78 research outputs found

    Parameterized Complexity Dichotomy for Steiner Multicut

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    The Steiner Multicut problem asks, given an undirected graph G, terminals sets T1,...,Tt ⊆\subseteq V(G) of size at most p, and an integer k, whether there is a set S of at most k edges or nodes s.t. of each set Ti at least one pair of terminals is in different connected components of G \ S. This problem generalizes several graph cut problems, in particular the Multicut problem (the case p = 2), which is fixed-parameter tractable for the parameter k [Marx and Razgon, Bousquet et al., STOC 2011]. We provide a dichotomy of the parameterized complexity of Steiner Multicut. That is, for any combination of k, t, p, and the treewidth tw(G) as constant, parameter, or unbounded, and for all versions of the problem (edge deletion and node deletion with and without deletable terminals), we prove either that the problem is fixed-parameter tractable or that the problem is hard (W[1]-hard or even (para-)NP-complete). We highlight that: - The edge deletion version of Steiner Multicut is fixed-parameter tractable for the parameter k+t on general graphs (but has no polynomial kernel, even on trees). We present two proofs: one using the randomized contractions technique of Chitnis et al, and one relying on new structural lemmas that decompose the Steiner cut into important separators and minimal s-t cuts. - In contrast, both node deletion versions of Steiner Multicut are W[1]-hard for the parameter k+t on general graphs. - All versions of Steiner Multicut are W[1]-hard for the parameter k, even when p=3 and the graph is a tree plus one node. Hence, the results of Marx and Razgon, and Bousquet et al. do not generalize to Steiner Multicut. Since we allow k, t, p, and tw(G) to be any constants, our characterization includes a dichotomy for Steiner Multicut on trees (for tw(G) = 1), and a polynomial time versus NP-hardness dichotomy (by restricting k,t,p,tw(G) to constant or unbounded).Comment: As submitted to journal. This version also adds a proof of fixed-parameter tractability for parameter k+t using the technique of randomized contraction

    Fixed-parameter tractability of multicut parameterized by the size of the cutset

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    Given an undirected graph GG, a collection {(s1,t1),...,(sk,tk)}\{(s_1,t_1),..., (s_k,t_k)\} of pairs of vertices, and an integer pp, the Edge Multicut problem ask if there is a set SS of at most pp edges such that the removal of SS disconnects every sis_i from the corresponding tit_i. Vertex Multicut is the analogous problem where SS is a set of at most pp vertices. Our main result is that both problems can be solved in time 2O(p3)...nO(1)2^{O(p^3)}... n^{O(1)}, i.e., fixed-parameter tractable parameterized by the size pp of the cutset in the solution. By contrast, it is unlikely that an algorithm with running time of the form f(p)...nO(1)f(p)... n^{O(1)} exists for the directed version of the problem, as we show it to be W[1]-hard parameterized by the size of the cutset

    On Computing the Maximum Parsimony Score of a Phylogenetic Network

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    Phylogenetic networks are used to display the relationship of different species whose evolution is not treelike, which is the case, for instance, in the presence of hybridization events or horizontal gene transfers. Tree inference methods such as Maximum Parsimony need to be modified in order to be applicable to networks. In this paper, we discuss two different definitions of Maximum Parsimony on networks, "hardwired" and "softwired", and examine the complexity of computing them given a network topology and a character. By exploiting a link with the problem Multicut, we show that computing the hardwired parsimony score for 2-state characters is polynomial-time solvable, while for characters with more states this problem becomes NP-hard but is still approximable and fixed parameter tractable in the parsimony score. On the other hand we show that, for the softwired definition, obtaining even weak approximation guarantees is already difficult for binary characters and restricted network topologies, and fixed-parameter tractable algorithms in the parsimony score are unlikely. On the positive side we show that computing the softwired parsimony score is fixed-parameter tractable in the level of the network, a natural parameter describing how tangled reticulate activity is in the network. Finally, we show that both the hardwired and softwired parsimony score can be computed efficiently using Integer Linear Programming. The software has been made freely available

    Algorithm design techniques for parameterized graph modification problems

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    Diese Arbeit beschaeftigt sich mit dem Entwurf parametrisierter Algorithmen fuer Graphmodifikationsprobleme wie Feedback Vertex Set, Multicut in Trees, Cluster Editing und Closest 3-Leaf Powers. Anbei wird die Anwendbarkeit von vier Technicken zur Entwicklung parametrisierter Algorithmen, naemlich, Datenreduktion, Suchbaum, Iterative Kompression und Dynamische Programmierung, fuer solche Graphmodifikationsprobleme untersucht

    A survey of parameterized algorithms and the complexity of edge modification

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    The survey is a comprehensive overview of the developing area of parameterized algorithms for graph modification problems. It describes state of the art in kernelization, subexponential algorithms, and parameterized complexity of graph modification. The main focus is on edge modification problems, where the task is to change some adjacencies in a graph to satisfy some required properties. To facilitate further research, we list many open problems in the area.publishedVersio

    Algorithms for Cut Problems on Trees

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    We study the {\sc multicut on trees} and the {\sc generalized multiway Cut on trees} problems. For the {\sc multicut on trees} problem, we present a parameterized algorithm that runs in time O∗(ρk)O^{*}(\rho^k), where ρ=2+1≈1.555\rho = \sqrt{\sqrt{2} + 1} \approx 1.555 is the positive root of the polynomial x4−2x2−1x^4-2x^2-1. This improves the current-best algorithm of Chen et al. that runs in time O∗(1.619k)O^{*}(1.619^k). For the {\sc generalized multiway cut on trees} problem, we show that this problem is solvable in polynomial time if the number of terminal sets is fixed; this answers an open question posed in a recent paper by Liu and Zhang. By reducing the {\sc generalized multiway cut on trees} problem to the {\sc multicut on trees} problem, our results give a parameterized algorithm that solves the {\sc generalized multiway cut on trees} problem in time O∗(ρk)O^{*}(\rho^k), where ρ=2+1≈1.555\rho = \sqrt{\sqrt{2} + 1} \approx 1.555 time

    Parameterized Complexity of Weighted Multicut in Trees

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    The Edge Multicut problem is a classical cut problem where given anundirected graph GG, a set of pairs of vertices P\mathcal{P}, and a budgetkk, the goal is to determine if there is a set SS of at most kk edges suchthat for each (s,t)∈P(s,t) \in \mathcal{P}, G−SG-S has no path from ss to tt. EdgeMulticut has been relatively recently shown to be fixed-parameter tractable(FPT), parameterized by kk, by Marx and Razgon [SICOMP 2014], andindependently by Bousquet et al. [SICOMP 2018]. In the weighted version of theproblem, called Weighted Edge Multicut one is additionally given a weightfunction wt:E(G)→N\mathtt{wt} : E(G) \to \mathbb{N} and a weight bound ww, and thegoal is to determine if there is a solution of size at most kk and weight atmost ww. Both the FPT algorithms for Edge Multicut by Marx et al. and Bousquetet al. fail to generalize to the weighted setting. In fact, the weightedproblem is non-trivial even on trees and determining whether Weighted EdgeMulticut on trees is FPT was explicitly posed as an open problem by Bousquet etal. [STACS 2009]. In this article, we answer this question positively bydesigning an algorithm which uses a very recent result by Kim et al. [STOC2022] about directed flow augmentation as subroutine. We also study a variant of this problem where there is no bound on the sizeof the solution, but the parameter is a structural property of the input, forexample, the number of leaves of the tree. We strengthen our results by statingthem for the more general vertex deletion version.<br
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