Programa de Pós-graduação em Ciência da Computação em Rede
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Navegando Programa de Pós-graduação em Ciência da Computação em Rede por Por Orientador "Nascimento, Hugo Alexandre Dantas do"
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Item Problemas de otimização combinatória para união explícita de arestas(Universidade Federal de Goiás, 2018-03-21) Ferreira, Joelma de Moura; Foulds, Les; http://lattes.cnpq.br/3737395828552021; Nascimento, Hugo Alexandre Dantas do; http://lattes.cnpq.br/2920005922426876; Freitas, Carla Maria Dal Sasso; Paulovich, Fernando; Longo, Humberto José; Soares, Telma Woerle de LimaEdge bundling is a technique to group, align, coordinate and position the depiction of edges in a graph drawing, so that sets of edges appear to be brought together into shared visual structures, i.e. bundles. The ultimate goal is to reduce clutter to improve how it conveys information. This thesis provides a general formulation for the explicity edge bundling problems, as a formal combinatorial optimization problem. This allows for the definition and comparison of edge bundling problems. In addition, we present four explicity edge bundling optimization problems that address minimizing the total number of bundles, in conjunction with other aspects, as the main goal. An evolutionary edge bundling algorithm is described. The algorithm was successfully tested by solving three related problems applied to real-world instances. The reported experimental results demonstrate the effectiveness and the applicability of the proposed evolutionary algorithm to help resolve edge bundling problems formally defined as optimization models.Item Construção de visualizações de matrizes origem-destino no cenário do tráfego urbano com foco em avaliação de usabilidade(Universidade Federal de Goiás, 2016-09-26) Gondim, Halley Wesley Alexandre Silva; Nascimento, Hugo Alexandre Dantas do; http://lattes.cnpq.br/2920005922426876; Carvalho, Cedric Luiz de; Freitas, Carla Maria Dal Sasso; Albuquerque, Eduardo Simões de; Soares, Fabrízzio Alphonsus Alves de Melo NunesMost of the medium and large cities in the world suffer from the problems related to the growth of the number of vehicles. Congestion, air pollution and weather are some examples of these problems, today constantly reminded of the great damage done to citizens. The use of Information Visualization techniques can serve to support the analysis of these problems and help identify viable and effective solutions for them. On the other hand, the application of Information Visualization to the problems of urban traffic is still a poorly explored area and generally focused on simple aspects of traffic. The present thesis thus addresses the lack of studies in this area, especially in the representation of data related to origin-destination (OD) matrices. In order to do so, a specific classification is proposed for visualizations aimed at the urban traffic scenario, with the purpose of facilitating the identification of works and authors related to the area. In addition, there is the creation of new visualizations, directed to OD arrays, in order to offer different alternatives in the representation of traffic data. Finally, an approach is proposed to evaluate visualizations of OD matrices and correlated information, with the intention of offering adequate feedback to interface designers and enabling the creation of more effective visualizations.Item Application of GPU Computing to Some Urban Traffic Problems(Universidade Federal de Goiás, 2016-11-30) Jradi, Walid Abdala Rfaei; Martins, Wellington Santos; http://lattes.cnpq.br/3041686206689904; Nascimento, Hugo Alexandre Dantas do; http://lattes.cnpq.br/2920005922426876; Camponogara, Eduardo; Clua, Esteban Walter Gonzalez; Mongelli , Henrique; Costa, Fábio MoreiraThe present work studies and proposes GPU-based parallel algorithms and implementations for the problem of macroscopic assignment of urban traffic on large-scale networks, promoting an in-depth investigation on each sub-problem that must be efficiently solved during the traffic assignment process. Among the main contributions of this work, there are: 1) the first GPU-based algorithm for the enumeration of chordless cycles; 2) a new parallel GPU-based shortest path algorithm that takes advantage of some common properties of urban traffic networks; a refinement in the parallel reduction implementation proposed by one of the leaders in the GPU market, which resulted in a 2.8x speedup relative to its original version; and finally, 3) a parallel algorithm for the macroscopic traffic assignment problem, 39x faster than the equivalent sequential approach when applied to large scale networks. The main goal of this thesis is to contribute to the extension of the PET-Gyn software, proposing efficient GPU data structures and parallel algorithms for a faster resolution of two well known problems in the literature: The Traffic Assignment Problem (TAP) and the Enumeration of Chordless Cycles. When applied to difficult input sets, the performed experiments showed a clear advantage of the parallel algorithms over their sequential versions.