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Solving Sparse Instances of Max SAT via Width Reduction and Greedy Restriction

机译:通过宽度减小和贪婪约束求解最大SAT的稀疏实例

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We present a moderately exponential time and polynomial space algorithm for sparse instances of Max SAT. Our algorithms run in time of the form for instances with n variables and cn clauses. Our deterministic and randomized algorithm achieve and respectively. Previously, an exponential space deterministic algorithm with was shown by Dantsin and Wolpert [SAT 2006] and a polynomial space deterministic algorithm with was shown by Kulikov and Kutzkov [CSR [2007]]. Our algorithms have three new features. They can handle instances with (1) weights and (2) hard constraints, and also (3) they can solve counting versions of Max SAT. Our deterministic algorithm is based on the combination of two techniques, width reduction of Schuler and greedy restriction of Santhanam. Our randomized algorithm uses random restriction instead of greedy restriction.
机译:我们为Max SAT的稀疏实例提供了中等指数的时间和多项式空间算法。对于具有n个变量和cn子句的实例,我们的算法以时间的形式运行。我们的确定性算法和随机算法分别实现和。以前,Dantsin和Wolpert [SAT 2006]展示了一个指数空间确定性算法,而Kulikov和Kutzkov [CSR [2007]]则展示了一个多项式空间确定性算法。我们的算法具有三个新功能。他们可以处理具有(1)权重和(2)硬约束的实例,并且(3)他们可以求解Max SAT的计数版本。我们的确定性算法基于两种技术的结合:舒勒的宽度减小和Santhanam的贪婪约束。我们的随机算法使用随机限制而不是贪婪限制。

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