Artigos

URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/5

Navegar

Filtrar resultados informando as primeiras letras
Agora exibindo 1 - 2 de 2
  • Imagem de Miniatura
    Item
    Computational meta-heuristics based on Machine Learning to optimize fuel consumption of vessels using diesel engines
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) SIQUEIRA JÚNIOR, Paulo Oliveira; NASCIMENTO, Manoel Henrique Reis; SILVA, Ítalo Rodrigo Soares; PARENTE, Ricardo Silva; FONSECA JÚNIOR, Milton; LEITE, Jandecy Cabral.; LEITE, Jandecy Cabral
    With the expansion of river transportation, especially in the case of small and medium-sized vessels that make longer routes, the cost of fuel, if not taken as an analysis criterion for a larger profit margin, is considered a primary factor, considering that the value of fuel, specifically diesel, to power internal combustion engines is high. Therefore, the use of tools that assist in decision-making becomes necessary, as is the case of the present research, which aims to contribute with a computational model of prediction and optimization of the best speed to decrease fuel cost, considering the characteristics of the SCANIA 315 propulsion model, of a vessel from the river port of Manaus that carries out river transportation to several municipalities in Amazonas. According to the results of the simulations, the best training algorithm of the Artificial Neural Network (ANN) was the BFGS Quasi-Newton, considering the characteristics of the engine for optimization with Genetic Algorithm (GA).
  • Imagem de Miniatura
    Item
    Problema de Roteamento de Veículo e suas Variantes: uma Revisão Sistemática de Literatura
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2022) BATISTA, Roberto Lopes; UHLMANN, Iracyanne Retto.; LEITE, Jandecy Cabral
    This study addresses a systematic literature review on the Vehicle Routing Problem (VRP) and its variants, building a bibliographic portfolio regarding the most suitable type of VRP for postal services. For this research, the ProKnow-C methodology was adopted, enabling the selection of articles in a more assertive, rigorous, and specific manner, eliminating redundancies and subjectivities, by searching articles in the Scopus and Web of Science databases. The objective of this article is to analyze the state of the art on VRP and its variants, and the main methodological approaches used, in the context of distribution logistics. A total of 114 articles aligned with the theme were selected, demonstrating that there is a vast literature on vehicle routing. This review shows that the genetic algorithm with adaptations is the most widely used model today to optimize routes for parcel collection and delivery.