An Efficient Implementation for WalkSAT

Parallel WalkSAT with Clause Learning

We present an extension of WalkSAT, a stochastic local search algorithm for solving SAT problems. Our extension learns new clauses by resolving existing clauses based on the current state of a WalkSAT run. We show that clause learning leads to significant speedup in WalkSAT runs, both in terms of fewer steps and faster runtime. We argue that our WalkSAT implementation is easily parallelizable, ...

Auto-Walksat: A Self-Tuning Implementation of Walksat

QingTing: A Local Search SAT Solver Using an Effective Switching Strategy and an Efficient Unit Propagation

Advances in local-search SAT solvers have traditionally been presented in the context of local search solvers only. The most recent and rather comprehensive comparisons between UnitWalk and several versions of WalkSAT demonstrate that neither solver dominates on all benchmarks. QingTing2 (a ‘dragonfly’ in Mandarin) is a SAT solver script that relies on a novel switching strategy to invoke one o...

A Local Search SAT Solver Using an Effective Switching Strategy and an Efficient Unit Propagation

Advances in local-search SAT solvers have traditionally been presented in the context of local search solvers only. The most recent and rather comprehensive comparisons between UnitWalk and several versions of WalkSAT demonstrate that neither solver dominates on all benchmarks. QingTing2 (a ‘dragonfly’ in Mandarin) is a SAT solver script that relies on a novel switching strategy to invoke one o...

UBCSAT: An Implementation and Experimentation Environment for SLS Algorithms for SAT & MAX-SAT

In this paper we introduce UBCSAT, a new implementation and experimentation environment for Stochastic Local Search (SLS) algorithms for SAT and MAX-SAT. Based on a novel triggered procedure architecture, UBCSAT provides implementations of numerous well-known and widely used SLS algorithms for SAT and MAX-SAT, including GSAT, WalkSAT, and SAPS; these implementations generally match or exceed th...