利用超图划分高效布尔可满足性

V. Durairaj, P. Kalla
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引用次数: 12

摘要

提出了基于超图划分的约束分解方法来指导布尔可满足性搜索。在超图上对变量约束关系进行建模,并采用基于划分的技术对约束进行分解。然后对分解进行分析,有效地解决了CNF-SAT问题。本研究的贡献有两个方面:1)设计了一种使用超图划分的约束分解技术;2)设计基于该分解的约束解析方法。初步实验表明,我们的方法是快速的,可扩展的,并且可以显着提高SAT引擎的性能(通常是数量级)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploiting hypergraph partitioning for efficient Boolean satisfiability
This paper presents hypergraph partitioning based constraint decomposition procedures to guide Boolean satisfiability search. Variable-constraint relationships are modeled on a hypergraph and partitioning based techniques are employed to decompose the constraints. Subsequently, the decomposition is analyzed to solve the CNF-SAT problem efficiently. The contributions of this research are two-fold: 1) to engineer a constraint decomposition technique using hypergraph partitioning; 2) to engineer a constraint resolution method based on this decomposition. Preliminary experiments show that our approach is fast, scalable and can significantly increase the performance (often orders of magnitude) of the SAT engine.
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