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On the Approximability of Splitting-SAT in 2-CNF Horn Formulas

机译:2-CNF Horn公式中Split-SAT的逼近性

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Splitting a variable in a Boolean formula means to replace an arbitrary set of its occurrences by a new variable. In the minimum splitting SAT problem, we ask for a minimum-size set of variables to be split in order to make the formula satisfiable. This problem is known to be APX-hard, even for 2-CNF formulas. We consider the case of 2-CNF Horn formulas, i. e., 2-CNF formulas without positive 2-clauses, and prove that this problem is APX-hard as well. We also analyze subcases of 2-CNF Horn formulas, where additional clause types are forbidden. While excluding negative 2-clauses admits a polynomial-time algorithm based on network flows, the splitting problem stays APX-hard for formulas consisting of positive 1-clauses and negative 2-clauses only. Instead of splitting as many variables as possible to make a formula satisfiable, one can also look at the dual problem of finding the maximum number of variables that can be assigned without violating a clause. We also study the approximability of this maximum assignment problem on 2-CNF Horn formulas. While the polynomially solvable subproblems are the same as for the splitting problem, the maximum assignment problem in general Horn formulas is as hard to approximate as the maximum independent set problem.
机译:在布尔公式中拆分变量意味着用新变量替换任意出现的变量集。在最小拆分SAT问题中,我们要求对最小大小的变量集进行拆分,以使公式可满足要求。即使对于2-CNF公式,此问题也是已知的APX难题。我们考虑2-CNF Horn公式的情况,即。例如,没有正2个从句的2-CNF公式,并证明此问题对APX也是很困难的。我们还分析了2-CNF Horn公式的子案例,其中禁止使用其他子句类型。尽管排除负的2个子句允许基于网络流的多项式时间算法,但对于仅由正的1个子句和负的2个子句组成的公式,拆分问题仍然难以解决。除了分配尽可能多的变量以使公式可满足之外,还可以着眼于双重问题,即找到可以分配的最大变量数而不违反子句。我们还研究了在2-CNF Horn公式上此最大赋值问题的逼近度。虽然多项式可解子问题与分裂问题相同,但一般的Horn公式中的最大赋值问题与最大独立集问题一样难以近似。

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