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Community-Based Partitioning for MaxSAT Solving

机译:MaxSAT解决方案的基于社区的分区

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Unsatisfiability-based algorithms for Maximum Satisfiability (MaxSAT) have been shown to be very effective in solving several classes of problem instances. These algorithms rely on successive calls to a SAT solver, where an unsatisfiable subformula is identified at each iteration. However, in some cases, the SAT solver returns unnecessarily large subformulas. In this paper a new technique is proposed to partition the MaxSAT formula in order to identify smaller unsatisfiable subformulas at each call of the SAT solver. Preliminary experimental results analyze the effect of partitioning the MaxSAT formula into communities. This technique is shown to significantly improve the unsatisfiability-based algorithm for different benchmark sets.
机译:基于不满足度的最大满意度(MaxSAT)算法在解决几类问题实例方面非常有效。这些算法依赖于对SAT解算器的连续调用,其中在每次迭代中都会识别出无法满足的子公式。但是,在某些情况下,SAT解算器会返回不必要的大子公式。在本文中,提出了一种新技术来划分MaxSAT公式,以便在每次SAT解算器调用时识别较小的无法满足的子公式。初步实验结果分析了将MaxSAT公式划分为社区的效果。事实证明,该技术可显着改善针对不同基准集的基于不满足性的算法。

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