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Problemas computacionais em teoria topológica dos grafos / Computational problems in topological graph theoryPocai, Rafael Veiga 11 December 2015 (has links)
Este trabalho tem por objetivo estudar os problemas computacionais que surgem ao se relacionar grafos com superfícies bidimensionais, dando especial atenção aos problemas do número de cruzamentos mínimo no plano (CROSSING NUMBER) e a problemas relacionados ao desenho de grafos em livros. Apresentamos uma redução do problema MULTICUT para CROSSING NUMBER, além de um resultado de complexidade em grafos de comparabilidade baseado em um resultado conhecido para desenhos em livros. / The objective of this text is to study computational problems that emerge from the relation between graphs and bidimensional surfaces, giving special attention to the crossing number problem and graph drawings on books. We present a reduction from MULTICUT to CROSSING NUMBER, in addition to a complexity result on comparability graphs based on a known result about drawings on books.
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Problemas computacionais em teoria topológica dos grafos / Computational problems in topological graph theoryRafael Veiga Pocai 11 December 2015 (has links)
Este trabalho tem por objetivo estudar os problemas computacionais que surgem ao se relacionar grafos com superfícies bidimensionais, dando especial atenção aos problemas do número de cruzamentos mínimo no plano (CROSSING NUMBER) e a problemas relacionados ao desenho de grafos em livros. Apresentamos uma redução do problema MULTICUT para CROSSING NUMBER, além de um resultado de complexidade em grafos de comparabilidade baseado em um resultado conhecido para desenhos em livros. / The objective of this text is to study computational problems that emerge from the relation between graphs and bidimensional surfaces, giving special attention to the crossing number problem and graph drawings on books. We present a reduction from MULTICUT to CROSSING NUMBER, in addition to a complexity result on comparability graphs based on a known result about drawings on books.
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Simultaneous Graph Representation ProblemsJampani, Krishnam Raju January 2011 (has links)
Many graphs arising in practice can be represented in a concise and intuitive way that conveys their structure. For example: A planar graph can be represented in the plane with points for vertices and non-crossing curves for edges. An interval graph can be represented on the real line with intervals for vertices and intersection of intervals representing edges. The concept of ``simultaneity'' applies for several types of graphs: the idea is to find representations for two graphs that share some common vertices and edges, and ensure that the common vertices and edges are represented the same way. Simultaneous representation problems arise in any situation where two related graphs should be represented consistently. A main instance is for temporal relationships, where an old graph and a new graph share some common parts. Pairs of related graphs arise in many other situations. For example, two social networks that share some members; two schedules that share some events, overlap graphs of DNA fragments of two similar organisms, circuit graphs of two adjacent layers on a computer chip etc. In this thesis, we study the simultaneous
representation problem for several graph classes.
For planar graphs the problem is defined as follows. Let G1 and G2 be two graphs sharing some vertices and edges. The simultaneous planar embedding problem asks whether there exist planar embeddings (or drawings) for G1 and G2 such that every vertex shared by the two graphs is mapped to the same point and every shared edge is mapped to the same curve in both embeddings. Over the last few years there has been a lot of work on simultaneous planar embeddings, which have been called `simultaneous embeddings with fixed edges'. A major open question is whether simultaneous planarity for two graphs can be tested in polynomial time. We give a linear-time algorithm for testing the simultaneous planarity of any two graphs that share a 2-connected subgraph. Our algorithm also extends to the case of k planar graphs, where each vertex [edge] is either common to all graphs
or belongs to exactly one of them.
Next we introduce a new notion of simultaneity for intersection graph classes (interval graphs, chordal graphs etc.) and for comparability graphs. For interval graphs, the problem is defined as follows. Let G1 and G2 be two interval graphs sharing some vertices I and the edges induced by I. G1 and G2 are said to be `simultaneous interval graphs' if there exist interval representations of G1 and G2 such that any vertex of I is assigned to the same interval in both the representations. The `simultaneous representation problem' for interval graphs asks whether G1 and G2 are simultaneous interval graphs. The problem is defined in a similar way for other intersection graph classes.
For comparability graphs and any intersection graph class, we show that the simultaneous representation problem for the graph class is equivalent to a graph augmentation problem: given graphs G1 and G2, sharing vertices I and the corresponding induced edges, do there exist edges E' between G1-I and G2-I such that the graph G1 U G_2 U E' belongs to the graph class. This equivalence implies that the simultaneous representation problem is closely related to other well-studied classes in the literature, namely, sandwich graphs and probe graphs.
We give efficient algorithms for solving the simultaneous representation problem for interval graphs, chordal graphs, comparability graphs and permutation graphs. Further, our algorithms for comparability and permutation graphs solve a more general version of the problem when there are multiple graphs, any two of which share the same common graph. This version of the problem also generalizes probe graphs.
