Partial MaxSAT (PMS) and Weighted PMS (WPMS) are two practical generalizations of the MaxSAT problem. In this paper, we propose a local search algorithm for these problems, called BandHS, which applies two multi-armed bandits to guide the search directions when escaping local optima. One bandit is combined with all the soft clauses to help the algorithm select to satisfy appropriate soft clauses, and the other bandit with all the literals in hard clauses to help the algorithm select appropriate literals to satisfy the hard clauses. These two bandits can improve the algorithm's search ability in both feasible and infeasible solution spaces. We further propose an initialization method for (W)PMS that prioritizes both unit and binary clauses when producing the initial solutions. Extensive experiments demonstrate the excellent performance and generalization capability of our proposed methods, that greatly boost the state-of-the-art local search algorithm, SATLike3.0, and the state-of-the-art SAT-based incomplete solver, NuWLS-c.
翻译:部分 MaxSAT (PMS) 和 加权 PMS (WPMS) 是 MaxSAT 问题的两个实用概略。 在本文中, 我们提议了一种本地搜索算法, 称为 BandHS, 用于在逃离本地opima 时引导搜索方向。 一个土匪与所有软条款相结合, 以帮助算法选择满足适当的软条款, 另一个土匪与所有硬条款的字面文字结合, 以帮助算法选择合适的字面来满足硬条款。 这两个土匪可以在可行和不可行的解决方案空间提高算法的搜索能力。 我们进一步提议了( W) PMS 的初始化方法, 它将单元和二元条款放在优先位置。 广泛的实验表明我们拟议方法的出色性能和普及能力, 大大提升了最先进的本地搜索算法, SAT 3 0. 和 状态的SAT 不完整解算法, NuWLS- c 。