new algorithm performs better in cases with fewer critical clauses.

Success probability is maximized by selecting the best of two algorithms for each instance.

Abstract

In this work we propose and analyze a simple randomized algorithm to find a satisfiable assignment for a Boolean formula in conjunctive normal form (CNF) having at most 3 literals in every clause. Given a k-CNF formula phi on n variables, and alpha in{0,1}^n that satisfies phi, a clause of phi is critical if exactly one literal of that clause is satisfied under assignment alpha. Paturi et. al. (Chicago Journal of Theoretical Computer Science 1999) proposed a simple randomized algorithm (PPZ) for k-SAT for which success probability increases with the number of critical clauses (with respect to a fixed satisfiable solution of the input formula). Here, we first describe another simple randomized algorithm DEL which performs better if the number of critical clauses are less (with respect to a fixed satisfiable solution of the input formula). Subsequently, we combine these two simple algorithms such that the success probability of the combined algorithm is maximum of the success probabilities of PPZ and DEL on every input instance. We show that when the average number of clauses per variable that appear as unique true literal in one or more critical clauses in phi is between 1 and 1.9317, combined algorithm performs better than the PPZ algorithm.