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Simultaneous Graph Representation ProblemsJampani, Krishnam Raju January 2011 (has links)
Many graphs arising in practice can be represented in a concise and intuitive way that conveys their structure. For example: A planar graph can be represented in the plane with points for vertices and non-crossing curves for edges. An interval graph can be represented on the real line with intervals for vertices and intersection of intervals representing edges. The concept of ``simultaneity'' applies for several types of graphs: the idea is to find representations for two graphs that share some common vertices and edges, and ensure that the common vertices and edges are represented the same way. Simultaneous representation problems arise in any situation where two related graphs should be represented consistently. A main instance is for temporal relationships, where an old graph and a new graph share some common parts. Pairs of related graphs arise in many other situations. For example, two social networks that share some members; two schedules that share some events, overlap graphs of DNA fragments of two similar organisms, circuit graphs of two adjacent layers on a computer chip etc. In this thesis, we study the simultaneous
representation problem for several graph classes.
For planar graphs the problem is defined as follows. Let G1 and G2 be two graphs sharing some vertices and edges. The simultaneous planar embedding problem asks whether there exist planar embeddings (or drawings) for G1 and G2 such that every vertex shared by the two graphs is mapped to the same point and every shared edge is mapped to the same curve in both embeddings. Over the last few years there has been a lot of work on simultaneous planar embeddings, which have been called `simultaneous embeddings with fixed edges'. A major open question is whether simultaneous planarity for two graphs can be tested in polynomial time. We give a linear-time algorithm for testing the simultaneous planarity of any two graphs that share a 2-connected subgraph. Our algorithm also extends to the case of k planar graphs, where each vertex [edge] is either common to all graphs
or belongs to exactly one of them.
Next we introduce a new notion of simultaneity for intersection graph classes (interval graphs, chordal graphs etc.) and for comparability graphs. For interval graphs, the problem is defined as follows. Let G1 and G2 be two interval graphs sharing some vertices I and the edges induced by I. G1 and G2 are said to be `simultaneous interval graphs' if there exist interval representations of G1 and G2 such that any vertex of I is assigned to the same interval in both the representations. The `simultaneous representation problem' for interval graphs asks whether G1 and G2 are simultaneous interval graphs. The problem is defined in a similar way for other intersection graph classes.
For comparability graphs and any intersection graph class, we show that the simultaneous representation problem for the graph class is equivalent to a graph augmentation problem: given graphs G1 and G2, sharing vertices I and the corresponding induced edges, do there exist edges E' between G1-I and G2-I such that the graph G1 U G_2 U E' belongs to the graph class. This equivalence implies that the simultaneous representation problem is closely related to other well-studied classes in the literature, namely, sandwich graphs and probe graphs.
We give efficient algorithms for solving the simultaneous representation problem for interval graphs, chordal graphs, comparability graphs and permutation graphs. Further, our algorithms for comparability and permutation graphs solve a more general version of the problem when there are multiple graphs, any two of which share the same common graph. This version of the problem also generalizes probe graphs.
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Coloração de Arestas em Grafos Split-Comparabilidade / Edge coloring in split-comparability graphsCruz, Jadder Bismarck de Sousa 02 May 2017 (has links)
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Previous issue date: 2017-05-02 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Let G = (V, E) be a simple and undirected graph. An edge-coloring is an assignment of colors to the edges of the graph such that any two adjacent edges receive different colors. The chromatic index of a graph G is the smallest number of colors such that G has an edge-coloring. Clearly, a lower bound for the chromatic index is the degree of the vertex of higher degree, denoted by ?(G). In 1964, Vizing proved that chromatic index is ?(G) or ?(G) + 1. The Classification Problem is to determine if the chromatic index is ?(G) (Class 1 ) or if it is ?(G) + 1 (Class 2 ). Let n be number of vertices of a graph G and let m be its number of edges. We say G is overfull if m > (n-1) 2 ?(G). Every overfull graph is Class 2. A graph is subgraph-overfull if it has a subgraph with same maximum degree and it is overfull. It is well-known that every overfull and subgraph-overfull graph is Class 2. The Overfull Conjecture asserts that every graph with ?(G) > n 3 is Class 2 if and only if it is subgraph-overfull. In this work we prove the Overfull Conjecture to a particular class of graphs, known as split-comparability graphs. The Overfull Conjecture was open to this class. / Dado um grafo simples e não direcionado G = (V, E), uma coloração de arestas é uma função que atribui cores às arestas do grafo tal que todas as arestas que incidem em um mesmo vértice têm cores distintas. O índice cromático é o número mínimo de cores para obter uma coloração própria das arestas de um grafo. Um limite inferior para o índice cromático é, claramente, o grau do vértice de maior grau, denotado por ?(G). Em 1964, Vizing provou que o índice cromático ou é ?(G) ou ?(G) + 1, surgindo assim o Problema da Classificação, que consiste em determinar se o índice cromático é ?(G) (Classe 1 ) ou ?(G) + 1 (Classe 2 ). Seja n o número de vértices de um grafo G e m seu número de arestas. Dizemos que um grafo é sobrecarregado se m > (n-1) 2 ?(G). Um grafo é subgrafo-sobrecarregado se tem um subgrafo de mesmo grau máximo que é sobrecarregado. É sabido que se um grafo é sobrecarregado ou subgrafo-sobrecarregado ele é necessariamente Classe 2. A Conjectura Overfull é uma famosa conjectura de coloração de arestas e diz que um grafo com ?(G) > n 3 é Classe 2 se e somente se é subgrafo-sobrecarregado. Neste trabalho provamos a Conjectura Overfull para uma classe de grafos, a classe dos grafos split-comparabilidade. Até este momento a Conjectura Overfull estava aberta para esta classe.
