7 results on '"W[1]-hard"'
Search Results
2. On the Parameterized Complexity of Relaxations of Clique
- Author
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Baril, Ambroise, Castillon, Antoine, Oijid, Nacim, Knowledge representation, reasonning (ORPAILLEUR), Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Graphes, AlgOrithmes et AppLications (GOAL), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Liris, Loria, CRIStAL, Knowledge representation, reasonning [ORPAILLEUR], Graphes, AlgOrithmes et AppLications [GOAL], Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL], Laboratoire d'InfoRmatique en Image et Systèmes d'information [LIRIS], and Université Claude Bernard Lyon 1 [UCBL]
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clique ,W[1]-hard ,γ-complete subgraph ,[INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC] ,s-club ,complexity ,s-clique ,[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO] - Abstract
We investigate the parameterized complexity of several problems formalizing cluster identification in graphs. In other words we ask whether a graph contains a large enough and sufficiently connected subgraph. We study here three relaxations of Clique: s-Club and s-Clique, in which the relaxation is focused on the distances in respectively the cluster and the original graph, and γ-Complete Subgraph in which the relaxation is made on the minimal degree in the cluster. As these three problems are known to be NP-hard, we study here their parameterized complexities. We prove that s-Club and s-Clique are NP-hard even restricted to graphs of degeneracy ≤ 3 whenever s ≥ 3, and to graphs of degeneracy ≤ 2 whenever s ≥ 5, which is a strictly stronger result than its W[1]-hardness parameterized by the degeneracy. We also obtain that these problems are solvable in polynomial time on graphs of degeneracy 1. Concerning γ-Complete Subgraph, we prove that it is W[1]-hard parameterized by both the degeneracy, which implies the W[1]-hardness parameterized by the number of vertices in the γ-complete-subgraph, and the number of elements outside the γ-complete subgraph.
- Published
- 2023
3. Tractability, hardness, and kernelization lower bound for and/or graph solution.
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dos Santos Souza, Uéverton and Protti, Fábio
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KERNEL functions , *MATHEMATICAL bounds , *GRAPH theory , *ARTIFICIAL intelligence , *DATA structures , *MATHEMATICAL optimization - Abstract
And/or graphs are well-known data structures with several applications in many fields of computer science, such as Artificial Intelligence, Distributed Systems, Software Engineering, and Operations Research. An and/or graph is an acyclic digraph G containing a single source vertex s , where every vertex v ∈ V ( G ) has a label f ( v ) ∈ { and,or }. In an and/or graph, (weighted) edges represent dependency relations between vertices: a vertex labeled and depends on all of its out-neighbors, while a vertex labeled or depends on only one of its out-neighbors. A solution subgraph H of an and/or graph G is a subdigraph of G containing its source vertex and such that if an and -vertex (resp. or -vertex) is included in H then all (resp. one) of its out-edges must also be included in H . In general, solution subgraphs represent feasible solutions of problems modeled by and/or graphs. The optimization problem associated with an and/or graph G consists of finding a minimum weight solution subgraph H of G , where the weight of a solution subgraph is the sum of the weights of its edges. Because of its wide applicability, in this work we develop a multivariate investigation of this optimization problem. In a previous paper (Souza et al., 2013) we have analyzed the complexity of such a problem under various aspects, including parameterized versions of it. However, the main open question has remained open: Is the problem of finding a solution subgraph of weight at most k (where k is the parameter) in FPT? In this paper we answer negatively to this question, proving the W[1]-hardness of the problem, and its W[P]-completeness when zero-weight edges are allowed. We also show that the problem is fixed-parameter tractable when parameterized by the tree-width, but it is W[SAT]-hard with respect to the clique-width and k as aggregated parameters. In addition, we show that when the out-edges of each or -vertex have all the same weight (a condition very common in practice), the problem becomes fixed-parameter tractable by the clique-width. Finally, using a framework developed by Bodlaender et al . (2009) and Fortnow and Santhanam (2011), based upon the notion of compositionality, we show that the tractable cases do not admit a polynomial kernel unless NP ⊆ coNP∕poly , even restricted to instances without or -vertices with out-degree greater than two. [ABSTRACT FROM AUTHOR]
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- 2017
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4. Width Parameterizations for Knot-Free Vertex Deletion on Digraphs
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Stéphane Bessy and Marin Bougeret and Alan D. A. Carneiro and Fábio Protti and Uéverton S. Souza, Bessy, Stéphane, Bougeret, Marin, Carneiro, Alan D. A., Protti, Fábio, Souza, Uéverton S., Stéphane Bessy and Marin Bougeret and Alan D. A. Carneiro and Fábio Protti and Uéverton S. Souza, Bessy, Stéphane, Bougeret, Marin, Carneiro, Alan D. A., Protti, Fábio, and Souza, Uéverton S.
