84 research outputs found

    On some simplicial elimination schemes for chordal graphs

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    We present here some results on particular elimination schemes for chordal graphs, namely we show that for any chordal graph we can construct in linear time a simplicial elimination scheme starting with a pending maximal clique attached via a minimal separator maximal (resp. minimal) under inclusion among all minimal separators

    On the Enumeration of Minimal Dominating Sets and Related Notions

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    A dominating set DD in a graph is a subset of its vertex set such that each vertex is either in DD or has a neighbour in DD. In this paper, we are interested in the enumeration of (inclusion-wise) minimal dominating sets in graphs, called the Dom-Enum problem. It is well known that this problem can be polynomially reduced to the Trans-Enum problem in hypergraphs, i.e., the problem of enumerating all minimal transversals in a hypergraph. Firstly we show that the Trans-Enum problem can be polynomially reduced to the Dom-Enum problem. As a consequence there exists an output-polynomial time algorithm for the Trans-Enum problem if and only if there exists one for the Dom-Enum problem. Secondly, we study the Dom-Enum problem in some graph classes. We give an output-polynomial time algorithm for the Dom-Enum problem in split graphs, and introduce the completion of a graph to obtain an output-polynomial time algorithm for the Dom-Enum problem in P6P_6-free chordal graphs, a proper superclass of split graphs. Finally, we investigate the complexity of the enumeration of (inclusion-wise) minimal connected dominating sets and minimal total dominating sets of graphs. We show that there exists an output-polynomial time algorithm for the Dom-Enum problem (or equivalently Trans-Enum problem) if and only if there exists one for the following enumeration problems: minimal total dominating sets, minimal total dominating sets in split graphs, minimal connected dominating sets in split graphs, minimal dominating sets in co-bipartite graphs.Comment: 15 pages, 3 figures, In revisio

    On a class of intersection graphs

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    Given a directed graph D = (V,A) we define its intersection graph I(D) = (A,E) to be the graph having A as a node-set and two nodes of I(D) are adjacent if their corresponding arcs share a common node that is the tail of at least one of these arcs. We call these graphs facility location graphs since they arise from the classical uncapacitated facility location problem. In this paper we show that facility location graphs are hard to recognize and they are easy to recognize when the graph is triangle-free. We also determine the complexity of the vertex coloring, the stable set and the facility location problems on that class

    A Note on Graphs of Linear Rank-Width 1

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    We prove that a connected graph has linear rank-width 1 if and only if it is a distance-hereditary graph and its split decomposition tree is a path. An immediate consequence is that one can decide in linear time whether a graph has linear rank-width at most 1, and give an obstruction if not. Other immediate consequences are several characterisations of graphs of linear rank-width 1. In particular a connected graph has linear rank-width 1 if and only if it is locally equivalent to a caterpillar if and only if it is a vertex-minor of a path [O-joung Kwon and Sang-il Oum, Graphs of small rank-width are pivot-minors of graphs of small tree-width, arxiv:1203.3606] if and only if it does not contain the co-K_2 graph, the Net graph and the 5-cycle graph as vertex-minors [Isolde Adler, Arthur M. Farley and Andrzej Proskurowski, Obstructions for linear rank-width at most 1, arxiv:1106.2533].Comment: 9 pages, 2 figures. Not to be publishe

    Algorithmic Aspects of a General Modular Decomposition Theory

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    A new general decomposition theory inspired from modular graph decomposition is presented. This helps unifying modular decomposition on different structures, including (but not restricted to) graphs. Moreover, even in the case of graphs, the terminology ``module'' not only captures the classical graph modules but also allows to handle 2-connected components, star-cutsets, and other vertex subsets. The main result is that most of the nice algorithmic tools developed for modular decomposition of graphs still apply efficiently on our generalisation of modules. Besides, when an essential axiom is satisfied, almost all the important properties can be retrieved. For this case, an algorithm given by Ehrenfeucht, Gabow, McConnell and Sullivan 1994 is generalised and yields a very efficient solution to the associated decomposition problem

    A Polynomial Delay Algorithm for Enumerating Minimal Dominating Sets in Chordal Graphs

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    An output-polynomial algorithm for the listing of minimal dominating sets in graphs is a challenging open problem and is known to be equivalent to the well-known Transversal problem which asks for an output-polynomial algorithm for listing the set of minimal hitting sets in hypergraphs. We give a polynomial delay algorithm to list the set of minimal dominating sets in chordal graphs, an important and well-studied graph class where such an algorithm was open for a while.Comment: 13 pages, 1 figure, submitte

