arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1403.4010cs.CC
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顶点覆盖解的组织机制与计数算法

Organization mechanism and counting algorithm on Vertex-Cover solutions

Wei Wei, Renquan Zhang, Baolong Niu, Binghui Guo, Zhiming Zheng

摘要:

计算组合优化问题的解数是计算复杂性研究中的一个重要课题,特别是在P-完全复杂性类上。本文首先利用未冻结顶点的连通度和连通分支研究了顶点覆盖未冻结子图的一些组织形式。在此基础上,提出了一种点覆盖解计数算法,并给出了算法的复杂度分析,其结果与模拟结果吻合良好,且在c = e邻域内比1-RSB算法有更好的性能。在此基础上,研究了解数统计量的变化和波动,揭示了解数的演化机理。此外,还研究了随机图和无标度图解空间的边缘概率分布,以说明它们解空间的不同演化特征。因此,基于解空间的图表示进行解的计数是研究NP完全问题和#P完全问题的困难性的一种有意义的方法,适当的算法设计可以使组合优化问题和相应的计数问题得到更好的近似解。

英文摘要:

Counting the solution number of combinational optimization problems is an important topic in the study of computational complexity, especially on the #P-complete complexity class. In this paper, we first investigate some organizations of Vertex-Cover unfrozen subgraphs by the underlying connectivity and connected components of unfrozen vertices. Then, a Vertex-Cover Solution Number Counting Algorithm is proposed and its complexity analysis is provided, the results of which fit very well with the simulations and have better performance than those by 1-RSB in a neighborhood of c = e for random graphs. Base on the algorithm, variation and fluctuation on the solution number statistics are studied to reveal the evolution mechanism of the solution numbers. Besides, marginal probability distributions on the solution space are investigated on both random graph and scale-free graph to illustrate different evolution characteristics of their solution spaces. Thus, doing solution number counting based on graph expression of solution space should be an alternative and meaningful way to study the hardness of NP-complete and #P-complete problems, and appropriate algorithm design can help to achieve better approximations of solving combinational optimization problems and the corresponding counting problems.

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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