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UnitWalk: A new SAT solver that uses local search guided by unit clause elimination

机译:UnitWalk:一种新的SAT求解器,使用通过单元子句消除指导的本地搜索

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In this paper we present a new randomized algorithm for SAT, i.e., the satisfiability problem for Boolean formulas in conjunctive normal form. Despite its simplicity, this algorithm performs well on many common benchmarks ranging from graph coloring problems to microprocessor verification. Our algorithm is inspired by two randomized algorithms having the best current worst-case upper bounds ([27,28] and [30,31]). We combine the main ideas of these algorithms in one algorithm. The two approaches we use are local search (which is used in many SAT algorithms, e.g., in GSAT [34] and WalkSAT [33]) and unit clause elimination (which is rarely used in local search algorithms). In this paper we do not prove any theoretical bounds. However, we present encouraging results of computational experiments comparing several implementations of our algorithm with other SAT solvers. We also prove that our algorithm is probabilistically approximately complete (PAC).
机译:在本文中,我们提出了一种新的SAT随机算法,即合取范式的布尔公式的可满足性问题。尽管它很简单,但是该算法在许多常见的基准测试中表现良好,从图形着色问题到微处理器验证,无一例外。我们的算法的灵感来自两个具有最佳当前最坏情况上限([27,28]和[30,31])的随机算法。我们将这些算法的主要思想组合在一种算法中。我们使用的两种方法是局部搜索(在许多SAT算法中使用,例如,在GSAT [34]和WalkSAT [33]中使用)和单元子句消除(在局部搜索算法中很少使用)。在本文中,我们没有证明任何理论上的界限。但是,我们提出了令人鼓舞的计算实验结果,将我们的算法的几种实现与其他SAT求解器进行了比较。我们还证明了我们的算法是概率近似完全(PAC)。

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