2,543 research outputs found

    Optimality program in segment and string graphs

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    Planar graphs are known to allow subexponential algorithms running in time 2O(n)2^{O(\sqrt n)} or 2O(nlogn)2^{O(\sqrt n \log n)} for most of the paradigmatic problems, while the brute-force time 2Θ(n)2^{\Theta(n)} is very likely to be asymptotically best on general graphs. Intrigued by an algorithm packing curves in 2O(n2/3logn)2^{O(n^{2/3}\log n)} by Fox and Pach [SODA'11], we investigate which problems have subexponential algorithms on the intersection graphs of curves (string graphs) or segments (segment intersection graphs) and which problems have no such algorithms under the ETH (Exponential Time Hypothesis). Among our results, we show that, quite surprisingly, 3-Coloring can also be solved in time 2O(n2/3logO(1)n)2^{O(n^{2/3}\log^{O(1)}n)} on string graphs while an algorithm running in time 2o(n)2^{o(n)} for 4-Coloring even on axis-parallel segments (of unbounded length) would disprove the ETH. For 4-Coloring of unit segments, we show a weaker ETH lower bound of 2o(n2/3)2^{o(n^{2/3})} which exploits the celebrated Erd\H{o}s-Szekeres theorem. The subexponential running time also carries over to Min Feedback Vertex Set but not to Min Dominating Set and Min Independent Dominating Set.Comment: 19 pages, 15 figure

    Parameterized (in)approximability of subset problems

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    We discuss approximability and inapproximability in FPT-time for a large class of subset problems where a feasible solution SS is a subset of the input data and the value of SS is S|S|. The class handled encompasses many well-known graph, set, or satisfiability problems such as Dominating Set, Vertex Cover, Set Cover, Independent Set, Feedback Vertex Set, etc. In a first time, we introduce the notion of intersective approximability that generalizes the one of safe approximability and show strong parameterized inapproximability results for many of the subset problems handled. Then, we study approximability of these problems with respect to the dual parameter nkn-k where nn is the size of the instance and kk the standard parameter. More precisely, we show that under such a parameterization, many of these problems, while W[\cdot]-hard, admit parameterized approximation schemata.Comment: 7 page

    (Total) Vector Domination for Graphs with Bounded Branchwidth

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    Given a graph G=(V,E)G=(V,E) of order nn and an nn-dimensional non-negative vector d=(d(1),d(2),,d(n))d=(d(1),d(2),\ldots,d(n)), called demand vector, the vector domination (resp., total vector domination) is the problem of finding a minimum SVS\subseteq V such that every vertex vv in VSV\setminus S (resp., in VV) has at least d(v)d(v) neighbors in SS. The (total) vector domination is a generalization of many dominating set type problems, e.g., the dominating set problem, the kk-tuple dominating set problem (this kk is different from the solution size), and so on, and its approximability and inapproximability have been studied under this general framework. In this paper, we show that a (total) vector domination of graphs with bounded branchwidth can be solved in polynomial time. This implies that the problem is polynomially solvable also for graphs with bounded treewidth. Consequently, the (total) vector domination problem for a planar graph is subexponential fixed-parameter tractable with respectto kk, where kk is the size of solution.Comment: 16 page

    Complexity of Grundy coloring and its variants

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    The Grundy number of a graph is the maximum number of colors used by the greedy coloring algorithm over all vertex orderings. In this paper, we study the computational complexity of GRUNDY COLORING, the problem of determining whether a given graph has Grundy number at least kk. We also study the variants WEAK GRUNDY COLORING (where the coloring is not necessarily proper) and CONNECTED GRUNDY COLORING (where at each step of the greedy coloring algorithm, the subgraph induced by the colored vertices must be connected). We show that GRUNDY COLORING can be solved in time O(2.443n)O^*(2.443^n) and WEAK GRUNDY COLORING in time O(2.716n)O^*(2.716^n) on graphs of order nn. While GRUNDY COLORING and WEAK GRUNDY COLORING are known to be solvable in time O(2O(wk))O^*(2^{O(wk)}) for graphs of treewidth ww (where kk is the number of colors), we prove that under the Exponential Time Hypothesis (ETH), they cannot be solved in time O(2o(wlogw))O^*(2^{o(w\log w)}). We also describe an O(22O(k))O^*(2^{2^{O(k)}}) algorithm for WEAK GRUNDY COLORING, which is therefore \fpt for the parameter kk. Moreover, under the ETH, we prove that such a running time is essentially optimal (this lower bound also holds for GRUNDY COLORING). Although we do not know whether GRUNDY COLORING is in \fpt, we show that this is the case for graphs belonging to a number of standard graph classes including chordal graphs, claw-free graphs, and graphs excluding a fixed minor. We also describe a quasi-polynomial time algorithm for GRUNDY COLORING and WEAK GRUNDY COLORING on apex-minor graphs. In stark contrast with the two other problems, we show that CONNECTED GRUNDY COLORING is \np-complete already for k=7k=7 colors.Comment: 24 pages, 7 figures. This version contains some new results and improvements. A short paper based on version v2 appeared in COCOON'1

    Algorithms and almost tight results for 3-colorability of small diameter graphs.

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    The 3-coloring problem is well known to be NP-complete. It is also well known that it remains NP-complete when the input is restricted to graphs with diameter 4. Moreover, assuming the Exponential Time Hypothesis (ETH), 3-coloring cannot be solved in time 2o(n) on graphs with n vertices and diameter at most 4. In spite of extensive studies of the 3-coloring problem with respect to several basic parameters, the complexity status of this problem on graphs with small diameter, i.e. with diameter at most 2, or at most 3, has been an open problem. In this paper we investigate graphs with small diameter. For graphs with diameter at most 2, we provide the first subexponential algorithm for 3-coloring, with complexity 2O(nlogn√). Furthermore we extend the notion of an articulation vertex to that of an articulation neighborhood, and we provide a polynomial algorithm for 3-coloring on graphs with diameter 2 that have at least one articulation neighborhood. For graphs with diameter at most 3, we establish the complexity of 3-coloring by proving for every ε∈[0,1) that 3-coloring is NP-complete on triangle-free graphs of diameter 3 and radius 2 with n vertices and minimum degree δ=Θ(nε). Moreover, assuming ETH, we use three different amplification techniques of our hardness results, in order to obtain for every ε∈[0,1) subexponential asymptotic lower bounds for the complexity of 3-coloring on triangle-free graphs with diameter 3 and minimum degree δ=Θ(nε). Finally, we provide a 3-coloring algorithm with running time 2O(min{δΔ, nδlogδ}) for arbitrary graphs with diameter 3, where n is the number of vertices and δ (resp. Δ) is the minimum (resp. maximum) degree of the input graph. To the best of our knowledge, this is the first subexponential algorithm for graphs with δ=ω(1) and for graphs with δ=O(1) and Δ=o(n). Due to the above lower bounds of the complexity of 3-coloring, the running time of this algorithm is asymptotically almost tight when the minimum degree of the input graph is δ=Θ(nε), where ε∈[12,1), as its time complexity is 2O(nδlogδ)=2O(n1−εlogn) and the corresponding lower bound states that there is no 2o(n1−ε)-time algorithm
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