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arXiv 1307.6948cs.CCcond-mat.dis-nn
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反馈顶点集问题的自旋玻璃方法

Spin glass approach to the feedback vertex set problem

Hai-Jun Zhou

摘要:

无向图的反馈顶点集(FVS)是指包含图的每个圈的至少一个顶点的顶点集。反馈顶点集问题包括构造一个小于给定值的FVS。这个组合优化问题有许多实际应用,但它是在最坏情况下的计算复杂性的不确定多项式完全类。在本文中,我们定义了一个自旋玻璃模型的FVS问题,然后研究这个模型上的有限连通随机图系综。在我们的模型中,全局循环约束通过图的所有边上的局部约束来表示,然后通过分布式消息传递过程(如置信传播)来处理它们。我们的信念传播引导的抽取算法可以构造几乎最优的反馈顶点集的单个随机图实例和规则格。我们还设计了一个有向图上的FVS问题的自旋玻璃模型。我们的工作将是非常有用的一组顶点,有助于最显着的动态复杂性的一个大型网络系统。

英文摘要:

A feedback vertex set (FVS) of an undirected graph is a set of vertices that contains at least one vertex of each cycle of the graph. The feedback vertex set problem consists of constructing a FVS of size less than a certain given value. This combinatorial optimization problem has many practical applications, but it is in the nondeterministic polynomial-complete class of worst-case computational complexity. In this paper we define a spin glass model for the FVS problem and then study this model on the ensemble of finite-connectivity random graphs. In our model the global cycle constraints are represented through the local constraints on all the edges of the graph, and they are then treated by distributed message-passing procedures such as belief propagation. Our belief propagation-guided decimation algorithm can construct nearly optimal feedback vertex sets for single random graph instances and regular lattices. We also design a spin glass model for the FVS problem on a directed graph. Our work will be very useful for identifying the set of vertices that contribute most significantly to the dynamical complexity of a large networked system.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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