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Ignasi Sau

Publications and source records attributed to Ignasi Sau.

At least 55 records · Page 3Linked to original sources

arXiv2021

Hitting minors on bounded treewidth graphs. II. Single-exponential algorithms

For a finite collection of graphs ${\cal F}$, the ${\cal F}$-M-DELETION (resp. ${\cal F}$-TM-DELETION) problem consists in, given a graph $G$ and an integer $k$, decide whether there exists $S \subseteq V(G)$ with $|S| \leq k$ such that $G \setminus S$ does not contain any of the graphs in ${\cal F}$ as a minor (resp. topological minor). We are interested in the parameterized complexity of both problems when the parameter is the treewidth of $G$, denoted by $tw$, and specifically in the cases where ${\cal F}$ contains a single connected planar graph $H$. We present algorithms running in time $2^{O(tw)} \cdot n^{O(1)}$, called single-exponential, when $H$ is either $P_3$, $P_4$, $C_4$, the paw, the chair, and the banner for both $\{H\}$-M-DELETION and $\{H\}$-TM-DELETION, and when $H=K_{1,i}$, with $i \geq 1$, for $\{H\}$-TM-DELETION. Some of these algorithms use the rank-based approach introduced by Bodlaender et al. [Inform Comput, 2015]. This is the second of a series of articles on this topic, and the results given here together with other ones allow us, in particular, to provide a tight dichotomy on the complexity of $\{H\}$-M-DELETION in terms of $H$.

cs.DS↗

arXiv2021

Hitting minors on bounded treewidth graphs. III. Lower bounds

For a finite collection of graphs ${\cal F}$, the ${\cal F}$-M-DELETION problem consists in, given a graph $G$ and an integer $k$, decide whether there exists $S \subseteq V(G)$ with $|S| \leq k$ such that $G \setminus S$ does not contain any of the graphs in ${\cal F}$ as a minor. We are interested in the parameterized complexity of ${\cal F}$-M-DELETION when the parameter is the treewidth of $G$, denoted by $tw$. Our objective is to determine, for a fixed ${\cal F}$, the smallest function $f_{\cal F}$ such that ${\cal F}$-M-DELETION can be solved in time $f_{\cal F}(tw) \cdot n^{O(1)}$ on $n$-vertex graphs. We provide lower bounds under the ETH on $f_{\cal F}$ for several collections ${\cal F}$. We first prove that for any ${\cal F}$ containing connected graphs of size at least two, $f_{\cal F}(tw)= 2^{Ω(tw)}$, even if the input graph $G$ is planar. Our main contribution consists of superexponential lower bounds for a number of collections ${\cal F}$, inspired by a reduction of Bonnet et al.~[IPEC, 2017]. In particular, we prove that when ${\cal F}$ contains a single connected graph $H$ that is either $P_5$ or is not a minor of the banner (that is, the graph consisting of a $C_4$ plus a pendent edge), then $f_{\cal F}(tw)= 2^{Ω(tw \cdot \log tw)}$. This is the third of a series of articles on this topic, and the results given here together with other ones allow us, in particular, to provide a tight dichotomy on the complexity of $\{H\}$-M-DELETION, in terms of $H$, when $H$ is connected.

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arXiv2021

k-apices of minor-closed graph classes. II. Parameterized algorithms

Let ${\cal G}$ be a minor-closed graph class. We say that a graph $G$ is a $k$-apex of ${\cal G}$ if $G$ contains a set $S$ of at most $k$ vertices such that $G\setminus S$ belongs to ${\cal G}$. We denote by ${\cal A}_k ({\cal G})$ the set of all graphs that are $k$-apices of ${\cal G}.$ In the first paper of this series we obtained upper bounds on the size of the graphs in the minor-obstruction set of ${\cal A}_k ({\cal G})$, i.e., the minor-minimal set of graphs not belonging to ${\cal A}_k ({\cal G}).$ In this article we provide an algorithm that, given a graph $G$ on $n$ vertices, runs in $2^{{\sf poly}(k)}\cdot n^3$-time and either returns a set $S$ certifying that $G \in {\cal A}_k ({\cal G})$, or reports that $G \notin {\cal A}_k ({\cal G})$. Here ${\sf poly}$ is a polynomial function whose degree depends on the maximum size of a minor-obstruction of ${\cal G}.$ In the special case where ${\cal G}$ excludes some apex graph as a minor, we give an alternative algorithm running in $2^{{\sf poly}(k)}\cdot n^2$-time.

