Artigos
URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/219
Artigos produzidos de convênios e parcerias com IES
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Item Otimização Multiobjetivo de Filtros Harmônicos Passivos para Instalações Industriais Usando Técnicas de NSGA-II(INSTITUTO DE TECNOLOGIA, 2015) LEITE, Jandecy Cabral; ABRIL, Ignacio Perez; AZEVEDO, Manoel Socorro Santos; MEDEIROS, Adelson Bezerra de; NASCIMENTO, Manoel Henrique Reis; VALENZUELA, Walter Andres Vermehren; Prof. Dr. Waldinei Rosa Monteiro.This paper presents a mathematical method and a computational tool for the selection and sizing of passive harmonic filters in industrial systems using the NSGA-II genetic algorithm. The goal is to maximize the economic benefits of the project, minimize harmonic distortion in the PCC current and bus voltages, and comply with power quality standards (ANEEL and IEEE 519-92). The results demonstrate the method's effectiveness in determining filter parameters, selecting configurations, and addressing multiple operational scenarios.Item Impacto ecológico de los Intercambiadores de calor de tubo y coraza(INSTITUTO DE TECNOLOGIA, 2014) REYES-RODRÍGUEZ, Maida Bárbara; MOYA RODRÍGUEZ, Jorge Laureano; CRUZ FONTICIELLA, Oscar Miguel; Prof Dr. Walter Barra JuniorShell and tube heat exchangers are essential components in chemical process industries. This paper proposes a new expression to evaluate their environmental impact, combining the “entransy dissipation” concept — introduced as an alternative to entropy — with Angulo-Brown’s “ecological function.” A multi-objective optimization considering irreversibilities and cost is also conducted, using genetic algorithms as the solving method.Item Uso de Algoritmo Cultural com uma Nova Abordagem Memética por meio do Simulated Annealing para o Problema do Caixeiro Viajante(INSTITUTO DE TECNOLOGIA, 2014) SILVA, Deam J. A.; SILVA, Joaquim A. L.; AFFONSO, Carolina M.; OLIVEIRA, Roberto C. L.; MAGALHÃES, Edilson MarquesThe paper proposes a hybrid algorithm combining Cultural Algorithms (CAs) and Genetic Algorithms (GAs), with local search via simulated annealing and 2-opt/3-opt heuristics, to solve the Traveling Salesman Problem (TSP). The aim is to overcome premature convergence and local optima traps common in traditional metaheuristics. Experiments with 442 and 532-city instances showed that the approach achieved solutions close to the known optimum, outperforming other methods in the literature.