8,330 research outputs found

    More applications of the d-neighbor equivalence: acyclicity and connectivity constraints

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    In this paper, we design a framework to obtain efficient algorithms for several problems with a global constraint (acyclicity or connectivity) such as Connected Dominating Set, Node Weighted Steiner Tree, Maximum Induced Tree, Longest Induced Path, and Feedback Vertex Set. We design a meta-algorithm that solves all these problems and whose running time is upper bounded by 2O(k)nO(1)2^{O(k)}\cdot n^{O(1)}, 2O(klog(k))nO(1)2^{O(k \log(k))}\cdot n^{O(1)}, 2O(k2)nO(1)2^{O(k^2)}\cdot n^{O(1)} and nO(k)n^{O(k)} where kk is respectively the clique-width, Q\mathbb{Q}-rank-width, rank-width and maximum induced matching width of a given decomposition. Our meta-algorithm simplifies and unifies the known algorithms for each of the parameters and its running time matches asymptotically also the running times of the best known algorithms for basic NP-hard problems such as Vertex Cover and Dominating Set. Our framework is based on the dd-neighbor equivalence defined in [Bui-Xuan, Telle and Vatshelle, TCS 2013]. The results we obtain highlight the importance of this equivalence relation on the algorithmic applications of width measures. We also prove that our framework could be useful for W[1]W[1]-hard problems parameterized by clique-width such as Max Cut and Maximum Minimal Cut. For these latter problems, we obtain nO(k)n^{O(k)}, nO(k)n^{O(k)} and n2O(k)n^{2^{O(k)}} time algorithms where kk is respectively the clique-width, the Q\mathbb{Q}-rank-width and the rank-width of the input graph

    Exploiting c\mathbf{c}-Closure in Kernelization Algorithms for Graph Problems

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    A graph is c-closed if every pair of vertices with at least c common neighbors is adjacent. The c-closure of a graph G is the smallest number such that G is c-closed. Fox et al. [ICALP '18] defined c-closure and investigated it in the context of clique enumeration. We show that c-closure can be applied in kernelization algorithms for several classic graph problems. We show that Dominating Set admits a kernel of size k^O(c), that Induced Matching admits a kernel with O(c^7*k^8) vertices, and that Irredundant Set admits a kernel with O(c^(5/2)*k^3) vertices. Our kernelization exploits the fact that c-closed graphs have polynomially-bounded Ramsey numbers, as we show

    Tight Kernel Bounds for Problems on Graphs with Small Degeneracy

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    In this paper we consider kernelization for problems on d-degenerate graphs, i.e. graphs such that any subgraph contains a vertex of degree at most dd. This graph class generalizes many classes of graphs for which effective kernelization is known to exist, e.g. planar graphs, H-minor free graphs, and H-topological-minor free graphs. We show that for several natural problems on d-degenerate graphs the best known kernelization upper bounds are essentially tight.Comment: Full version of ESA 201
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