7 research outputs found

    On bipartization of cubic graphs by removal of an independent set

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    We study a new problem for cubic graphs: bipartization of a cubic graph Q by deleting sufficiently large independent set I. It can be expressed as follows: Given a connected n-vertex tripartite cubic graph Q = (V, E) with independence number α(Q), does Q contain an independent set I of size k such that Q − I is bipartite? We are interested for which value of k the answer to this question is affirmative. We prove constructively that if α(Q) ≄ 4n/10, then the answer is positive for each k fulfilling ⌊(n − α(Q))/2⌋ ≀ k ≀ α(Q). It remains an open question if a similar construction is possible for cubic graphs with α(Q) \u3c 4n/10. Next, we show that this problem with α(Q) ≄ 4n/10 and k fulfilling inequalities ⌊n/3⌋ ≀ k ≀ α(Q) can be related to semi-equitable graph 3-coloring, where one color class is of size k, and the subgraph induced by the remaining vertices is equitably 2-colored. This means that Q has a coloring of type (k, ⌈(n − k)/2⌉, ⌊(n − k)/2⌋)

    Complexity and algorithms related to two classes of graph problems

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    This thesis addresses the problems associated with conversions on graphs and editing by removing a matching. We study the f-reversible processes, which are those associated with a threshold value for each vertex, and whose dynamics depends on the number of neighbors with different state for each vertex. We set a tight upper bound for the period and transient lengths, characterize all trees that reach the maximum transient length for 2-reversible processes, and we show that determining the size of a minimum conversion set is NP-hard. We show that the AND-OR model defines a convexity on graphs. We show results of NP-completeness and efficient algorithms for certain convexity parameters for this new one, as well as approximate algorithms. We introduce the concept of generalized threshold processes, where the results are NP-completeness and efficient algorithms for both non relaxed and relaxed versions. We study the problem of deciding whether a given graph admits a removal of a matching in order to destroy all cycles. We show that this problem is NP-hard even for subcubic graphs, but admits efficient solution for several graph classes. We study the problem of deciding whether a given graph admits a removal of a matching in order to destroy all odd cycles. We show that this problem is NP-hard even for planar graphs with bounded degree, but admits efficient solution for some graph classes. We also show parameterized results.Esta tese aborda problemas associados a conversĂ”es em grafos e de edição pela remoção de um emparelhamento. Estudamos processos f-reversĂ­veis, que sĂŁo aqueles associados a um valor de limiar para cada vĂ©rtice e cuja dinĂąmica depende da quantidade de vizinhos com estado contrĂĄrio para cada vĂ©rtice. Estabelecemos um limite superior justo para o tamanho do perĂ­odo e transiente, caracterizamos todas as ĂĄrvores que alcançam o transiente mĂĄximo em processos 2-reversĂ­veis e mostramos que determinar o tamanho de um conjunto conversor mĂ­nimo Ă© NP-difĂ­cil. Mostramos que o modelo AND-OR define uma convexidade sobre grafos. Mostramos resultados de NP-completude e algoritmos eficientes para certos parĂąmetros de convexidade para esta nova, assim como algoritmos aproximativos. Introduzimos o conceito de processos de limiar generalizados, onde mostramos resultados de NP-completude e algoritmos eficientes para ambas as versĂ”es nĂŁo relaxada e relaxada. Estudamos o problema de decidir se um dado grafo admite uma remoção de um emparelhamento de modo a remover todos os ciclos. Mostramos que este problema Ă© NP-difĂ­cil mesmo para grafos subcĂșbicos, mas admite solução eficiente para vĂĄrias classes de grafos. Estudamos o problema de decidir se um dado grafo admite uma remoção de um emparelhamento de modo a remover todos os ciclos Ă­mpares. Mostramos que este problema Ă© NP-difĂ­cil mesmo para grafos planares com grau limitado, mas admite solução eficiente para algumas classes de grafos. Mostramos tambĂ©m resultados parametrizados
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