63 research outputs found

    An FPT algorithm and a polynomial kernel for Linear Rankwidth-1 Vertex Deletion

    Get PDF
    Linear rankwidth is a linearized variant of rankwidth, introduced by Oum and Seymour [Approximating clique-width and branch-width. J. Combin. Theory Ser. B, 96(4):514--528, 2006]. Motivated from recent development on graph modification problems regarding classes of graphs of bounded treewidth or pathwidth, we study the Linear Rankwidth-1 Vertex Deletion problem (shortly, LRW1-Vertex Deletion). In the LRW1-Vertex Deletion problem, given an nn-vertex graph GG and a positive integer kk, we want to decide whether there is a set of at most kk vertices whose removal turns GG into a graph of linear rankwidth at most 11 and find such a vertex set if one exists. While the meta-theorem of Courcelle, Makowsky, and Rotics implies that LRW1-Vertex Deletion can be solved in time f(k)n3f(k)\cdot n^3 for some function ff, it is not clear whether this problem allows a running time with a modest exponential function. We first establish that LRW1-Vertex Deletion can be solved in time 8knO(1)8^k\cdot n^{\mathcal{O}(1)}. The major obstacle to this end is how to handle a long induced cycle as an obstruction. To fix this issue, we define necklace graphs and investigate their structural properties. Later, we reduce the polynomial factor by refining the trivial branching step based on a cliquewidth expression of a graph, and obtain an algorithm that runs in time 2O(k)n42^{\mathcal{O}(k)}\cdot n^4. We also prove that the running time cannot be improved to 2o(k)nO(1)2^{o(k)}\cdot n^{\mathcal{O}(1)} under the Exponential Time Hypothesis assumption. Lastly, we show that the LRW1-Vertex Deletion problem admits a polynomial kernel.Comment: 29 pages, 9 figures, An extended abstract appeared in IPEC201

    Parameterized Complexity of Vertex Splitting to Pathwidth at most 1

    Full text link
    Motivated by the planarization of 2-layered straight-line drawings, we consider the problem of modifying a graph such that the resulting graph has pathwidth at most 1. The problem Pathwidth-One Vertex Explosion (POVE) asks whether such a graph can be obtained using at most kk vertex explosions, where a vertex explosion replaces a vertex vv by deg(v)(v) degree-1 vertices, each incident to exactly one edge that was originally incident to vv. For POVE, we give an FPT algorithm with running time O(4km)O(4^k \cdot m) and an O(k2)O(k^2) kernel, thereby improving over the O(k6)O(k^6)-kernel by Ahmed et al. [GD 22] in a more general setting. Similarly, a vertex split replaces a vertex vv by two distinct vertices v1v_1 and v2v_2 and distributes the edges originally incident to vv arbitrarily to v1v_1 and v2v_2. Analogously to POVE, we define the problem variant Pathwidth-One Vertex Splitting (POVS) that uses the split operation instead of vertex explosions. Here we obtain a linear kernel and an algorithm with running time O((6k+12)km)O((6k+12)^k \cdot m). This answers an open question by Ahmed et al. [GD22]. Finally, we consider the problem Π\Pi Vertex Splitting (Π\Pi-VS), which generalizes the problem POVS and asks whether a given graph can be turned into a graph of a specific graph class Π\Pi using at most kk vertex splits. For graph classes Π\Pi that can be tested in monadic second-order graph logic (MSO2_2), we show that the problem Π\Pi-VS can be expressed as an MSO2_2 formula, resulting in an FPT algorithm for Π\Pi-VS parameterized by kk if Π\Pi additionally has bounded treewidth. We obtain the same result for the problem variant using vertex explosions

    Hitting forbidden minors: Approximation and Kernelization

    Get PDF
    We study a general class of problems called F-deletion problems. In an F-deletion problem, we are asked whether a subset of at most kk vertices can be deleted from a graph GG such that the resulting graph does not contain as a minor any graph from the family F of forbidden minors. We obtain a number of algorithmic results on the F-deletion problem when F contains a planar graph. We give (1) a linear vertex kernel on graphs excluding tt-claw K1,tK_{1,t}, the star with tt leves, as an induced subgraph, where tt is a fixed integer. (2) an approximation algorithm achieving an approximation ratio of O(log3/2OPT)O(\log^{3/2} OPT), where OPTOPT is the size of an optimal solution on general undirected graphs. Finally, we obtain polynomial kernels for the case when F contains graph θc\theta_c as a minor for a fixed integer cc. The graph θc\theta_c consists of two vertices connected by cc parallel edges. Even though this may appear to be a very restricted class of problems it already encompasses well-studied problems such as {\sc Vertex Cover}, {\sc Feedback Vertex Set} and Diamond Hitting Set. The generic kernelization algorithm is based on a non-trivial application of protrusion techniques, previously used only for problems on topological graph classes

