Treedepth decomposition has several practical applications and can be used to speed up many parameterized algorithms. There are several works aiming to design a scalable algorithm to compute exact treedepth decompositions. Those include works based on a set of all minimal separators. In those algorithms, although a number of minimal separators are enumerated, the minimal separators that are used for an optimal solution are empirically very small. Therefore, analyzing the upper bound on the size of minimal separators is an important problem because it has the potential to significantly reduce the computation time. A minimal separator $S$ is called an optimal top separator if $td(G) = |S| + td(G \backslash S)$, where $td(G)$ denotes the treedepth of $G$. Then, we have two theoretical results on the size of optimal top separators. (1) For any $G$, there is an optimal top separator $S$ such that $|S| \le 2tw(G)$, where $tw(G)$ is the treewidth of $G$. (2) For any $c < 2$, there exists a graph $G$ such that any optimal top separator $S$ of $G$ have $|S| > c \cdot tw(G)$, i.e., the first result gives a tight bound on the size of an optimal top separator.
翻译:树深度分解有几个实用的应用程序, 可以用来加速许多参数化算法。 有好几项工作旨在设计一个可缩放的算法, 以计算精确的树深度分解。 其中包括基于所有最小分隔器的一组工程。 在这些算法中, 尽管列出了一些最小的分隔器, 但用于优化解决方案的最小分隔器在经验上是很小的。 因此, 分析最小分隔器大小的上层界限是一个重要问题, 因为它有可能大大缩短计算时间。 如果 $( G) = + + td( G\ backsash S)$, 最小分隔器的值是最小分隔器的底部分隔器。 因此, 我们对于最优化的顶层分隔器的大小有两种理论结果。 (1) 对于任何G美元, 最理想的顶层分隔器$S$, 如果 $( g) = ++++ t$, 美元, 最高值是任何顶层G$。