51 research outputs found

    Composing dynamic programming tree-decomposition-based algorithms

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    Given two integers β„“\ell and pp as well as β„“\ell graph classes H1,…,Hβ„“\mathcal{H}_1,\ldots,\mathcal{H}_\ell, the problems GraphPart(H1,…,Hβ„“,p)\mathsf{GraphPart}(\mathcal{H}_1, \ldots, \mathcal{H}_\ell,p), VertPart(H1,…,Hβ„“)\mathsf{VertPart}(\mathcal{H}_1, \ldots, \mathcal{H}_\ell), and EdgePart(H1,…,Hβ„“)\mathsf{EdgePart}(\mathcal{H}_1, \ldots, \mathcal{H}_\ell) ask, given graph GG as input, whether V(G)V(G), V(G)V(G), E(G)E(G) respectively can be partitioned into β„“\ell sets S1,…,Sβ„“S_1, \ldots, S_\ell such that, for each ii between 11 and β„“\ell, G[Vi]∈HiG[V_i] \in \mathcal{H}_i, G[Vi]∈HiG[V_i] \in \mathcal{H}_i, (V(G),Si)∈Hi(V(G),S_i) \in \mathcal{H}_i respectively. Moreover in GraphPart(H1,…,Hβ„“,p)\mathsf{GraphPart}(\mathcal{H}_1, \ldots, \mathcal{H}_\ell,p), we request that the number of edges with endpoints in different sets of the partition is bounded by pp. We show that if there exist dynamic programming tree-decomposition-based algorithms for recognizing the graph classes Hi\mathcal{H}_i, for each ii, then we can constructively create a dynamic programming tree-decomposition-based algorithms for GraphPart(H1,…,Hβ„“,p)\mathsf{GraphPart}(\mathcal{H}_1, \ldots, \mathcal{H}_\ell,p), VertPart(H1,…,Hβ„“)\mathsf{VertPart}(\mathcal{H}_1, \ldots, \mathcal{H}_\ell), and EdgePart(H1,…,Hβ„“)\mathsf{EdgePart}(\mathcal{H}_1, \ldots, \mathcal{H}_\ell). We show that, in some known cases, the obtained running times are comparable to those of the best know algorithms

    Contraction-Bidimensionality of Geometric Intersection Graphs

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    Given a graph G, we define bcg(G) as the minimum k for which G can be contracted to the uniformly triangulated grid Gamma_k. A graph class G has the SQGC property if every graph G in G has treewidth O(bcg(G)c) for some 1 <= c < 2. The SQGC property is important for algorithm design as it defines the applicability horizon of a series of meta-algorithmic results, in the framework of bidimensionality theory, related to fast parameterized algorithms, kernelization, and approximation schemes. These results apply to a wide family of problems, namely problems that are contraction-bidimensional. Our main combinatorial result reveals a general family of graph classes that satisfy the SQGC property and includes bounded-degree string graphs. This considerably extends the applicability of bidimensionality theory for several intersection graph classes of 2-dimensional geometrical objects

    Non-monotone target sets for threshold values restricted to 00, 11, and the vertex degree

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    We consider a non-monotone activation process (Xt)t∈{0,1,2,…}(X_t)_{t\in\{ 0,1,2,\ldots\}} on a graph GG, where X0βŠ†V(G)X_0\subseteq V(G), Xt={u∈V(G):∣NG(u)∩Xtβˆ’1∣β‰₯Ο„(u)}X_t=\{ u\in V(G):|N_G(u)\cap X_{t-1}|\geq \tau(u)\} for every positive integer tt, and Ο„:V(G)β†’Z\tau:V(G)\to \mathbb{Z} is a threshold function. The set X0X_0 is a so-called non-monotone target set for (G,Ο„)(G,\tau) if there is some t0t_0 such that Xt=V(G)X_t=V(G) for every tβ‰₯t0t\geq t_0. Ben-Zwi, Hermelin, Lokshtanov, and Newman [Discrete Optimization 8 (2011) 87-96] asked whether a target set of minimum order can be determined efficiently if GG is a tree. We answer their question in the affirmative for threshold functions Ο„\tau satisfying Ο„(u)∈{0,1,dG(u)}\tau(u)\in \{ 0,1,d_G(u)\} for every vertex~uu. For such restricted threshold functions, we give a characterization of target sets that allows to show that the minimum target set problem remains NP-hard for planar graphs of maximum degree 33 but is efficiently solvable for graphs of bounded treewidth
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