The class of GAlled-Tree Explainable (GATEx) graphs has recently been discovered as a natural generalization of cographs. Cographs are precisely those graphs that can be uniquely represented by a rooted tree where the...
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The class of GAlled-Tree Explainable (GATEx) graphs has recently been discovered as a natural generalization of cographs. Cographs are precisely those graphs that can be uniquely represented by a rooted tree where the leaves correspond to the vertices of the graph. As a generalization, GATEx graphs are precisely those that can be uniquely represented by a particular rooted acyclic network, called a galled-tree. This paper explores the use of galled-trees to solve combinatorial problems on GATEx graphs that are, in general, NP-hard. We demonstrate that finding a maximum clique, an optimal vertex coloring, a perfect order, as well as a maximum independent set in GATEx graphs can be efficiently done in lineartime. The key idea behind the linear-time algorithms is to utilize the galled-trees that explain the GATEx graphs as a guide for computing the respective cliques, colorings, perfect orders, or independent sets.
The maximum cut problem in graphs and its generalizations are fundamental combinatorial problems. Several of these cut problems were recently shown to be fixed-parameter tractable and admit polynomial kernels when par...
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The maximum cut problem in graphs and its generalizations are fundamental combinatorial problems. Several of these cut problems were recently shown to be fixed-parameter tractable and admit polynomial kernels when parameterized above the tight lower bound measured by the size and order of the graph. In this paper we continue this line of research and considerably improve several of those results:We show that an algorithm by Crowston et al. (Algorithmica 72(3):734-757, 2015) for (Signed) Max-Cut Above Edwards-Erd A s Bound can be implemented so as to run in lineartime;this significantly improves the previous analysis with run time . We give an asymptotically optimal kernel for (Signed) Max-Cut Above Edwards-Erd A s Bound with O(k) vertices, improving a kernel with vertices by Crowston et al. (Theor Comput Sci 513:53-64, 2013). We improve all known kernels for parameterizations above strongly -extendible properties (a generalization of the Max-Cut results) by Crowston et al. (Proceedings of FSTTCS 2013, Leibniz international proceedings in informatics, Guwahati, 2013) from vertices to O(k) vertices. Therefore, Max Acyclic Subdigraph parameterized above Poljak-Turzik bound admits a kernel with O(k) vertices and can be solved in time;this answers an open question by Crowston et al. (Proceedings of FSTTCS 2012, Leibniz international proceedings in informatics, Hyderabad, 2012).
A connected graph is distance-hereditary if any two vertices have the same distance in all of its connected induced subgraphs. This paper proposes a unified method for designing linear-time algorithms for counting ind...
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A connected graph is distance-hereditary if any two vertices have the same distance in all of its connected induced subgraphs. This paper proposes a unified method for designing linear-time algorithms for counting independent sets and their two variants, independent dominating sets and independent perfect dominating sets, in distance-hereditary graphs. (C) 2017 Elsevier B.V. All rights reserved.
A planar orthogonal drawing of a planar 4-graph G (i.e., a planar graph with vertex-degree at most four) is a crossing-free drawing that maps each vertex of G to a distinct point of the plane and each edge of G to a p...
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A planar orthogonal drawing of a planar 4-graph G (i.e., a planar graph with vertex-degree at most four) is a crossing-free drawing that maps each vertex of G to a distinct point of the plane and each edge of G to a polygonal chain consisting of horizontal and vertical segments. A longstanding open question in Graph Drawing, dating back over 30 years, is whether there exists a linear-time algorithm to compute an orthogonal drawing of a plane 4-graph with the minimum number of bends. The term "plane" indicates that the input graph comes together with a planar embedding, which must be preserved by the drawing (i.e., the drawing must have the same set of faces as the input graph). In this paper we positively answer the question above for the widely-studied class of series-parallel graphs. Our linear-time algorithm is based on a characterization of the planar series-parallel graphs that admit an orthogonal drawing without bends. This characterization is given in terms of the orthogonal spirality that each type of triconnected component of the graph can take;the orthogonal spirality of a component measures how much that component is "rolled-up" in an orthogonal drawing of the graph.
Software watermarking involves integrating an identifier within the software, enabling timely retrieval to disclose authorship/ownership, and deter piracy. Various software watermarking schemes have been proposed in t...
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Suppose that we are given a positive integer k, and a k-(vertex-)colouring f 0 of a given graph G. Then we are asked to find a colouring of G using the minimum number of colours among colourings that are reachable fro...
