论文标题
树木中加权多型的参数化复杂性
Parameterized Complexity of Weighted Multicut in Trees
论文作者
论文摘要
边缘多次问题是一个经典的削减问题,在给定一个无向图$ g $的情况下,一组顶点$ \ mathcal {p} $和一个预算$ k $,目的是确定最多$ k $的$ k $ edges,每个$ k $ edge co y not $ k $ n \ inth $ not \ n $ t $ t $ t $ t $ t $ t $ t $, Edge Multiput已被相对较最近被证明是固定参数(FPT),由Marx和Razgon [Sicomp 2014],由Bousquet等人独立。 [Sicomp 2018]。在此问题的加权版本中,称为加权边缘多速度,还可以给出一个权重函数$ \ mathtt {wt}:e(g)\ to \ to \ mathbb {n} $和一个重量$ w $,目标是确定最多$ k $的解决方案和最多$ w $的最大解决方案。 Marx等人的Edge Multiput的FPT算法。和Bousquet等。无法推广到加权设置。实际上,即使在树木上,加权问题也不平淡,并确定Bousquet等人明确提出了树木上的加权边缘多形的fpt。 [Stacs 2009]。在本文中,我们通过设计一种使用Kim等人最新结果的算法来积极回答这个问题。 [STOC 2022]关于定向流量增强为子例程。 我们还研究了该问题的一种变体,在该问题上没有解决方案的大小,但是参数是输入的结构性特性,例如,树的叶子数量。我们通过说明更通用的顶点删除版本来加强结果。
The Edge Multicut problem is a classical cut problem where given an undirected graph $G$, a set of pairs of vertices $\mathcal{P}$, and a budget $k$, the goal is to determine if there is a set $S$ of at most $k$ edges such that for each $(s,t) \in \mathcal{P}$, $G-S$ has no path from $s$ to $t$. Edge Multicut has been relatively recently shown to be fixed-parameter tractable (FPT), parameterized by $k$, by Marx and Razgon [SICOMP 2014], and independently by Bousquet et al. [SICOMP 2018]. In the weighted version of the problem, called Weighted Edge Multicut one is additionally given a weight function $\mathtt{wt} : E(G) \to \mathbb{N}$ and a weight bound $w$, and the goal is to determine if there is a solution of size at most $k$ and weight at most $w$. Both the FPT algorithms for Edge Multicut by Marx et al. and Bousquet et al. fail to generalize to the weighted setting. In fact, the weighted problem is non-trivial even on trees and determining whether Weighted Edge Multicut on trees is FPT was explicitly posed as an open problem by Bousquet et al. [STACS 2009]. In this article, we answer this question positively by designing an algorithm which uses a very recent result by Kim et al. [STOC 2022] about directed flow augmentation as subroutine. We also study a variant of this problem where there is no bound on the size of the solution, but the parameter is a structural property of the input, for example, the number of leaves of the tree. We strengthen our results by stating them for the more general vertex deletion version.