- Abstract
A knot in a directed graph G is a strongly connected subgraph Q of G with at least two vertices, such that no vertex in V(Q) is an in-neighbor of a vertex in V(G)\V(Q). Knots are important graph structures, because they characterize the existence of deadlocks in a classical distributed computation model, the so-called OR-model. Deadlock detection is correlated with the recognition of knot-free graphs as well as deadlock resolution is closely related to the Knot-Free Vertex Deletion (KFVD) problem, which consists of determining whether an input graph G has a subset S subseteq V(G) of size at most k such that G[V\S] contains no knot. Because of natural applications in deadlock resolution, KFVD is closely related to Directed Feedback Vertex Set. In this paper we focus on graph width measure parameterizations for KFVD. First, we show that: (i) KFVD parameterized by the size of the solution k is W[1]-hard even when p, the length of a longest directed path of the input graph, as well as kappa, its Kenny-width, are bounded by constants, and we remark that KFVD is para-NP-hard even considering many directed width measures as parameters, but in FPT when parameterized by clique-width; (ii) KFVD can be solved in time 2^{O(tw)} x n, but assuming ETH it cannot be solved in 2^{o(tw)} x n^{O(1)}, where tw is the treewidth of the underlying undirected graph. Finally, since the size of a minimum directed feedback vertex set (dfv) is an upper bound for the size of a minimum knot-free vertex deletion set, we investigate parameterization by dfv and we show that (iii) KFVD can be solved in FPT-time parameterized by either dfv+kappa or dfv+p. Results of (iii) cannot be improved when replacing dfv by k due to (i).
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- 2019
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5. Parameterized Complexity of Conflict-Free Matchings and Paths
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Akanksha Agrawal and Pallavi Jain and Lawqueen Kanesh and Saket Saurabh, Agrawal, Akanksha, Jain, Pallavi, Kanesh, Lawqueen, Saurabh, Saket, Akanksha Agrawal and Pallavi Jain and Lawqueen Kanesh and Saket Saurabh, Agrawal, Akanksha, Jain, Pallavi, Kanesh, Lawqueen, and Saurabh, Saket
- Abstract
An input to a conflict-free variant of a classical problem Gamma, called Conflict-Free Gamma, consists of an instance I of Gamma coupled with a graph H, called the conflict graph. A solution to Conflict-Free Gamma in (I,H) is a solution to I in Gamma, which is also an independent set in H. In this paper, we study conflict-free variants of Maximum Matching and Shortest Path, which we call Conflict-Free Matching (CF-Matching) and Conflict-Free Shortest Path (CF-SP), respectively. We show that both CF-Matching and CF-SP are W[1]-hard, when parameterized by the solution size. Moreover, W[1]-hardness for CF-Matching holds even when the input graph where we want to find a matching is itself a matching, and W[1]-hardness for CF-SP holds for conflict graph being a unit-interval graph. Next, we study these problems with restriction on the conflict graphs. We give FPT algorithms for CF-Matching when the conflict graph is chordal. Also, we give FPT algorithms for both CF-Matching and CF-SP, when the conflict graph is d-degenerate. Finally, we design FPT algorithms for variants of CF-Matching and CF-SP, where the conflicting conditions are given by a (representable) matroid.
