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On smoothed k-CNF formulas and the Walksat algorithm

机译:在平滑的K-CNF公式和Walksat算法上

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In this paper we study the model of ε-smoothed k-CNF formulas. Starting from an arbitrary instance F with n variables and m = dn clauses, apply the ε-smoothing operation of flipping the polarity of every literal in every clause independently at random with probabilityε. Keepingεand k fixed, and letting the density d = m/n grow, it is rather easy to see that for d ≥ ε~(-k) ln2, F becomes whp unsatisfiable after smoothing. We show that a lower density that behaves roughly like ε~(-k+1) suffices for this purpose. We also show that our bound on d is nearly best possible in the sense that there are k-CNF formulas F of slightly lower density that whp remain satisfiable after smoothing. One consequence of our proof is a new lower bound of Ω(2~k/k~2) on the density up to which Walksat solves random k-CNFs in polynomial time whp. We are not aware of any previous rigorous analysis showing that Walksat is successful at densities that are increasing as a function of k.
机译:在本文中,我们研究了ε-平滑的K-CNF公式模型。从具有n个变量和m = dn条款的任意实例f开始,应用随机与概率ε独立地翻转每个子句中每个文字极性的ε平滑操作。保持εand固定,让密度d = m / n生长,对于D≥ε〜(-k)Ln2,F变得Whp在平滑后变得不当,而且相当容易。我们表明,对于此目的,表现出大致相同的ε〜(-k + 1)的较低密度。我们还表明,我们对D的绑定几乎最好,有意义的是,有k-cnf公式f的k-cnf公式f略低于密度,Whp在平滑后保持满足。我们证据的一种后果是ω(2〜k / k〜2)的新下限,对多项式时间WHP中的随机k-CNFS求解随机k-cnf。我们不了解任何先前的严格分析,表明Walksat在作为k的函数上升的密度上成功。

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