We study the parameterized and classical complexity of two problems that are concerned with induced paths on three vertices, called P(3)s, in undirected graphs G = ( V, E). In Strong Triadic Closure we aim to label th...
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We study the parameterized and classical complexity of two problems that are concerned with induced paths on three vertices, called P(3)s, in undirected graphs G = ( V, E). In Strong Triadic Closure we aim to label the edges in E as strong and weak such that at most k edges are weak and G contains no induced P-3 with two strong edges. In Cluster Deletion we aim to destroy all induced P3s by a minimum number of edge deletions. We first show that Strong Triadic Closure admits a 4k-vertex kernel. Then, we study parameterization by l := |E|- k and show that both problems are fixed-parameter tractable and unlikely to admit a polynomial kernel with respect to l. Finally, we give a dichotomy of the classical complexity of both problems on H-free graphs for all H of order at most four.
We study a variant of the problem of finding a collection of disjoint s-clubs in a given network. Given a graph, the problem asks whether there exists a collection of at most r disjoint s-clubs that covers at least k ...
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We study a variant of the problem of finding a collection of disjoint s-clubs in a given network. Given a graph, the problem asks whether there exists a collection of at most r disjoint s-clubs that covers at least k vertices of the network. An s-club is a connected graph that has diameter bounded by s, for a positive integer s. We demand that each club is non-trivial, that is it has order at least t >= 2, for some positive integer t. We prove that the problem is APX-hard even when the input graph has bounded degree, s = 2, t = 3 and r = vertical bar V vertical bar. Moreover, we show that the problem is polynomial-time solvable when s >= 4, t = 3 and r = vertical bar V vertical bar, and when s >= 3, t = 2 and r = vertical bar V vertical bar. Finally, for s >= 2, we present a fixed-parameter algorithm for the problem, when parameterized by the number of covered vertices. (C) 2019 Elsevier B.V. All rights reserved.
We study the one-player game SPIRAL GALAXIES from an algorithmic viewpoint. SPIRAL GALAXIES has been shown to be NP-hard [6] more than a decade ago, but so far it seems that no one has dared exploring its algorithmic ...
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We study the one-player game SPIRAL GALAXIES from an algorithmic viewpoint. SPIRAL GALAXIES has been shown to be NP-hard [6] more than a decade ago, but so far it seems that no one has dared exploring its algorithmic universe. We take this trip and visit some of its corners. (C) 2015 Elsevier B.V. All rights reserved.
We give an analog of the Myhill-Nerode theorem from formal language theory for hypergraphs and use it to derive the following results for two NP-hard hypergraph problems. (1) We provide an algorithm for testing whethe...
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We give an analog of the Myhill-Nerode theorem from formal language theory for hypergraphs and use it to derive the following results for two NP-hard hypergraph problems. (1) We provide an algorithm for testing whether a hypergraph has cutwidth at most that runs in linear time for constant . In terms of parameterized complexity theory, the problem is fixed-parameter linear parameterized by . (2) We show that it is not expressible in monadic second-order logic whether a hypergraph has bounded (fractional, generalized) hypertree width. The proof leads us to conjecture that, in terms of parameterized complexity theory, these problems are W[1]-hard parameterized by the incidence treewidth (the treewidth of the incidence graph). Thus, in the form of the Myhill-Nerode theorem for hypergraphs, we obtain a method to derive linear-time algorithms and to obtain indicators for intractability for hypergraph problems parameterized by incidence treewidth.
We develop a framework for applying treewidth-based dynamic programming on graphs with "hybrid structure", i.e., with parts that may not have small treewidth but instead possess other structural properties. ...
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We develop a framework for applying treewidth-based dynamic programming on graphs with "hybrid structure", i.e., with parts that may not have small treewidth but instead possess other structural properties. Informally, this is achieved by defining a refinement of treewidth which only considers parts of the graph that do not belong to a pre-specified tractable graph class. Our approach allows us to not only generalize existing fixed-parameter algorithms exploiting treewidth, but also fixed-parameter algorithms which use the size of a modulator as their parameter. As the flagship application of our framework, we obtain a parameter that combines treewidth and rank-width to obtain fixed-parameter algorithms for CHROMATIC NUMBER, HAMILTONIAN CYCLE, and MAX-CUT. (C) 2021 The Author(s). Published by Elsevier Inc.
