Analysis of comparative effectiveness of state-of-the-art heuristics for CDCL SAT solvers

S. Kochemazov
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Abstract

The Conflict-Driven Clause Learning algorithms for solving the Boolean satisfiability problem comprise the major part of the methods used to solve various instances of the problems that arise in industry and science. In recent years there have been proposed several major heuristics for these algorithms which are assumed to be de facto good for the solvers’ performance over diverse sets of benchmarks. The goal of this paper is to evaluate the contribution of each separate heuristic to the performance of a state-of-the-art solver, see the extent to which they are beneficial, and figure out if the heuristics have any particular features that need to be taken into account.
最先进的启发式CDCL SAT求解器的比较有效性分析
用于解决布尔可满足性问题的冲突驱动子句学习算法构成了用于解决工业和科学中出现的各种问题实例的主要部分。近年来,人们提出了几种主要的启发式算法,这些算法被认为实际上对求解器在不同基准集上的性能很好。本文的目标是评估每个单独的启发式对最先进的求解器性能的贡献,看看它们的有益程度,并找出启发式是否有任何需要考虑的特定特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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