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URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/219

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    Methodology Proposal for Multicriteria Optimization Using NSGA-II in Industrial Applications
    (INSTITUTO DE TECNOLOGIA, 2023) CASTRO, Anderson de Oliveira; BEZERRA, Ubiratan Holanda; LEITE, Jandecy Cabral; AZEVEDO, Manoel Socorro Santos.; Professor Dr. Bernardo Borges Pompeu Neto
    The paper proposes a methodology for multicriteria optimization using the NSGA-II genetic algorithm in industrial applications, specifically in the assembly process of electronic components in surface mount technology (SMT) machines. The study addresses problems such as feeder arrangement and head routing, aiming to reduce the total cycle time. The methodology integrates known approaches and applies multi-objective optimization to enhance machine performance, with results validated in a real industrial environment.
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    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 Souza
    This 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.