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Using heuristics to find minimal unsatisfiable subformulas in satisfiability problems

机译:使用启发式方法在可满足性问题中找到最小的不满足子公式

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摘要

In this paper, we propose efficient algorithms to extract minimal unsatisfiable subsets of clauses or variables in unsatisfiable propositional formulas. Such subsets yield unsatisfiable propositional subformulas that become satisfiable when any of their clauses or variables is removed. These subformulas have numerous applications, including proving unsatisfiability and post-infeasibility analysis. The algorithms we propose are based on heuristics, and thus, can be applied to large instances. Furthermore, we show that, in some cases, the minimality of the subformulas can be proven with these algorithms. We also present an original algorithm to find minimum cardinality unsatisfiable subformulas in smaller instances. Finally, we report computational experiments on unsatisfiable instances from various sources, that demonstrate the effectiveness of our algorithms.
机译:在本文中,我们提出了有效的算法来提取不满意命题公式中从句或变量的最小不满意子集。这样的子集会产生无法满足的命题子公式,这些子公式在删除其子句或变量中的任何子句时都变得可以满足。这些子公式具有许多应用,包括证明不满意和不可行后分析。我们提出的算法基于启发式算法,因此可以应用于大型实例。此外,我们表明,在某些情况下,这些算法可以证明子公式的最小性。我们还提出了一种原始算法,可以在较小的实例中找到最小基数不满足的子公式。最后,我们报告了来自各种来源的无法满足的实例的计算实验,证明了我们算法的有效性。

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