    A Note On Computing Set Overlap Classes

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    Let V{\cal V} be a finite set of nn elements and F={X1,X2,>...,Xm}{\cal F}=\{X_1,X_2, >..., X_m\} a family of mm subsets of V.{\cal V}. Two sets XiX_i and XjX_j of F{\cal F} overlap if Xi∩Xj≠∅,X_i \cap X_j \neq \emptyset, Xj∖Xi≠∅,X_j \setminus X_i \neq \emptyset, and Xi∖Xj≠∅.X_i \setminus X_j \neq \emptyset. Two sets X,Y∈FX,Y\in {\cal F} are in the same overlap class if there is a series X=X1,X2,...,Xk=YX=X_1,X_2, ..., X_k=Y of sets of F{\cal F} in which each XiXi+1X_iX_{i+1} overlaps. In this note, we focus on efficiently identifying all overlap classes in O(n+∑i=1m∣Xi∣)O(n+\sum_{i=1}^m |X_i|) time. We thus revisit the clever algorithm of Dahlhaus of which we give a clear presentation and that we simplify to make it practical and implementable in its real worst case complexity. An useful variant of Dahlhaus's approach is also explained

    Efficient enumeration of maximal split subgraphs and sub-cographs and related classes

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    In this paper, we are interested in algorithms that take in input an arbitrary graph GG, and that enumerate in output all the (inclusion-wise) maximal "subgraphs" of GG which fulfil a given property Π\Pi. All over this paper, we study several different properties Π\Pi, and the notion of subgraph under consideration (induced or not) will vary from a result to another. More precisely, we present efficient algorithms to list all maximal split subgraphs, sub-cographs and some subclasses of cographs of a given input graph. All the algorithms presented here run in polynomial delay, and moreover for split graphs it only requires polynomial space. In order to develop an algorithm for maximal split (edge-)subgraphs, we establish a bijection between the maximal split subgraphs and the maximal independent sets of an auxiliary graph. For cographs and some subclasses , the algorithms rely on a framework recently introduced by Conte & Uno called Proximity Search. Finally we consider the extension problem, which consists in deciding if there exists a maximal induced subgraph satisfying a property Π\Pi that contains a set of prescribed vertices and that avoids another set of vertices. We show that this problem is NP-complete for every "interesting" hereditary property Π\Pi. We extend the hardness result to some specific edge version of the extension problem

    HH-product and HH-threshold graphs

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    This paper is the continuation of the research of the author and his colleagues of the {\it canonical} decomposition of graphs. The idea of the canonical decomposition is to define the binary operation on the set of graphs and to represent the graph under study as a product of prime elements with respect to this operation. We consider the graph together with the arbitrary partition of its vertex set into nn subsets (nn-partitioned graph). On the set of nn-partitioned graphs distinguished up to isomorphism we consider the binary algebraic operation ∘H\circ_H (HH-product of graphs), determined by the digraph HH. It is proved, that every operation ∘H\circ_H defines the unique factorization as a product of prime factors. We define HH-threshold graphs as graphs, which could be represented as the product ∘H\circ_{H} of one-vertex factors, and the threshold-width of the graph GG as the minimum size of HH such, that GG is HH-threshold. HH-threshold graphs generalize the classes of threshold graphs and difference graphs and extend their properties. We show, that the threshold-width is defined for all graphs, and give the characterization of graphs with fixed threshold-width. We study in detail the graphs with threshold-widths 1 and 2

    On graphs associated to sets of rankings

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    In this paper we analyze families of rankings by studying structural properties of graphs. Given a finite number of elements and a set of rankings of those elements, two elements compete when they exchange their relative positions in at least two rankings, and we can associate an undirected graph to a set of rankings by connecting elements that compete. We call this graph a competitivity graph. Competitivity graphs have already appeared in the literature as co-comparability graphs, f-graphs or intersection graphs associated to a concatenation of permutation diagrams. We introduce certain important sets of nodes in a competitivity graph. For example, nodes that compete among them form a competitivity set and nodes connected by chains of competitors form a set of eventual competitors. These sets are analyzed and a method to obtain sets of eventual competitors directly from a set of rankings is shown. © 2015 Elsevier B.V.This paper was partially supported by Spanish MICINN Funds and FEDER Funds MTM2009-13848, MTM2010-16153 and MTM2010-18674, and Junta de Andalucia Funds FQM-264. The authors would like to thank an anonymous referee for the valuable comments and remarks.Criado Herrero, R.; García, E.; Pedroche Sánchez, F.; Romance, M. (2016). On graphs associated to sets of rankings. Journal of Computational and Applied Mathematics. 291:497-508. doi:10.1016/j.cam.2015.03.009S49750829
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