29 research outputs found

    Graph Treewidth and Geometric Thickness Parameters

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    Consider a drawing of a graph GG in the plane such that crossing edges are coloured differently. The minimum number of colours, taken over all drawings of GG, is the classical graph parameter "thickness". By restricting the edges to be straight, we obtain the "geometric thickness". By further restricting the vertices to be in convex position, we obtain the "book thickness". This paper studies the relationship between these parameters and treewidth. Our first main result states that for graphs of treewidth kk, the maximum thickness and the maximum geometric thickness both equal k/2\lceil{k/2}\rceil. This says that the lower bound for thickness can be matched by an upper bound, even in the more restrictive geometric setting. Our second main result states that for graphs of treewidth kk, the maximum book thickness equals kk if k2k \leq 2 and equals k+1k+1 if k3k \geq 3. This refutes a conjecture of Ganley and Heath [Discrete Appl. Math. 109(3):215-221, 2001]. Analogous results are proved for outerthickness, arboricity, and star-arboricity.Comment: A preliminary version of this paper appeared in the "Proceedings of the 13th International Symposium on Graph Drawing" (GD '05), Lecture Notes in Computer Science 3843:129-140, Springer, 2006. The full version was published in Discrete & Computational Geometry 37(4):641-670, 2007. That version contained a false conjecture, which is corrected on page 26 of this versio

    Simple realizability of complete abstract topological graphs simplified

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    An abstract topological graph (briefly an AT-graph) is a pair A=(G,X)A=(G,\mathcal{X}) where G=(V,E)G=(V,E) is a graph and X(E2)\mathcal{X}\subseteq {E \choose 2} is a set of pairs of its edges. The AT-graph AA is simply realizable if GG can be drawn in the plane so that each pair of edges from X\mathcal{X} crosses exactly once and no other pair crosses. We show that simply realizable complete AT-graphs are characterized by a finite set of forbidden AT-subgraphs, each with at most six vertices. This implies a straightforward polynomial algorithm for testing simple realizability of complete AT-graphs, which simplifies a previous algorithm by the author. We also show an analogous result for independent Z2\mathbb{Z}_2-realizability, where only the parity of the number of crossings for each pair of independent edges is specified.Comment: 26 pages, 17 figures; major revision; original Section 5 removed and will be included in another pape

    Configurations with few crossings in topological graphs

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    AbstractIn this paper we study the problem of computing subgraphs of a certain configuration in a given topological graph G such that the number of crossings in the subgraph is minimum. The configurations that we consider are spanning trees, s–t paths, cycles, matchings, and κ-factors for κ∈{1,2}. We show that it is NP-hard to approximate the minimum number of crossings for these configurations within a factor of k1−ε for any ε>0, where k is the number of crossings in G.We then give a simple fixed-parameter algorithm that tests in O⋆(2k) time whether G has a crossing-free configuration for any of the above, where the O⋆-notation neglects polynomial terms. For some configurations we have faster algorithms. The respective running times are O⋆(1.9999992k) for spanning trees and O⋆((3)k) for s-t paths and cycles. For spanning trees we also have an O⋆(1.968k)-time Monte-Carlo algorithm. Each O⋆(βk)-time decision algorithm can be turned into an O⋆((β+1)k)-time optimization algorithm that computes a configuration with the minimum number of crossings

    String graphs. I. The number of critical nonstring graphs is infinite

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    AbstractString graphs (intersection graphs of curves in the plane) were originally studied in connection with RC-circuits. The family of string graphs is closed in the induced minor order, and so it is reasonable to study critical nonstring graphs (nonstring graphs such that all of their proper induced minors are string graphs). The question of whether there are infinitely many nonisomorphic critical nonstring graphs has been an open problem for some time. The main result of this paper settles this question. In a later paper of this series we show that recognizing string graphs is NP-hard

    Simultaneous Graph Embeddings with Fixed Edges

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    We study the problem of simultaneously embedding several graphs on the same vertex set in such a way that edges common to two or more graphs are represented by the same curve. This problem is known as simultaneously embedding graphs with fixed edges. We show that this problem is closely related to the weak realizability problem: Can a graph be drawn such that all edge crossings occur in a given set of edge pairs? By exploiting this relationship we can explain why the simultaneous embedding problem is challenging, both from a computational and a combinatorial point of view. More precisely, we prove that simultaneously embedding graphs with fixed edges is NP-complete even for three planar graphs. For two planar graphs the complexity status is still open

    Simultaneous Graph Embeddings with Fixed Edges

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    We study the problem of simultaneously embedding several graphs on the same vertex set in such a way that edges common to two or more graphs are represented by the same curve. This problem is known as simultaneously embedding graphs with fixed edges. We show that this problem is closely related to the weak realizability problem: Can a graph be drawn such that all edge crossings occur in a given set of edge pairs? By exploiting this relationship we can explain why the simultaneous embedding problem is challenging, both from a computational and a combinatorial point of view. More precisely, we prove that simultaneously embedding graphs with fixed edges is NP-complete even for three planar graphs. For two planar graphs the complexity status is still open

    The Complexity of Drawing Graphs on Few Lines and Few Planes

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    It is well known that any graph admits a crossing-free straight-line drawing in R3\mathbb{R}^3 and that any planar graph admits the same even in R2\mathbb{R}^2. For a graph GG and d{2,3}d \in \{2,3\}, let ρd1(G)\rho^1_d(G) denote the minimum number of lines in Rd\mathbb{R}^d that together can cover all edges of a drawing of GG. For d=2d=2, GG must be planar. We investigate the complexity of computing these parameters and obtain the following hardness and algorithmic results. - For d{2,3}d\in\{2,3\}, we prove that deciding whether ρd1(G)k\rho^1_d(G)\le k for a given graph GG and integer kk is R{\exists\mathbb{R}}-complete. - Since NPR\mathrm{NP}\subseteq{\exists\mathbb{R}}, deciding ρd1(G)k\rho^1_d(G)\le k is NP-hard for d{2,3}d\in\{2,3\}. On the positive side, we show that the problem is fixed-parameter tractable with respect to kk. - Since RPSPACE{\exists\mathbb{R}}\subseteq\mathrm{PSPACE}, both ρ21(G)\rho^1_2(G) and ρ31(G)\rho^1_3(G) are computable in polynomial space. On the negative side, we show that drawings that are optimal with respect to ρ21\rho^1_2 or ρ31\rho^1_3 sometimes require irrational coordinates. - Let ρ32(G)\rho^2_3(G) be the minimum number of planes in R3\mathbb{R}^3 needed to cover a straight-line drawing of a graph GG. We prove that deciding whether ρ32(G)k\rho^2_3(G)\le k is NP-hard for any fixed k2k \ge 2. Hence, the problem is not fixed-parameter tractable with respect to kk unless P=NP\mathrm{P}=\mathrm{NP}

    Configuations with few crossings in topological graphs

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    In this paper we study the problem of computing subgraphs of a certain configuration in a given topological graph G such that the number of crossings in the subgraph is minimum. The configurations that we consider are spanning trees, s-t paths, cycles, matchings, and kappa-factors for kappa in {1,2}. We show that it is NP-hard to approximate the minimum number of crossings for these configurations within a factor of k^(1-epsilon) for any epsilon > 0, where k is the number of crossings in G. We then show that the problems are fixed-parameter tractable if we use the number of crossings in the given graph as the parameter. Finally we present a mixed-integer linear program formulation for each problem and a simple but effective heuristic for spanning trees
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