cs.DS↗

arXiv2021

Parameterized complexity of computing maximum minimal blocking and hitting sets

A blocking set in a graph $G$ is a subset of vertices that intersects every maximum independent set of $G$. Let ${\sf mmbs}(G)$ be the size of a maximum (inclusion-wise) minimal blocking set of $G$. This parameter has recently played an important role in the kernelization of Vertex Cover parameterized by the distance to a graph class ${\cal F}$. Indeed, it turns out that the existence of a polynomial kernel for this problem is closely related to the property that ${\sf mmbs}({\cal F})=\sup_{G \in {\cal F}}{\sf mmbs}(G)$ is bounded by a constant, and thus several recent results focused on determining ${\sf mmbs}({\cal F})$ for different classes ${\cal F}$. We consider the parameterized complexity of computing ${\sf mmbs}$ under various parameterizations, such as the size of a maximum independent set of the input graph and the natural parameter. We provide a panorama of the complexity of computing both ${\sf mmbs}$ and ${\sf mmhs}$, which is the size of a maximum minimal hitting set of a hypergraph, a closely related parameter. Finally, we consider the problem of computing ${\sf mmbs}$ parameterized by treewidth, especially relevant in the context of kernelization. Given the "counting" nature of ${\sf mmbs}$, it does not seem to be expressible in monadic second-order logic, hence its tractability does not follow from Courcelle's theorem. Our main technical contribution is a fixed-parameter tractable algorithm for this problem.

cs.DS↗

arXiv2020

Target set selection with maximum activation time

A target set selection model is a graph $G$ with a threshold function $τ:V\to \mathbb{N}$ upper-bounded by the vertex degree. For a given model, a set $S_0\subseteq V(G)$ is a target set if $V(G)$ can be partitioned into non-empty subsets $S_0,S_1,\dotsc,S_t$ such that, for $i \in \{1, \ldots, t\}$, $S_i$ contains exactly every vertex $v$ having at least $τ(v)$ neighbors in $S_0\cup\dots\cup S_{i-1}$. We say that $t$ is the activation time $t_τ(S_0)$ of the target set $S_0$. The problem of, given such a model, finding a target set of minimum size has been extensively studied in the literature. In this article, we investigate its variant, which we call TSS-time, in which the goal is to find a target set $S_0$ that maximizes $t_τ(S_0)$. That is, given a graph $G$, a threshold function $τ$ in $G$, and an integer $k$, the objective of the TSS-time problem is to decide whether $G$ contains a target set $S_0$ such that $t_τ(S_0)\geq k$. Let $τ^* = \max_{v \in V(G)} τ(v)$. Our main result is the following dichotomy about the complexity of TSS-time when $G$ belongs to a minor-closed graph class ${\cal C}$: if ${\cal C}$ has bounded local treewidth, the problem is FPT parameterized by $k$ and $τ^{\star}$; otherwise, it is NP-complete even for fixed $k=4$ and $τ^{\star}=2$. We also prove that, with $τ^*=2$, the problem is NP-hard in bipartite graphs for fixed $k=5$, and from previous results we observe that TSS-time is NP-hard in planar graphs and W[1]-hard parameterized by treewidth. Finally, we present a linear-time algorithm to find a target set $S_0$ in a given tree maximizing $t_τ(S_0)$.

