CNF formula simplification using implication reasoning

Rajat Arora, M. Hsiao
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引用次数: 4

Abstract

We propose a novel preprocessing technique that helps to significantly simplify a CNF instance, such that the resulting formula is easier for any SAT-solver to solve. The core of this simplification centers on a suite of lemmas and theorems derived from nontrivial Boolean reasoning. These theorems help us to deduce powerful unary and binary clauses which aid in the identification of necessary assignments, equivalent signals, complementary signals and other implication relationships among the CNF variables. The nontrivial clauses, when added to the original CNF database, subsequently simplify the CNF formula. We illustrate through experimental results that the CNF formula simplification obtained using our tool outperforms the simplification obtained using the recent preprocessors namely Hypre [F. Bacchus et al., (2003)] and NIVER [S. Subbarayan et al. (2004)]. Also, considerable savings in computation time are obtained when the simplified CNF formula is given to the SAT-solver for processing.
使用蕴涵推理简化CNF公式
我们提出了一种新的预处理技术,有助于显着简化CNF实例,从而使生成的公式对任何sat求解器来说都更容易求解。这种简化的核心集中在一组从非平凡布尔推理中导出的引理和定理上。这些定理帮助我们推导出强大的一元和二元子句,这些子句有助于识别CNF变量之间的必要赋值、等效信号、互补信号和其他隐含关系。当将非平凡子句添加到原始CNF数据库中时,随后简化了CNF公式。通过实验结果表明,使用我们的工具获得的CNF公式简化优于使用最新的预处理器Hypre [F]获得的简化。Bacchus等,(2003)];Subbarayan et al.(2004)。同时,将简化后的CNF公式交给sat求解器进行处理,大大节省了计算时间。
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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