论文标题
列举最大感应子图
Enumerating Maximal Induced Subgraphs
论文作者
论文摘要
给定图形$ g $,最大诱导子图问题要求列举属于某个遗传图类的所有最大诱导子图。虽然其优化版本(在文献中被称为最小顶点缺失问题)进行了深入研究,但枚举算法以一些简单的图形类别(例如独立集合,集团和森林)而闻名,直到最近[Conte and uno,Stoc,Stoc 2019]]。此问题也有连接的变化,其中仅关注那些连接的诱导子图。我们介绍了两种新方法,使我们能够开发算法,以解决许多重要的图形类别的两种变化。被证明在枚举算法中非常强大的一般技术是在问题的所有解决方案上构建解决方案图,即,在所有解决方案上进行多个挖掘图,而这种方法的关键是使解决方案图紧密连接,以便简单的解决方案映射可以解决问题。我们将无报复路径介绍给我们构建的解决方案图的牢固连接性。概括了Cohen,Kimelfeld和Sagiv [JCSS 2008]的概念,我们介绍了$ t $限制的版本,$ t $是一个正整数,是最大(连接的)诱导子分类问题,并表明它等同于原始问题,即在递增的多种元素时间上的可溶性。此外,我们给出了这两种变体之间的减少,因此可以解决我们研究的每个类别的变化之一。我们的工作还导致了几个重要的已知结果的直接和简单证明。
Given a graph $G$, the maximal induced subgraphs problem asks to enumerate all maximal induced subgraphs of $G$ that belong to a certain hereditary graph class. While its optimization version, known as the minimum vertex deletion problem in literature, has been intensively studied, enumeration algorithms are known for a few simple graph classes, e.g., independent sets, cliques, and forests, until very recently [Conte and Uno, STOC 2019]. There is also a connected variation of this problem, where one is concerned with only those induced subgraphs that are connected. We introduce two new approaches, which enable us to develop algorithms that solve both variations for a number of important graph classes. A general technique that has been proved very powerful in enumeration algorithms is to build a solution map, i.e., a multiple digraph on all the solutions of the problem, and the key of this approach is to make the solution map strongly connected, so that a simple traversal of the solution map solves the problem. We introduce retaliation-free paths to certificate strong connectedness of the solution map we build. Generalizing the idea of Cohen, Kimelfeld, and Sagiv [JCSS 2008], we introduce the $t$-restricted version, $t$ being a positive integer, of the maximal (connected) induced subgraphs problem, and show that it is equivalent to the original problem in terms of solvability in incremental polynomial time. Moreover, we give reductions between the two variations, so that it suffices to solve one of the variations for each class we study. Our work also leads to direct and simpler proofs of several important known results.