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Suppose that we are given a positive integer k, and a k-(vertex-)colouring f 0 of a given graph G. Then we are asked to find a colouring of G using the minimum number of colours among colourings that are reachable from f 0 by iteratively changing a colour assignment of exactly one vertex while maintaining the property of k-colourings. In this paper, we give linear-time algorithms to solve the problem for graphs of degeneracy at most two and for the case where k = 3 . These results imply linear-time algorithms for series-parallel graphs and grid graphs. In addition, we give linear-time algorithms for chordal graphs and cographs. On the other hand, we show that, for any k = 4 , this problem remains NP-hard for planar graphs with degeneracy three and maximum degree four. Thus, we obtain a complexity dichotomy for this problem with respect to the degeneracy of a graph and the number k of colours.
Phylogenetic networks are used to represent evolutionary scenarios in biology and linguistics. To find the most probable scenario, it may be necessary to compare candidate networks. In particular, one needs to disting...
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Phylogenetic networks are used to represent evolutionary scenarios in biology and linguistics. To find the most probable scenario, it may be necessary to compare candidate networks. In particular, one needs to distinguish different networks and determine whether one network is contained in another. In this paper, we introduce cherry-picking networks, a class of networks that can be reduced by a so-called cherry-picking sequence. We then show how to compare such networks using their sequences. We characterize reconstructible cherry-picking networks, which are the networks that are uniquely determined by the sequences that reduce them, making them distinguishable. Furthermore, we show that a cherry-picking network is contained in another cherry picking network if a sequence for the latter network reduces the former network, provided both networks can be reconstructed from their sequences in a similar way (i.e., they are in the same reconstructible class). Lastly, we show that the converse of the above statement holds for tree-child networks, thereby showing that NETWORK CONTAINMENT, the problem of checking whether a network is contained in another, can be solved by computing cherry picking sequences in lineartime for tree-child networks. (C) 2020 The Author(s). Published by Elsevier B.V.
Finding maximum-cardinality matchings in undirected graphs is arguably one of the most central graph primitives. For m-edge and n-vertex graphs, it is well-known to be solvable in O(m root n) time;however, for several...
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Finding maximum-cardinality matchings in undirected graphs is arguably one of the most central graph primitives. For m-edge and n-vertex graphs, it is well-known to be solvable in O(m root n) time;however, for several applications this running time is still too slow. We investigate how linear-time (and almost linear-time) data reduction (used as preprocessing) can alleviate the situation. More specifically, we focus on linear-time kernelization. We start a deeper and systematic study both for general graphs and for bipartite graphs. Our data reduction algorithms easily comply (in form of preprocessing) with every solution strategy (exact, approximate, heuristic), thus making them attractive in various settings.
We consider a problem in computational origami. Given a piece of paper as a convex polygon P and a point f located within, we fold every point on a boundary of P to f and compute a region that is safe from folding, i....
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We consider a problem in computational origami. Given a piece of paper as a convex polygon P and a point f located within, we fold every point on a boundary of P to f and compute a region that is safe from folding, i.e., the region with no creases. This problem is an extended version of a problem by Akitaya, Ballinger, Demaine, Hull, and Schmidt that only folds corners of the polygon. To find the region, we prove structural properties of intersections of parabola-bounded regions and use them to devise a linear-time algorithm. We also prove a structural result regarding the complexity of the safe region as a variable of the location of point f, i.e., the number of arcs of the safe region can be determined using the straight skeleton of the polygon P.
A partition;= {V1, V2, ..., Vk} of the vertex set V of a graph G into k color classes Vi, with 1 < i < k is called a quorum coloring if for every vertex v is an element of V, at least half of the vertices in the...
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A partition;= {V1, V2, ..., Vk} of the vertex set V of a graph G into k color classes Vi, with 1 < i < k is called a quorum coloring if for every vertex v is an element of V, at least half of the vertices in the closed neighborhood N[v] of v have the same color as v. The maximum cardinality of a quorum coloring of G is called the quorum coloring number of G and is denoted by *q(G). A quorum coloring of order *q(G) is a *q-coloring. In this paper, we partially answer an open problem concerning quorum colorings of graphs. Namely, we improve a sharp lower bound given in 2012 by Eroh and Gera on the quorum coloring number of a nontrivial tree, and show that our new lower bound can be computed in lineartime. Moreover, we show that this bound is attained by all non trivial binary trees. (c) 2022 Elsevier B.V. All rights reserved.
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