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arXiv2020

A Unifying Model for Locally Constrained Spanning Tree Problems

Given a graph $G$ and a digraph $D$ whose vertices are the edges of $G$, we investigate the problem of finding a spanning tree of $G$ that satisfies the constraints imposed by $D$. The restrictions to add an edge in the tree depend on its neighborhood in $D$. Here, we generalize previously investigated problems by also considering as input functions $\ell$ and $u$ on $E(G)$ that give a lower and an upper bound, respectively, on the number of constraints that must be satisfied by each edge. The produced feasibility problem is denoted by \texttt{G-DCST}, while the optimization problem is denoted by \texttt{G-DCMST}. We show that \texttt{G-DCST} is NP-complete even under strong assumptions on the structures of $G$ and $D$, as well as on functions $\ell$ and $u$. On the positive side, we prove two polynomial results, one for \texttt{G-DCST} and another for \texttt{G-DCMST}, and also give a simple exponential-time algorithm along with a proof that it is asymptotically optimal under the Ð. Finally, we prove that other previously studied constrained spanning tree (\textsc{CST}) problems can be modeled within our framework, namely, the \textsc{Conflict CST}, the \textsc{Forcing CS, the \textsc{At Least One/All Dependency CST}, the \textsc{Maximum Degree CST}, the \textsc{Minimum Degree CST}, and the \textsc{Fixed-Leaves Minimum Degree CST}.

cs.CC↗

arXiv2019

Finding cuts of bounded degree: complexity, FPT and exact algorithms, and kernelization

A matching cut is a partition of the vertex set of a graph into two sets $A$ and $B$ such that each vertex has at most one neighbor in the other side of the cut. The MATCHING CUT problem asks whether a graph has a matching cut, and has been intensively studied in the literature. Motivated by a question posed by Komusiewicz et al. [IPEC 2018], we introduce a natural generalization of this problem, which we call $d$-CUT: for a positive integer $d$, a $d$-cut is a bipartition of the vertex set of a graph into two sets $A$ and $B$ such that each vertex has at most $d$ neighbors across the cut. We generalize (and in some cases, improve) a number of results for the MATCHING CUT problem. Namely, we begin with an NP-hardness reduction for $d$-CUT on $(2d+2)$-regular graphs and a polynomial algorithm for graphs of maximum degree at most $d+2$. The degree bound in the hardness result is unlikely to be improved, as it would disprove a long-standing conjecture in the context of internal partitions. We then give FPT algorithms for several parameters: the maximum number of edges crossing the cut, treewidth, distance to cluster, and distance to co-cluster. In particular, the treewidth algorithm improves upon the running time of the best known algorithm for MATCHING CUT. Our main technical contribution, building on the techniques of Komusiewicz et al. [IPEC 2018], is a polynomial kernel for $d$-CUT for every positive integer $d$, parameterized by the distance to a cluster graph. We also rule out the existence of polynomial kernels when parameterizing simultaneously by the number of edges crossing the cut, the treewidth, and the maximum degree. Finally, we provide an exact exponential algorithm slightly faster than the naive brute force approach running in time $O^*(2^n)$.

cs.DS↗

arXiv2018

A tight Erdős-Pósa function for wheel minors

Let $W_t$ denote the wheel on $t+1$ vertices. We prove that for every integer $t \geq 3$ there is a constant $c=c(t)$ such that for every integer $k\geq 1$ and every graph $G$, either $G$ has $k$ vertex-disjoint subgraphs each containing $W_t$ as minor, or there is a subset $X$ of at most $c k \log k$ vertices such that $G-X$ has no $W_t$ minor. This is best possible, up to the value of $c$. We conjecture that the result remains true more generally if we replace $W_t$ with any fixed planar graph $H$.

cs.DM↗

arXiv2018

How much does a treedepth modulator help to obtain polynomial kernels beyond sparse graphs?

