Documentação de convênios
URI permanente desta comunidadehttps://rigalileo.itegam.org.br/handle/123456789/173
Trabalhos ténico-científico oriundos de convênios com universidades para oferta de turmas de mestrado e doutorados no Estado do Amazonas
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Resultados da Pesquisa
Item MODELO MATEMÁTICO PARA OTIMIZAÇÃO MULTIOBJETIVO DO DESPACHO ECONÔMICO AMBIENTAL DE USINAS TÉRMICAS USANDO O NSGA-II(Universidade Federal do Pará, 2017) MORAES, Nadime Mustafa; BEZERRA, Ubiratan HolandaOne of the priority tasks for thermoelectric plants is to supply the requested energy demand, ensuring the lowest possible cost. This task is especially important in the Northern Region of Brazil, particularly in the Manaus Industrial Hub (PIM), where much of the energy is supplied by Thermoelectric Power Plants (UTE). The selection of generators and their work regime is known as Economic Dispatch (DE). However, global concern about pollution caused by fossil fuels has made it essential to incorporate not only cost reduction but also the limitation of pollutant emissions in UTE operations. Thus, Environmental Economic Dispatch (DEA) emerges, aiming to simultaneously reduce costs and emissions. This thesis proposes an innovative mathematical model for DEA, using the NSGA-II evolutionary algorithm with two objective functions: fuel cost and amount of emissions. The model also introduces the Emissions Index, a new function to evaluate environmental contamination, considering the influence of the most harmful pollutants. The model was applied to engines of two UTEs in the city of Manaus, showing satisfactory results. The methodology proved robust when validated in two case studies: a set of ten thermal generating units and the IEEE 118-bus system.Item Metodología propuesta para la optimización multicriterio mediante algoritmos genéticos en las aplicaciones industriales(INSTITUTO DE TECNOLOGIA, 2014) CASTRO, Andy Oliveira; BEZERRA, Ulysses Henrique; LEITE, Jandecy Cabral; AZEVEDO, Marcelo da Silva Sousa; José Antônio da Silva SouzaThis paper proposes a new methodology for multi-criteria optimization in modular chip mounters using the NSGA-II genetic algorithm. Fitness functions were modeled, and a multi-criteria optimization tool was created based on machine functions and constraints. The same approach can be applied to other types of machines to support decision-making in industrial environments, aiming at efficiency and cost reduction.Item Optimización del proceso de montaje de componentes SMD usando algoritmo genético multiobjetivo en la industria(INSTITUTO DE TECNOLOGIA, 2014) CIRINO, Weverson dos Santos; MUSTAFE, Nadime; REIS, Ana; CASTRO, Anderson; BEZERRA, Ubiratan Holanda; Professora Dra. Fernanda Souza do NascimentoThe article proposes the optimization of the assembly sequence of SMD components on printed circuit boards using a multi-objective genetic algorithm (NSGA-II). The study was conducted in an electronics industry at the Manaus Industrial Hub, showing that the proposed algorithm outperformed the traditional machine inserter optimizer, reducing assembly time by 6 seconds per board and increasing productivity by 30%. The results highlight the effectiveness of NSGA-II in solving complex industrial optimization problems.Item Optimización Multiobjetivo de Filtros Pasivos(INSTITUTO DE TECNOLOGIA, 2012) LEITE, Jandecy Cabral; ABRIL, Ignacio Pérez; TOSTES, Maria Emilia de Lima; OLIVEIRA, Roberto Celio Limão de; MAGALHÃES, Edilson MarquesDifferent approaches have been used to formulate the problem of passive filter design, classified into single or multi-objective formulations. While previous contributions solve the multi-objective problem by minimizing a single objective function composed of a weighted sum of sub-objectives, this work uses the Non-dominated Sorting Genetic Algorithm (NSGA-II) to address the problem. The developed program determines the number, location, configuration, and parameters of passive filters required to obtain non-dominated optimal solutions, considering four predefined filter types. The solution of a practical example demonstrates the effectiveness of the proposed procedure.