Navegando por Assunto "Transporte"

Filtrar resultados informando as primeiras letras
Agora exibindo 1 - 2 de 2
  • Nenhuma Miniatura disponível
    Item
    Análise da interoperabilidade da infraestrutura de carregamento dos veículos elétricos e sistemas de transporte inteligente
    (Centro Universitário do Estado do Pará, 2021) Brito, Matheus Moraes de; Costa, Stefany Cristina Pinheiro; Santos, Michelle Bitar Lelis dos; http://lattes.cnpq.br/1208797288539861; Ribeiro, Moshe Dayan Sousa; http://lattes.cnpq.br/5200296393526606; Dias, Suzane Alfaia; http://lattes.cnpq.br/9675395702501834
    The urbanization growth and world capitals industrialization were expressive in the last decades, although pollution problems, fuel and constant congestions threaten the efficiency of urban development. Electric vehicles are a promising option to contribute in the energy diversification and an alternative to polluting forms commonly used in urban and rural road infrastructure, despite the differences between the duration recharging and refueling times between the types of vehicles. The inteligente transportation systems represent the implementation of transport advanced technologies to sense and process road conditions to improve traffic fluidity and avoid accidents. In order to improve the efficiency of electric vehicle charging, the research proposes the integration of recharge infrastructure with intelligenttransportation systems as a way of assisting drivers and companies seeking to join the new ecological trend.
  • Nenhuma Miniatura disponível
    Item
    Aplicação de um algoritmo genético para otimização do roteamento de veículos coletivos em rede
    (Centro Universitário do Estado do Pará, 2018-06-15) Almeida Neto, Adilson de; Ferreira, Fábio dos Santos; http://lattes.cnpq.br/4845857829374774; Pereira, Rodrigo Lisbôa; http://lattes.cnpq.br/0961152700140103; Souza, Daniel Leal; http://lattes.cnpq.br/6059334260016388
    Genetic algorithms are used in a wide range of optimization problems, especially in combinatorial problems, where the search space is, in many occasions, too large for exact methods to achieve optimal solutions. This class of problems bear great importance for mathematical models that reflect real world situations, such as vehicle routing. The goal of this work is to utilize a genetic algorithm to optimize networked linked capacitated vehicles, in this configuration, all passengers and drivers positions are known in every moment. To make this optimization possible, the problem was mathematically modeled using the Capacitated Vehicle Routing Problem (CVRP) as inspiration with alterations reflecting the nature of the network linked capacitated vehicles. After that, this work also compares the obtained performance to a non-optimized route, so that the gain from using this method can be observed.