In the last years, kernelization with structural parameters has been an active area of research within the field of parameterized complexity. As a relevant example, Gajarsk{y} et al. [ESA 2013] proved that every graph problem satisfying a property called finite integer index admits a linear kernel on graphs of bounded expansion and an almost linear kernel on nowhere dense graphs, parameterized by the size of a $c$-treedepth modulator, which is a vertex set whose removal results in a graph of treedepth at most $c$, where $c \geq 1$ is a fixed integer. The authors left as further research to investigate this parameter on general graphs, and in particular to find problems that, while admitting polynomial kernels on sparse graphs, behave differently on general graphs. In this article we answer this question by finding two very natural such problems: we prove that Vertex Cover admits a polynomial kernel on general graphs for any integer $c \geq 1$, and that Dominating Set does not for any integer $c \geq 2$ even on degenerate graphs, unless $\text{NP} \subseteq \text{coNP}/\text{poly}$. For the positive result, we build on the techniques of Jansen and Bodlaender [STACS 2011], and for the negative result we use a polynomial parameter transformation for $c\geq 3$ and an OR-cross-composition for $c = 2$. As existing results imply that Dominating Set admits a polynomial kernel on degenerate graphs for $c = 1$, our result provides a dichotomy about the existence of polynomial kernels for Dominating Set on degenerate graphs with this parameter.

cs.DS↗

arXiv2018

On the (parameterized) complexity of recognizing well-covered (r,l)-graphs

An $(r, \ell)$-partition of a graph $G$ is a partition of its vertex set into $r$ independent sets and $\ell$ cliques. A graph is $(r, \ell)$ if it admits an $(r, \ell)$-partition. A graph is well-covered if every maximal independent set is also maximum. A graph is $(r,\ell)$-well-covered if it is both $(r,\ell)$ and well-covered. In this paper we consider two different decision problems. In the $(r,\ell)$-Well-Covered Graph problem ($(r,\ell)$WCG for short), we are given a graph $G$, and the question is whether $G$ is an $(r,\ell)$-well-covered graph. In the Well-Covered $(r,\ell)$-Graph problem (WC$(r,\ell)$G for short), we are given an $(r,\ell)$-graph $G$ together with an $(r,\ell)$-partition of $V(G)$ into $r$ independent sets and $\ell$ cliques, and the question is whether $G$ is well-covered. We classify most of these problems into P, coNP-complete, NP-complete, NP-hard, or coNP-hard. Only the cases WC$(r,0)$G for $r\geq 3$ remain open. In addition, we consider the parameterized complexity of these problems for several choices of parameters, such as the size $α$ of a maximum independent set of the input graph, its neighborhood diversity, its clique-width, or the number $\ell$ of cliques in an $(r, \ell)$-partition. In particular, we show that the parameterized problem of deciding whether a general graph is well-covered parameterized by $α$ can be reduced to the WC$(0,\ell)$G problem parameterized by $\ell$. In addition, we prove that both problems are coW[2]-hard but can be solved in XP-time.

cs.DS↗

arXiv2018

Dual parameterization of Weighted Coloring

Given a graph $G$, a proper $k$-coloring of $G$ is a partition $c = (S_i)_{i\in [1,k]}$ of $V(G)$ into $k$ stable sets $S_1,\ldots, S_{k}$. Given a weight function $w: V(G) \to \mathbb{R}^+$, the weight of a color $S_i$ is defined as $w(i) = \max_{v \in S_i} w(v)$ and the weight of a coloring $c$ as $w(c) = \sum_{i=1}^{k}w(i)$. Guan and Zhu [Inf. Process. Lett., 1997] defined the weighted chromatic number of a pair $(G,w)$, denoted by $σ(G,w)$, as the minimum weight of a proper coloring of $G$. The problem of determining $σ(G,w)$ has received considerable attention during the last years, and has been proved to be notoriously hard: for instance, it is NP-hard on split graphs, unsolvable on $n$-vertex trees in time $n^{o(\log n)}$ unless the ETH fails, and W[1]-hard on forests parameterized by the size of a largest tree. In this article we provide some positive results for the problem, by considering its so-called dual parameterization: given a vertex-weighted graph $(G,w)$ and an integer $k$, the question is whether $σ(G,w) \leq \sum_{v \in V(G)} w(v) - k$. We prove that this problem is FPT by providing an algorithm running in time $9^k \cdot n^{O(1)}$, and it is easy to see that no algorithm in time $2^{o(k)} \cdot n^{O(1)}$ exists under the ETH. On the other hand, we present a kernel with at most $(2^{k-1}+1) (k-1)$ vertices, and we rule out the existence of polynomial kernels unless ${\sf NP} \subseteq {\sf coNP} / {\sf poly}$, even on split graphs with only two different weights. Finally, we identify some classes of graphs on which the problem admits a polynomial kernel, in particular interval graphs and subclasses of split graphs, and in the latter case we present lower bounds on the degrees of the polynomials.

