A Dynamic Phase Selection Strategy for Satisfiability Solvers

TL;DR

This paper introduces a low-cost dynamic phase selection strategy for SAT solvers that improves their performance by dynamically computing literal weights during search.

Contribution

It proposes a novel dynamic phase selection method based on implied-literals, enhancing existing solvers like Glucose 2.0 and Lingeling with significant performance gains.

Findings

Glucose with dynamic phase selection outperforms the original Glucose on SAT 2011 instances.

Lingeling with the new policy performs better than its original version.

The proposed method maintains low computational overhead due to compatibility with watched-literals scheme.

Abstract

The phase selection is an important of a SAT Solver based on conflict-driven DPLL. This paper presents a new phase selection strategy, in which the weight of each literal is defined as the sum of its implied-literals static weights. The implied literals of each literal is computed dynamically during the search. Therefore, it is call a dynamic phase selection strategy. In general, computing dynamically a weight is time-consuming. Hence, so far no SAT solver applies successfully a dynamic phase selection. Since the implied literal of our strategy conforms to that of the search process, the usual two watched-literals scheme can be applied here. Thus, the cost of our dynamic phase selection is very low. To improve Glucose 2.0 which won a Gold Medal for application category at SAT 2011 competition, we build five phase selection schemes using the dynamic phase selection policy. On application instances of SAT 2011, Glucose improved by the dynamic phase selection is significantly better than the original Glucose. We conduct also experiments on Lingeling, using the dynamic phase selection policy, and build two phase selection schemes. Experimental results show that the improved Lingeling is better than the original Lingeling.