6 research outputs found

    Planar Induced Subgraphs of Sparse Graphs

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    We show that every graph has an induced pseudoforest of at least nm/4.5n-m/4.5 vertices, an induced partial 2-tree of at least nm/5n-m/5 vertices, and an induced planar subgraph of at least nm/5.2174n-m/5.2174 vertices. These results are constructive, implying linear-time algorithms to find the respective induced subgraphs. We also show that the size of the largest KhK_h-minor-free graph in a given graph can sometimes be at most nm/6+o(m)n-m/6+o(m).Comment: Accepted by Graph Drawing 2014. To appear in Journal of Graph Algorithms and Application

    Subexponential Parameterized Algorithms for Planar and Apex-Minor-Free Graphs via Low Treewidth Pattern Covering

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    We prove the following theorem. Given a planar graph GG and an integer kk, it is possible in polynomial time to randomly sample a subset AA of vertices of GG with the following properties: (i) AA induces a subgraph of GG of treewidth O(klogk)\mathcal{O}(\sqrt{k}\log k), and (ii) for every connected subgraph HH of GG on at most kk vertices, the probability that AA covers the whole vertex set of HH is at least (2O(klog2k)nO(1))1(2^{\mathcal{O}(\sqrt{k}\log^2 k)}\cdot n^{\mathcal{O}(1)})^{-1}, where nn is the number of vertices of GG. Together with standard dynamic programming techniques for graphs of bounded treewidth, this result gives a versatile technique for obtaining (randomized) subexponential parameterized algorithms for problems on planar graphs, usually with running time bound 2O(klog2k)nO(1)2^{\mathcal{O}(\sqrt{k} \log^2 k)} n^{\mathcal{O}(1)}. The technique can be applied to problems expressible as searching for a small, connected pattern with a prescribed property in a large host graph, examples of such problems include Directed kk-Path, Weighted kk-Path, Vertex Cover Local Search, and Subgraph Isomorphism, among others. Up to this point, it was open whether these problems can be solved in subexponential parameterized time on planar graphs, because they are not amenable to the classic technique of bidimensionality. Furthermore, all our results hold in fact on any class of graphs that exclude a fixed apex graph as a minor, in particular on graphs embeddable in any fixed surface

    Network Sparsification for Steiner Problems on Planar and Bounded-Genus Graphs

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    We propose polynomial-time algorithms that sparsify planar and bounded-genus graphs while preserving optimal or near-optimal solutions to Steiner problems. Our main contribution is a polynomial-time algorithm that, given an unweighted graph GG embedded on a surface of genus gg and a designated face ff bounded by a simple cycle of length kk, uncovers a set FE(G)F \subseteq E(G) of size polynomial in gg and kk that contains an optimal Steiner tree for any set of terminals that is a subset of the vertices of ff. We apply this general theorem to prove that: * given an unweighted graph GG embedded on a surface of genus gg and a terminal set SV(G)S \subseteq V(G), one can in polynomial time find a set FE(G)F \subseteq E(G) that contains an optimal Steiner tree TT for SS and that has size polynomial in gg and E(T)|E(T)|; * an analogous result holds for an optimal Steiner forest for a set SS of terminal pairs; * given an unweighted planar graph GG and a terminal set SV(G)S \subseteq V(G), one can in polynomial time find a set FE(G)F \subseteq E(G) that contains an optimal (edge) multiway cut CC separating SS and that has size polynomial in C|C|. In the language of parameterized complexity, these results imply the first polynomial kernels for Steiner Tree and Steiner Forest on planar and bounded-genus graphs (parameterized by the size of the tree and forest, respectively) and for (Edge) Multiway Cut on planar graphs (parameterized by the size of the cutset). Additionally, we obtain a weighted variant of our main contribution

    Algorithms for Optimization Problems in Planar Graphs (Dagstuhl Seminar 13421)

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    This report documents the program and the outcomes of Dagstuhl Seminar 13421 "Algorithms for Optimization Problems in Planar Graphs". The seminar was held from October 13 to October 18, 2013. This report contains abstracts for the recent developments in planar graph algorithms discussed during the seminar as well as summaries of open problems in this area of research

    Digital Object Identifier 10.4230/DagRep.3.10.36 Edited in cooperation with Kyle Fox 1 Executive Summary

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    This report documents the program and the outcomes of Dagstuhl Seminar 13421 “Algorithms for Optimization Problems in Planar Graphs”. The seminar was held from October 13 to October 18, 2013. This report contains abstracts for the recent developments in planar graph algorithms discussed during the seminar as well as summaries of open problems in this area of research
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