    A polynomial kernel for Block Graph Deletion

    Get PDF
    In the Block Graph Deletion problem, we are given a graph GG on nn vertices and a positive integer kk, and the objective is to check whether it is possible to delete at most kk vertices from GG to make it a block graph, i.e., a graph in which each block is a clique. In this paper, we obtain a kernel with O(k6)\mathcal{O}(k^{6}) vertices for the Block Graph Deletion problem. This is a first step to investigate polynomial kernels for deletion problems into non-trivial classes of graphs of bounded rank-width, but unbounded tree-width. Our result also implies that Chordal Vertex Deletion admits a polynomial-size kernel on diamond-free graphs. For the kernelization and its analysis, we introduce the notion of `complete degree' of a vertex. We believe that the underlying idea can be potentially applied to other problems. We also prove that the Block Graph Deletion problem can be solved in time 10knO(1)10^{k}\cdot n^{\mathcal{O}(1)}.Comment: 22 pages, 2 figures, An extended abstract appeared in IPEC201

    Structural Parameterizations for Two Bounded Degree Problems Revisited

    Get PDF

    Preprocessing for Outerplanar Vertex Deletion: An Elementary Kernel of Quartic Size

    Get PDF
    In the ?-Minor-Free Deletion problem one is given an undirected graph G, an integer k, and the task is to determine whether there exists a vertex set S of size at most k, so that G-S contains no graph from the finite family ? as a minor. It is known that whenever ? contains at least one planar graph, then ?-Minor-Free Deletion admits a polynomial kernel, that is, there is a polynomial-time algorithm that outputs an equivalent instance of size k^{?(1)} [Fomin, Lokshtanov, Misra, Saurabh; FOCS 2012]. However, this result relies on non-constructive arguments based on well-quasi-ordering and does not provide a concrete bound on the kernel size. We study the Outerplanar Deletion problem, in which we want to remove at most k vertices from a graph to make it outerplanar. This is a special case of ?-Minor-Free Deletion for the family ? = {K?, K_{2,3}}. The class of outerplanar graphs is arguably the simplest class of graphs for which no explicit kernelization size bounds are known. By exploiting the combinatorial properties of outerplanar graphs we present elementary reduction rules decreasing the size of a graph. This yields a constructive kernel with ?(k?) vertices and edges. As a corollary, we derive that any minor-minimal obstruction to having an outerplanar deletion set of size k has ?(k?) vertices and edges

    Dynamic Parameterized Problems

    Get PDF
    In this work, we study the parameterized complexity of various classical graph-theoretic problems in the dynamic framework where the input graph is being updated by a sequence of edge additions and deletions. Vertex subset problems on graphs typically deal with finding a subset of vertices having certain properties that are of interest to us. In real-world applications, the graph under consideration often changes over time and due to this dynamics, the solution at hand might lose the desired properties. The goal in the area of dynamic graph algorithms is to efficiently maintain a solution under these changes. Recomputing a new solution on the new graph is an expensive task especially when the number of modifications made to the graph is significantly smaller than the size of the graph. In the context of parameterized algorithms, two natural parameters are the size k of the symmetric difference of the edge sets of the two graphs (on n vertices) and the size r of the symmetric difference of the two solutions. We study the Dynamic Pi-Deletion problem which is the dynamic variant of the Pi-Deletion problem and show NP-hardness, fixed-parameter tractability and kernelization results. For specific cases of Dynamic Pi-Deletion such as Dynamic Vertex Cover and Dynamic Feedback Vertex Set, we describe improved FPT algorithms and give linear kernels. Specifically, we show that Dynamic Vertex Cover admits algorithms with running times 1.1740^k*n^{O(1)} (polynomial space) and 1.1277^k*n^{O(1)} (exponential space). Then, we show that Dynamic Feedback Vertex Set admits a randomized algorithm with 1.6667^k*n^{O(1)} running time. Finally, we consider Dynamic Connected Vertex Cover, Dynamic Dominating Set and Dynamic Connected Dominating Set and describe algorithms with 2^k*n^{O(1)} running time improving over the known running time bounds for these problems. Additionally, for Dynamic Dominating Set and Dynamic Connected Dominating Set, we show that this is the optimal running time (up to polynomial factors) assuming the Set Cover Conjecture
    corecore