This paper presents a fixed-parameter algorithm for the tree edit distance problem for unordered trees under the unit cost model that works in O(2.62(k) . poly(n)) time and O(n(2)) space, where the parameter k is the ...
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This paper presents a fixed-parameter algorithm for the tree edit distance problem for unordered trees under the unit cost model that works in O(2.62(k) . poly(n)) time and O(n(2)) space, where the parameter k is the maximum bound of the edit distance and n is the maximum size of input trees. This paper also presents polynomial-time algorithms for the case where the maximum degree of the largest common subtree is bounded by a constant. (c) 2010 Elsevier B.V. All rights reserved.
A graph G is a (Pi(A), Pi(B))-graph if v(G) can be bipartitioned into A and B such that G[A] satisfies property Pi(A) and G[B] satisfies property Pi(B). The (Pi(A), Pi(B))-RECOGNITION problem is to recognize whether a...
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A graph G is a (Pi(A), Pi(B))-graph if v(G) can be bipartitioned into A and B such that G[A] satisfies property Pi(A) and G[B] satisfies property Pi(B). The (Pi(A), Pi(B))-RECOGNITION problem is to recognize whether a given graph is a (Pi(A), Pi(B))-graph. There are many (Pi(A), Pi(B))-RECOGNITION problems, including the recognition problems for bipartite, split, and unipolar graphs. We present efficient algorithms for many cases of (Pi(A), Pi(B))-RECOGNITION based on a technique which we dub inductive recognition. In particular, we give fixed-parameter algorithms for two NP-hard (Pi(A), Pi(B))-RECOGNITION problems, MONOPOLAR RECOGNITION and 2-SUBCOLORING, parameterized by the number of maximal cliques in G[A]. We complement our algorithmic results with several hardness results for (Pi(A),Pi(B))-RECOGNITION. (C) 2017 Elsevier Inc. All rights reserved.
The haplotyping problem has emerged in recent years as one of the most relevant problems in Computational Biology. In particular, in the Single Individual Haplotyping (SIN) problem, starting from a matrix of incomplet...
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The haplotyping problem has emerged in recent years as one of the most relevant problems in Computational Biology. In particular, in the Single Individual Haplotyping (SIN) problem, starting from a matrix of incomplete haplotype fragments, the goal is the reconstruction of the two complete haplotypes of an individual. In this paper we consider one of the variants of the Single Individual Haplotyping problem, the Longest Haplotyping Reconstruction (LHR) problem. We prove that the LHR problem is NP-hard even in the restricted case when the input matrix is error-free. Furthermore, we investigate the approximation complexity of the problem, and we show that the problem cannot be approximated within factor 2(log8) (nm) for any constant delta < 1, unless NP subset of DTIME vertical bar 2(poly) (log) (nm)vertical bar. Finally, we exhibit a fixed-parameter algorithm for the LHR problem, where the parameter is the size of the two reconstructed haplotypes. (C) 2011 Elsevier B.V. All rights reserved.
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...
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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 is an element of {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 give a simple fixed-parameter algorithm that tests in O*(2(k)) 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*(1.9999992(k)) for spanning trees and O*((root 3)(k)) for s-t paths and cycles. For spanning trees we also have an O*(1.968k)-time Monte-Carlo algorithm. Each. O*(beta(k))-time decision algorithm can be turned into an O*((beta + 1)(k))-time optimization algorithm that computes a configuration with the minimum number of crossings. (c) 2006 Elsevier B.V. All rights reserved.
Computational methods for inferring haplotype information from genotype data are used in studying the association between genomic variation and medical condition. Recently, Gusfield proposed a haplotype inference meth...
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Computational methods for inferring haplotype information from genotype data are used in studying the association between genomic variation and medical condition. Recently, Gusfield proposed a haplotype inference method that is based on perfect phylogeny principles. A fundamental problem arises when one tries to apply this approach in the presence of missing genotype data, which is common in practice. We show that the resulting theoretical problem is NP-hard even in very restricted cases. To cope with missing data, we introduce a variant of haplotyping via perfect phylogeny in which a path phylogeny is Sought. Searching for perfect path phylogenies is strongly motivated by the characteristics of human genotype data: 70% of real instances that admit a perfect phylogeny also admit a perfect path phylogeny. Our main result is a fixed-parameter algorithm for haplotyping with missing data via perfect path phylogenies. We also present a simple linear-time algorithm for the problem on complete data. (c) 2006 Elsevier B.V. All rights reserved.
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