45 research outputs found

    The PACE 2022 Parameterized Algorithms and Computational Experiments Challenge: Directed Feedback Vertex Set

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    The PACE 2022 Parameterized Algorithms and Computational Experiments Challenge: Directed Feedback Vertex Set

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    The Parameterized Algorithms and Computational Experiments challenge (PACE) 2022 was devoted to engineer algorithms solving the NP-hard Directed Feedback Vertex Set (DFVS) problem. The DFVS problem is to find a minimum subset XVX ⊆ V in a given directed graph G=(V,E)G = (V,E) such that, when all vertices of XX and their adjacent edges are deleted from GG, the remainder is acyclic. Overall, the challenge had 90 participants from 26 teams, 12 countries, and 3 continents that submitted their implementations to this year’s competition. In this report, we briefly describe the setup of the challenge, the selection of benchmark instances, as well as the ranking of the participating teams. We also briefly outline the approaches used in the submitted solvers

    Linear MIM-Width of Trees

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    We provide an O(nlogn)O(n \log n) algorithm computing the linear maximum induced matching width of a tree and an optimal layout.Comment: 19 pages, 7 figures, full version of WG19 paper of same nam

    Tight bounds for planar strongly connected Steiner subgraph with fixed number of terminals (and extensions)

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    (see paper for full abstract) Given a vertex-weighted directed graph G=(V,E)G=(V,E) and a set T={t1,t2,tk}T=\{t_1, t_2, \ldots t_k\} of kk terminals, the objective of the SCSS problem is to find a vertex set HVH\subseteq V of minimum weight such that G[H]G[H] contains a titjt_{i}\rightarrow t_j path for each iji\neq j. The problem is NP-hard, but Feldman and Ruhl [FOCS '99; SICOMP '06] gave a novel nO(k)n^{O(k)} algorithm for the SCSS problem, where nn is the number of vertices in the graph and kk is the number of terminals. We explore how much easier the problem becomes on planar directed graphs: - Our main algorithmic result is a 2O(k)nO(k)2^{O(k)}\cdot n^{O(\sqrt{k})} algorithm for planar SCSS, which is an improvement of a factor of O(k)O(\sqrt{k}) in the exponent over the algorithm of Feldman and Ruhl. - Our main hardness result is a matching lower bound for our algorithm: we show that planar SCSS does not have an f(k)no(k)f(k)\cdot n^{o(\sqrt{k})} algorithm for any computable function ff, unless the Exponential Time Hypothesis (ETH) fails. The following additional results put our upper and lower bounds in context: - In general graphs, we cannot hope for such a dramatic improvement over the nO(k)n^{O(k)} algorithm of Feldman and Ruhl: assuming ETH, SCSS in general graphs does not have an f(k)no(k/logk)f(k)\cdot n^{o(k/\log k)} algorithm for any computable function ff. - Feldman and Ruhl generalized their nO(k)n^{O(k)} algorithm to the more general Directed Steiner Network (DSN) problem; here the task is to find a subgraph of minimum weight such that for every source sis_i there is a path to the corresponding terminal tit_i. We show that, assuming ETH, there is no f(k)no(k)f(k)\cdot n^{o(k)} time algorithm for DSN on acyclic planar graphs.Comment: To appear in SICOMP. Extended abstract in SODA 2014. This version has a new author (Andreas Emil Feldmann), and the algorithm is faster and considerably simplified as compared to conference versio

    Parameterizing the permanent: Hardness for fixed excluded minors

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    Parameterized Inapproximability of Independent Set in HH-Free Graphs

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    We study the Independent Set (IS) problem in HH-free graphs, i.e., graphs excluding some fixed graph HH as an induced subgraph. We prove several inapproximability results both for polynomial-time and parameterized algorithms. Halld\'orsson [SODA 1995] showed that for every δ>0\delta>0 IS has a polynomial-time (d12+δ)(\frac{d-1}{2}+\delta)-approximation in K1,dK_{1,d}-free graphs. We extend this result by showing that Ka,bK_{a,b}-free graphs admit a polynomial-time O(α(G)11/a)O(\alpha(G)^{1-1/a})-approximation, where α(G)\alpha(G) is the size of a maximum independent set in GG. Furthermore, we complement the result of Halld\'orsson by showing that for some γ=Θ(d/logd),\gamma=\Theta(d/\log d), there is no polynomial-time γ\gamma-approximation for these graphs, unless NP = ZPP. Bonnet et al. [IPEC 2018] showed that IS parameterized by the size kk of the independent set is W[1]-hard on graphs which do not contain (1) a cycle of constant length at least 44, (2) the star K1,4K_{1,4}, and (3) any tree with two vertices of degree at least 33 at constant distance. We strengthen this result by proving three inapproximability results under different complexity assumptions for almost the same class of graphs (we weaken condition (2) that GG does not contain K1,5K_{1,5}). First, under the ETH, there is no f(k)no(k/logk)f(k)\cdot n^{o(k/\log k)} algorithm for any computable function ff. Then, under the deterministic Gap-ETH, there is a constant δ>0\delta>0 such that no δ\delta-approximation can be computed in f(k)nO(1)f(k) \cdot n^{O(1)} time. Also, under the stronger randomized Gap-ETH there is no such approximation algorithm with runtime f(k)no(k)f(k)\cdot n^{o(k)}. Finally, we consider the parameterization by the excluded graph HH, and show that under the ETH, IS has no no(α(H))n^{o(\alpha(H))} algorithm in HH-free graphs and under Gap-ETH there is no d/ko(1)d/k^{o(1)}-approximation for K1,dK_{1,d}-free graphs with runtime f(d,k)nO(1)f(d,k) n^{O(1)}.Comment: Preliminary version of the paper in WG 2020 proceeding

    Maximum Independent Set when excluding an induced minor: K1+tK2K_1 + tK_2 and tC3C4tC_3 \uplus C_4

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    Dallard, Milani\v{c}, and \v{S}torgel [arXiv '22] ask if for every class excluding a fixed planar graph HH as an induced minor, Maximum Independent Set can be solved in polynomial time, and show that this is indeed the case when HH is any planar complete bipartite graph, or the 5-vertex clique minus one edge, or minus two disjoint edges. A positive answer would constitute a far-reaching generalization of the state-of-the-art, when we currently do not know if a polynomial-time algorithm exists when HH is the 7-vertex path. Relaxing tractability to the existence of a quasipolynomial-time algorithm, we know substantially more. Indeed, quasipolynomial-time algorithms were recently obtained for the tt-vertex cycle, CtC_t [Gartland et al., STOC '21] and the disjoint union of tt triangles, tC3tC_3 [Bonamy et al., SODA '23]. We give, for every integer tt, a polynomial-time algorithm running in nO(t5)n^{O(t^5)} when HH is the friendship graph K1+tK2K_1 + tK_2 (tt disjoint edges plus a vertex fully adjacent to them), and a quasipolynomial-time algorithm running in nO(t2logn)+tO(1)n^{O(t^2 \log n)+t^{O(1)}} when HH is tC3C4tC_3 \uplus C_4 (the disjoint union of tt triangles and a 4-vertex cycle). The former extends a classical result on graphs excluding tK2tK_2 as an induced subgraph [Alekseev, DAM '07], while the latter extends Bonamy et al.'s result.Comment: 15 pages, 2 figure

    Maximum Independent Set When Excluding an Induced Minor: K? + tK? and tC? ? C?

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