cs.DS↗

arXiv2018

Counting Gallai 3-colorings of complete graphs

An edge coloring of the n-vertex complete graph K_n is a Gallai coloring if it does not contain any rainbow triangle, that is, a triangle whose edges are colored with three distinct colors. We prove that the number of Gallai colorings of K_n with at most three colors is at most 7(n+1)*2^{n choose 2}, which improves the best known upper bound of \frac{3}{2} * (n-1)! * 2^{(n-1) choose 2} in [Discrete Mathematics, 2017].

math.CO↗

arXiv2018

A Linear Kernel for Planar Total Dominating Set

A total dominating set of a graph $G=(V,E)$ is a subset $D \subseteq V$ such that every vertex in $V$ is adjacent to some vertex in $D$. Finding a total dominating set of minimum size is NP-hard on planar graphs and W[2]-complete on general graphs when parameterized by the solution size. By the meta-theorem of Bodlaender et al. [J. ACM, 2016], there exists a linear kernel for Total Dominating Set on graphs of bounded genus. Nevertheless, it is not clear how such a kernel can be effectively constructed, and how to obtain explicit reduction rules with reasonably small constants. Following the approach of Alber et al. [J. ACM, 2004], we provide an explicit kernel for Total Dominating Set on planar graphs with at most $410k$ vertices, where $k$ is the size of the solution. This result complements several known constructive linear kernels on planar graphs for other domination problems such as Dominating Set, Edge Dominating Set, Efficient Dominating Set, Connected Dominating Set, or Red-Blue Dominating Set.

cs.DS↗

arXiv2018

Maximum cuts in edge-colored graphs

The input of the Maximum Colored Cut problem consists of a graph $G=(V,E)$ with an edge-coloring $c:E\to \{1,2,3,\ldots , p\}$ and a positive integer $k$, and the question is whether $G$ has a nontrivial edge cut using at least $k$ colors. The Colorful Cut problem has the same input but asks for a nontrivial edge cut using all $p$ colors. Unlike what happens for the classical Maximum Cut problem, we prove that both problems are NP-complete even on complete, planar, or bounded treewidth graphs. Furthermore, we prove that Colorful Cut is NP-complete even when each color class induces a clique of size at most 3, but is trivially solvable when each color induces a $K_2$. On the positive side, we prove that Maximum Colored Cut is fixed-parameter tractable when parameterized by either $k$ or $p$, by constructing a cubic kernel in both cases.

cs.DS↗

arXiv2018

Weighted proper orientations of trees and graphs of bounded treewidth

Given a simple graph $G$, a weight function $w:E(G)\rightarrow \mathbb{N} \setminus \{0\}$, and an orientation $D$ of $G$, we define $μ^-(D) = \max_{v \in V(G)} w_D^-(v)$, where $w^-_D(v) = \sum_{u\in N_D^{-}(v)}w(uv)$. We say that $D$ is a weighted proper orientation of $G$ if $w^-_D(u) \neq w^-_D(v)$ whenever $u$ and $v$ are adjacent. We introduce the parameter weighted proper orientation number of $G$, denoted by $\overrightarrowχ(G,w)$, which is the minimum, over all weighted proper orientations $D$ of $G$, of $μ^-(D)$. When all the weights are equal to 1, this parameter is equal to the proper orientation number of $G$, which has been object of recent studies and whose determination is NP-hard in general, but polynomial-time solvable on trees. Here, we prove that the equivalent decision problem of the weighted proper orientation number (i.e., $\overrightarrowχ(G,w) \leq k$?) is (weakly) NP-complete on trees but can be solved by a pseudo-polynomial time algorithm whose running time depends on $k$. Furthermore, we present a dynamic programming algorithm to determine whether a general graph $G$ on $n$ vertices and treewidth at most ${\sf tw}$ satisfies $\overrightarrowχ(G,w) \leq k$, running in time $O(2^{{\sf tw}^2}\cdot k^{3{\sf tw}}\cdot {\sf tw} \cdot n)$, and we complement this result by showing that the problem is W[1]-hard on general graphs parameterized by the treewidth of $G$, even if the weights are polynomial in $n$.

