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引用次数: 918
摘要
我们研究了随机布尔表达式的可满足性(K-satisfiability),这些表达式由许多分句构建而成,每个分句有 K 个变量。子句与变量的比率 α 小于阈值 αc 的表达式几乎总是可满足的,而比率高于这个阈值的表达式几乎总是不可满足的。我们证明了存在一个低于 αc 的中间阶段,在这个阶段,可迁移状态的扩散是搜索算法复杂性开始的原因。我们介绍了一类可以处理这些可变状态的优化算法;其中一种算法已在现有最大的 K 可满足性基准上成功地进行了测试。
Analytic and Algorithmic Solution of Random Satisfiability Problems
We study the satisfiability of random Boolean expressions built from many clauses with K variables per clause (K-satisfiability). Expressions with a ratio α of clauses to variables less than a threshold αc are almost always satisfiable, whereas those with a ratio above this threshold are almost always unsatisfiable. We show the existence of an intermediate phase below αc, where the proliferation of metastable states is responsible for the onset of complexity in search algorithms. We introduce a class of optimization algorithms that can deal with these metastable states; one such algorithm has been tested successfully on the largest existing benchmark of K-satisfiability.
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