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Capturing Polynomial Time and Logarithmic Space using Modular Decompositions and Limited RecursionGrußien, Berit 10 November 2017 (has links)
Diese Arbeit leistet Beiträge im Bereich der deskriptiven Komplexitätstheorie. Zunächst beschäftigen wir uns mit der ungelösten Frage, ob es eine Logik gibt, welche die Klasse der Polynomialzeit-Eigenschaften (PTIME) charakterisiert. Wir betrachten Graphklassen, die unter induzierten Teilgraphen abgeschlossen sind. Auf solchen Graphklassen lässt sich die 1976 von Gallai eingeführte modulare Zerlegung anwenden. Graphen, die durch modulare Zerlegung nicht zerlegbar sind, heißen prim. Wir stellen ein neues Werkzeug vor: das Modulare Zerlegungstheorem. Es reduziert (definierbare) Kanonisierung einer Graphklasse C auf (definierbare) Kanonisierung der Klasse aller primen Graphen aus C, die mit binären Relationen auf einer linear geordneten Menge gefärbt sind. Mit Hilfe des Modularen Zerlegungstheorems zeigen wir, dass Fixpunktlogik mit Zählen (FP+C) PTIME auf der Klasse aller Permutationsgraphen und auf der Klasse aller chordalen Komparabilitätsgraphen charakterisiert. Wir beweisen zudem, dass modulare Zerlegungsbäume in Symmetrisch-Transitive-Hüllen-Logik mit Zählen (STC+C) definierbar und damit in logarithmischem Platz berechenbar sind.
Weiterhin definieren wir eine neue Logik für die Komplexitätsklasse Logarithmischer Platz (LOGSPACE). Wir erweitern die Logik erster Stufe mit Zählen um einen Operator, der eine in logarithmischem Platz berechenbare Form der Rekursion erlaubt. Die resultierende Logik LREC ist ausdrucksstärker als die Deterministisch-Transitive-Hüllen-Logik mit Zählen (DTC+C) und echt in FP+C enthalten. Wir zeigen, dass LREC LOGSPACE auf gerichteten Bäumen charakterisiert. Zudem betrachten wir eine Erweiterung LREC= von LREC, die sich gegenüber LREC durch bessere Abschlusseigenschaften auszeichnet und im Gegensatz zu LREC ausdrucksstärker als die Symmetrisch-Transitive-Hüllen-Logik (STC) ist. Wir beweisen, dass LREC= LOGSPACE sowohl auf der Klasse der Intervallgraphen als auch auf der Klasse der chordalen klauenfreien Graphen charakterisiert. / This theses is making contributions to the field of descriptive complexity theory. First, we look at the main open problem in this area: the question of whether there exists a logic that captures polynomial time (PTIME). We consider classes of graphs that are closed under taking induced subgraphs. For such graph classes, an effective graph decomposition, called modular decomposition, was introduced by Gallai in 1976. The graphs that are non-decomposable with respect to modular decomposition are called prime. We present a tool, the Modular Decomposition Theorem, that reduces (definable) canonization of a graph class C to (definable) canonization of the class of prime graphs of C that are colored with binary relations on a linearly ordered set. By an application of the Modular Decomposition Theorem, we show that fixed-point logic with counting (FP+C) captures PTIME on the class of permutation graphs and the class of chordal comparability graphs. We also prove that the modular decomposition tree is definable in symmetric transitive closure logic with counting (STC+C), and therefore, computable in logarithmic space.
Further, we introduce a new logic for the complexity class logarithmic space (LOGSPACE). We extend first-order logic with counting by a new operator that allows it to formalize a limited form of recursion which can be evaluated in logarithmic space. We prove that the resulting logic LREC is strictly more expressive than deterministic transitive closure logic with counting (DTC+C) and that it is strictly contained in FP+C. We show that LREC captures LOGSPACE on the class of directed trees. We also study an extension LREC= of LREC that has nicer closure properties and that, unlike LREC, is more expressive than symmetric transitive closure logic (STC). We prove that LREC= captures LOGSPACE on the class of interval graphs and on the class of chordal claw-free graphs.
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