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- 2019
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6. Ruling out FPT algorithms for Weighted Coloring on forests
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Júlio Araújo, Julien Baste, Ignasi Sau, Universidade Federal do Ceará = Federal University of Ceará (UFC), Algorithmes, Graphes et Combinatoire (ALGCO), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), ANR-16-CE40-0028,DE-MO-GRAPH,Décomposition de Modèles Graphiques(2016), Universidade Federal do Ceará ( UFC ), Algorithmes, Graphes et Combinatoire ( ALGCO ), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier ( LIRMM ), and Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS )
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FOS: Computer and information sciences ,[ MATH ] Mathematics [math] ,Weight function ,General Computer Science ,Minimum weight ,Parameterized complexity ,0102 computer and information sciences ,02 engineering and technology ,G.2.2 ,Computational Complexity (cs.CC) ,01 natural sciences ,Theoretical Computer Science ,Combinatorics ,W[1]-hard ,020204 information systems ,Computer Science - Data Structures and Algorithms ,FOS: Mathematics ,0202 electrical engineering, electronic engineering, information engineering ,Discrete Mathematics and Combinatorics ,Partition (number theory) ,Mathematics - Combinatorics ,Data Structures and Algorithms (cs.DS) ,[MATH]Mathematics [math] ,ComputingMilieux_MISCELLANEOUS ,Mathematics ,parameterized complexity ,Connected component ,Discrete mathematics ,forests ,Exponential time hypothesis ,Applied Mathematics ,05 social sciences ,max-coloring ,050301 education ,F.2.2 ,Graph ,Computer Science - Computational Complexity ,05C15 ,010201 computation theory & mathematics ,Combinatorics (math.CO) ,weighted coloring ,0503 education ,Algorithm - Abstract
Given a graph $G$, a proper $k$-coloring of $G$ is a partition $c = (S_i)_{i\in [1,k]}$ of $V(G)$ into $k$ stable sets $S_1,\ldots, S_{k}$. Given a weight function $w: V(G) \to \mathbb{R}^+$, the weight of a color $S_i$ is defined as $w(i) = \max_{v \in S_i} w(v)$ and the weight of a coloring $c$ as $w(c) = \sum_{i=1}^{k}w(i)$. Guan and Zhu [Inf. Process. Lett., 1997] defined the weighted chromatic number of a pair $(G,w)$, denoted by $\sigma(G,w)$, as the minimum weight of a proper coloring of $G$. For a positive integer $r$, they also defined $\sigma(G,w;r)$ as the minimum of $w(c)$ among all proper $r$-colorings $c$ of $G$. The complexity of determining $\sigma(G,w)$ when $G$ is a tree was open for almost 20 years, until Ara\'ujo et al. [SIAM J. Discrete Math., 2014] recently proved that the problem cannot be solved in time $n^{o(\log n)}$ on $n$-vertex trees unless the Exponential Time Hypothesis (ETH) fails. The objective of this article is to provide hardness results for computing $\sigma(G,w)$ and $\sigma(G,w;r)$ when $G$ is a tree or a forest, relying on complexity assumptions weaker than the ETH. Namely, we study the problem from the viewpoint of parameterized complexity, and we assume the weaker hypothesis $FPT \neq W[1]$. Building on the techniques of Ara\'ujo et al., we prove that when $G$ is a forest, computing $\sigma(G,w)$ is $W[1]$-hard parameterized by the size of a largest connected component of $G$, and that computing $\sigma(G,w;r)$ is $W[2]$-hard parameterized by $r$. Our results rule out the existence of $FPT$ algorithms for computing these invariants on trees or forests for many natural choices of the parameter., Comment: 14 pages, 4 figures
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- 2018
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7. Routing with Congestion in Acyclic Digraphs
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Saeed Akhoondian Amiri and Stephan Kreutzer and Dániel Marx and Roman Rabinovich, Amiri, Saeed Akhoondian, Kreutzer, Stephan, Marx, Dániel, Rabinovich, Roman, Saeed Akhoondian Amiri and Stephan Kreutzer and Dániel Marx and Roman Rabinovich, Amiri, Saeed Akhoondian, Kreutzer, Stephan, Marx, Dániel, and Rabinovich, Roman
- Abstract
We study the version of the k-disjoint paths problem where k demand pairs (s_1,t_1), ..., (s_k,t_k) are specified in the input and the paths in the solution are allowed to intersect, but such that no vertex is on more than c paths. We show that on directed acyclic graphs the problem is solvable in time n^{O(d)} if we allow congestion k-d for k paths. Furthermore, we show that, under a suitable complexity theoretic assumption, the problem cannot be solved in time f(k)n^{o(d*log(d))} for any computable function f.
- Published
- 2016
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