arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2207.04560cs.DM
收藏

图的最小支配集的多项式时间逼近

A polynomial-time approximation to a minimum dominating set in a graph

Frank Hernandez, Ernesto Parra, Jose Maria Sigarreta, Nodari Vakhania

摘要:

图$G=(V,E)$的{ \em支配集}是顶点$S\subseteq V$的子集,使得每个顶点$v\in V\setminus S$在$S$中至少有一个邻居。在连通图$G=(V,E)$中寻找具有最小基数的支配集是NP-困难的。一个多项式时间的近似算法,这个问题,这里描述,工作在两个阶段。在第一阶段,通过贪婪算法生成支配集,并且在第二阶段,净化(减少)该支配集。通过对第一阶段算法流程的分析和对第一阶段生成的支配集进行一种特殊的聚类,实现了约简。支配集的聚类自然地导致图$G$的一种特殊的生成森林,其用作第二净化阶段的基础。我们暴露了一些类型的图的算法的第一阶段已经提供了一个最佳的解决方案,并得出充分条件时,整个算法构造一个最佳的解决方案。我们给三个替代的近似比的算法的第一阶段,其中两个是表示在唯一不变的问题实例参数,我们也给一个额外的近似比的整体两阶段算法。贪婪算法的第一阶段原来是基本上相同的早期已知的国家的最先进的算法的集合覆盖和支配集问题Chvátal \cite{chvatal}和Parekh \cite{parekh}。在实践中,第二纯化阶段导致在第一阶段产生的主导集合的显著减少。这两个阶段的实际行为进行了验证,随机生成的问题实例。计算实验强调了阶段1的解决方案和阶段2的解决方案之间的差距。

英文摘要:

A {\em dominating set} of a graph $G=(V,E)$ is a subset of vertices $S\subseteq V$ such that every vertex $v\in V\setminus S$ has at least one neighbor in $S$. Finding a dominating set with the minimum cardinality in a connected graph $G=(V,E)$ is known to be NP-hard. A polynomial-time approximation algorithm for this problem, described here, works in two stages. At the first stage a dominant set is generated by a greedy algorithm, and at the second stage this dominating set is purified (reduced). The reduction is achieved by the analysis of the flowchart of the algorithm of the first stage and a special kind of clustering of the dominating set generated at the first stage. The clustering of the dominating set naturally leads to a special kind of a spanning forest of graph $G$, which serves as a basis for the second purification stage. We expose some types of graphs for which the algorithm of the first stage already delivers an optimal solution and derive sufficient conditions when the overall algorithm constructs an optimal solution. We give three alternative approximation ratios for the algorithm of the first stage, two of which are expressed in terms of solely invariant problem instance parameters, and we also give one additional approximation ratio for the overall two-stage algorithm. The greedy algorithm of the first stage turned out to be essentially the same as the earlier known state-of-the-art algorithms for the set cover and dominating set problem Chvátal \cite{chvatal} and Parekh \cite{parekh}. The second purification stage results in a significant reduction of the dominant set created at the first stage, in practice. The practical behavior of both stages was verified for randomly generated problem instances. The computational experiments emphasize the gap between a solution of Stage 1 and a solution of Stage 2.

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。

↑