cs.DS↗

arXiv2017

On the complexity of finding internally vertex-disjoint long directed paths

For two positive integers $k$ and $\ell$, a $(k \times \ell)$-spindle is the union of $k$ pairwise internally vertex-disjoint directed paths with $\ell$ arcs between two vertices $u$ and $v$. We are interested in the (parameterized) complexity of several problems consisting in deciding whether a given digraph contains a subdivision of a spindle, which generalize both the Maximum Flow and Longest Path problems. We obtain the following complexity dichotomy: for a fixed $\ell \geq 1$, finding the largest $k$ such that an input digraph $G$ contains a subdivision of a $(k \times \ell)$-spindle is polynomial-time solvable if $\ell \leq 3$, and NP-hard otherwise. We place special emphasis on finding spindles with exactly two paths and present FPT algorithms that are asymptotically optimal under the ETH. These algorithms are based on the technique of representative families in matroids, and use also color-coding as a subroutine. Finally, we study the case where the input graph is acyclic, and present several algorithmic and hardness results.

cs.DS↗

arXiv2017

Improved kernels for Signed Max Cut parameterized above lower bound on (r,l)-graphs

A graph $G$ is signed if each edge is assigned $+$ or $-$. A signed graph is balanced if there is a bipartition of its vertex set such that an edge has sign $-$ if and only if its endpoints are in different parts. The Edwards-Erdös bound states that every graph with $n$ vertices and $m$ edges has a balanced subgraph with at least $\frac{m}{2}+\frac{n-1}{4}$ edges. In the Signed Max Cut Above Tight Lower Bound (Signed Max Cut ATLB) problem, given a signed graph $G$ and a parameter $k$, the question is whether $G$ has a balanced subgraph with at least $\frac{m}{2}+\frac{n-1}{4}+\frac{k}{4}$ edges. This problem generalizes Max Cut Above Tight Lower Bound, for which a kernel with $O(k^5)$ vertices was given by Crowston et al. [ICALP 2012, Algorithmica 2015]. Crowston et al. [TCS 2013] improved this result by providing a kernel with $O(k^3)$ vertices for the more general Signed Max Cut ATLB problem. In this article we are interested in improving the size of the kernels for Signed Max Cut ATLB on restricted graph classes for which the problem remains hard. For two integers $r,\ell \geq 0$, a graph $G$ is an $(r,\ell)$-graph if $V(G)$ can be partitioned into $r$ independent sets and $\ell$ cliques. Building on the techniques of Crowston et al. [TCS 2013], we provide a kernel with $O(k^2)$ vertices on $(r,\ell)$-graphs for any fixed $r,\ell \geq 0$, and a simple linear kernel on subclasses of split graphs for which we prove that the problem is still NP-hard.

cs.DS↗

arXiv2017

A Linear Kernel for Planar Red-Blue Dominating Set

In the Red-Blue Dominating Set problem, we are given a bipartite graph $G = (V_B \cup V_R,E)$ and an integer $k$, and asked whether $G$ has a subset $D \subseteq V_B$ of at most $k$ "blue" vertices such that each "red" vertex from $V_R$ is adjacent to a vertex in $D$. We provide the first explicit linear kernel for this problem on planar graphs, of size at most $43k$.

cs.DS↗