Let $\Pi$ be a hereditary graph class. The problem of deletion to $\Pi$, takes as input a graph $G$ and asks for a minimum number (or a fixed integer $k$) of vertices to be deleted from $G$ so that the resulting graph belongs to $\Pi$. This is a well-studied problem in paradigms including approximation and parameterized complexity. Recently, the study of a natural extension of the problem was initiated where we are given a finite set of hereditary graph classes, and the goal is to determine whether $k$ vertices can be deleted from a given graph so that the connected components of the resulting graph belong to one of the given hereditary graph classes. The problem is shown to be FPT as long as the deletion problem to each of the given hereditary graph classes is fixed-parameter tractable, and the property of being in any of the graph classes is expressible in the counting monodic second order (CMSO) logic. While this was shown using some black box theorems, faster algorithms were shown when each of the hereditary graph classes has a finite forbidden set. In this paper, we do a deep dive on pairs of specific graph classes ($\Pi_1, \Pi_2$) in which we would like the connected components of the resulting graph to belong to, and design simpler and more efficient FPT algorithms. We design a general FPT algorithm and approximation algorithm for pairs of graph classes (possibly having infinite forbidden sets) satisfying certain conditions. These algorithms cover several pairs of popular graph classes. Our algorithm makes non-trivial use of the branching technique and as a black box, FPT algorithms for deletion to individual graph classes.
翻译:假设Π是遗传图类。删除到Π问题的输入是一个图G,要求从G中删除最少数量(或固定整数k)的顶点,以便得到的图属于Π。
这是在近似和参数化复杂性范式中进行研究的一个问题。最近,对问题的自然扩展进行了研究,其中我们得到一个有限的遗传图类集合,目标是确定是否可以从给定图形中删除k个顶点,使得处理结果的连接组件属于给定的一种遗传图类。只要每个给定的遗传图类的删除问题是固定参数可跟踪的,并且任何图类的属性都可以用计数单调二阶(CMSO)逻辑表示,该问题就被证明是FPT的。尽管使用了一些黑盒定理来证明这一点,但在每个遗传图类都有一个有限的禁止集合时,就可以展示更快的算法。在本文中,我们深入研究了一对具体图类(Π1,Π2),希望处理结果的连接组件属于这些图类,并设计了更简单,更有效的FPT算法。我们设计了一种通用的FPT算法和一种逼近算法,适用于满足某些条件的一对图类(可能具有无限的禁止集合)。这些算法涵盖了几对流行的图类。我们的算法充分利用分支技术,作为黑盒子,使用固定参数可跟踪的算法进行单个图类的删除。