911 research outputs found

    Decycling a graph by the removal of a matching: new algorithmic and structural aspects in some classes of graphs

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    A graph GG is {\em matching-decyclable} if it has a matching MM such that GMG-M is acyclic. Deciding whether GG is matching-decyclable is an NP-complete problem even if GG is 2-connected, planar, and subcubic. In this work we present results on matching-decyclability in the following classes: Hamiltonian subcubic graphs, chordal graphs, and distance-hereditary graphs. In Hamiltonian subcubic graphs we show that deciding matching-decyclability is NP-complete even if there are exactly two vertices of degree two. For chordal and distance-hereditary graphs, we present characterizations of matching-decyclability that lead to O(n)O(n)-time recognition algorithms

    Hamilton cycles in almost distance-hereditary graphs

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    Let GG be a graph on n3n\geq 3 vertices. A graph GG is almost distance-hereditary if each connected induced subgraph HH of GG has the property dH(x,y)dG(x,y)+1d_{H}(x,y)\leq d_{G}(x,y)+1 for any pair of vertices x,yV(H)x,y\in V(H). A graph GG is called 1-heavy (2-heavy) if at least one (two) of the end vertices of each induced subgraph of GG isomorphic to K1,3K_{1,3} (a claw) has (have) degree at least n/2n/2, and called claw-heavy if each claw of GG has a pair of end vertices with degree sum at least nn. Thus every 2-heavy graph is claw-heavy. In this paper we prove the following two results: (1) Every 2-connected, claw-heavy and almost distance-hereditary graph is Hamiltonian. (2) Every 3-connected, 1-heavy and almost distance-hereditary graph is Hamiltonian. In particular, the first result improves a previous theorem of Feng and Guo. Both results are sharp in some sense.Comment: 14 pages; 1 figure; a new theorem is adde

    Complexity of Token Swapping and its Variants

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    In the Token Swapping problem we are given a graph with a token placed on each vertex. Each token has exactly one destination vertex, and we try to move all the tokens to their destinations, using the minimum number of swaps, i.e., operations of exchanging the tokens on two adjacent vertices. As the main result of this paper, we show that Token Swapping is W[1]W[1]-hard parameterized by the length kk of a shortest sequence of swaps. In fact, we prove that, for any computable function ff, it cannot be solved in time f(k)no(k/logk)f(k)n^{o(k / \log k)} where nn is the number of vertices of the input graph, unless the ETH fails. This lower bound almost matches the trivial nO(k)n^{O(k)}-time algorithm. We also consider two generalizations of the Token Swapping, namely Colored Token Swapping (where the tokens have different colors and tokens of the same color are indistinguishable), and Subset Token Swapping (where each token has a set of possible destinations). To complement the hardness result, we prove that even the most general variant, Subset Token Swapping, is FPT in nowhere-dense graph classes. Finally, we consider the complexities of all three problems in very restricted classes of graphs: graphs of bounded treewidth and diameter, stars, cliques, and paths, trying to identify the borderlines between polynomial and NP-hard cases.Comment: 23 pages, 7 Figure

    The First Order Definability of Graphs with Separators via the Ehrenfeucht Game

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    We say that a first order formula Φ\Phi defines a graph GG if Φ\Phi is true on GG and false on every graph GG' non-isomorphic with GG. Let D(G)D(G) be the minimal quantifier rank of a such formula. We prove that, if GG is a tree of bounded degree or a Hamiltonian (equivalently, 2-connected) outerplanar graph, then D(G)=O(logn)D(G)=O(\log n), where nn denotes the order of GG. This bound is optimal up to a constant factor. If hh is a constant, for connected graphs with no minor KhK_h and degree O(n/logn)O(\sqrt n/\log n), we prove the bound D(G)=O(n)D(G)=O(\sqrt n). This result applies to planar graphs and, more generally, to graphs of bounded genus.Comment: 17 page

    Between Treewidth and Clique-width

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    Many hard graph problems can be solved efficiently when restricted to graphs of bounded treewidth, and more generally to graphs of bounded clique-width. But there is a price to be paid for this generality, exemplified by the four problems MaxCut, Graph Coloring, Hamiltonian Cycle and Edge Dominating Set that are all FPT parameterized by treewidth but none of which can be FPT parameterized by clique-width unless FPT = W[1], as shown by Fomin et al [7, 8]. We therefore seek a structural graph parameter that shares some of the generality of clique-width without paying this price. Based on splits, branch decompositions and the work of Vatshelle [18] on Maximum Matching-width, we consider the graph parameter sm-width which lies between treewidth and clique-width. Some graph classes of unbounded treewidth, like distance-hereditary graphs, have bounded sm-width. We show that MaxCut, Graph Coloring, Hamiltonian Cycle and Edge Dominating Set are all FPT parameterized by sm-width
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