385 research outputs found

    Counting Euler Tours in Undirected Bounded Treewidth Graphs

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    We show that counting Euler tours in undirected bounded tree-width graphs is tractable even in parallel - by proving a #SAC1\#SAC^1 upper bound. This is in stark contrast to #P-completeness of the same problem in general graphs. Our main technical contribution is to show how (an instance of) dynamic programming on bounded \emph{clique-width} graphs can be performed efficiently in parallel. Thus we show that the sequential result of Espelage, Gurski and Wanke for efficiently computing Hamiltonian paths in bounded clique-width graphs can be adapted in the parallel setting to count the number of Hamiltonian paths which in turn is a tool for counting the number of Euler tours in bounded tree-width graphs. Our technique also yields parallel algorithms for counting longest paths and bipartite perfect matchings in bounded-clique width graphs. While establishing that counting Euler tours in bounded tree-width graphs can be computed by non-uniform monotone arithmetic circuits of polynomial degree (which characterize #SAC1\#SAC^1) is relatively easy, establishing a uniform #SAC1\#SAC^1 bound needs a careful use of polynomial interpolation.Comment: 17 pages; There was an error in the proof of the GapL upper bound claimed in the previous version which has been subsequently remove

    Long induced paths in graphs

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    We prove that every 3-connected planar graph on nn vertices contains an induced path on Ω(logn)\Omega(\log n) vertices, which is best possible and improves the best known lower bound by a multiplicative factor of loglogn\log \log n. We deduce that any planar graph (or more generally, any graph embeddable on a fixed surface) with a path on nn vertices, also contains an induced path on Ω(logn)\Omega(\sqrt{\log n}) vertices. We conjecture that for any kk, there is a contant c(k)c(k) such that any kk-degenerate graph with a path on nn vertices also contains an induced path on Ω((logn)c(k))\Omega((\log n)^{c(k)}) vertices. We provide examples showing that this order of magnitude would be best possible (already for chordal graphs), and prove the conjecture in the case of interval graphs.Comment: 20 pages, 5 figures - revised versio

    Exploiting structure to cope with NP-hard graph problems: Polynomial and exponential time exact algorithms

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    An ideal algorithm for solving a particular problem always finds an optimal solution, finds such a solution for every possible instance, and finds it in polynomial time. When dealing with NP-hard problems, algorithms can only be expected to possess at most two out of these three desirable properties. All algorithms presented in this thesis are exact algorithms, which means that they always find an optimal solution. Demanding the solution to be optimal means that other concessions have to be made when designing an exact algorithm for an NP-hard problem: we either have to impose restrictions on the instances of the problem in order to achieve a polynomial time complexity, or we have to abandon the requirement that the worst-case running time has to be polynomial. In some cases, when the problem under consideration remains NP-hard on restricted input, we are even forced to do both. Most of the problems studied in this thesis deal with partitioning the vertex set of a given graph. In the other problems the task is to find certain types of paths and cycles in graphs. The problems all have in common that they are NP-hard on general graphs. We present several polynomial time algorithms for solving restrictions of these problems to specific graph classes, in particular graphs without long induced paths, chordal graphs and claw-free graphs. For problems that remain NP-hard even on restricted input we present exact exponential time algorithms. In the design of each of our algorithms, structural graph properties have been heavily exploited. Apart from using existing structural results, we prove new structural properties of certain types of graphs in order to obtain our algorithmic results

    A polynomial kernel for Block Graph Deletion

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    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

    Pebbling in Semi-2-Trees

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    Graph pebbling is a network model for transporting discrete resources that are consumed in transit. Deciding whether a given configuration on a particular graph can reach a specified target is NP{\sf NP}-complete, even for diameter two graphs, and deciding whether the pebbling number has a prescribed upper bound is Π2P\Pi_2^{\sf P}-complete. Recently we proved that the pebbling number of a split graph can be computed in polynomial time. This paper advances the program of finding other polynomial classes, moving away from the large tree width, small diameter case (such as split graphs) to small tree width, large diameter, continuing an investigation on the important subfamily of chordal graphs called kk-trees. In particular, we provide a formula, that can be calculated in polynomial time, for the pebbling number of any semi-2-tree, falling shy of the result for the full class of 2-trees.Comment: Revised numerous arguments for clarity and added technical lemmas to support proof of main theorem bette

    Structural parameterizations for boxicity

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    The boxicity of a graph GG is the least integer dd such that GG has an intersection model of axis-aligned dd-dimensional boxes. Boxicity, the problem of deciding whether a given graph GG has boxicity at most dd, is NP-complete for every fixed d2d \ge 2. We show that boxicity is fixed-parameter tractable when parameterized by the cluster vertex deletion number of the input graph. This generalizes the result of Adiga et al., that boxicity is fixed-parameter tractable in the vertex cover number. Moreover, we show that boxicity admits an additive 11-approximation when parameterized by the pathwidth of the input graph. Finally, we provide evidence in favor of a conjecture of Adiga et al. that boxicity remains NP-complete when parameterized by the treewidth.Comment: 19 page
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