Metodología propuesta para la optimización multicriterio mediante algoritmos genéticos en las aplicaciones industriales

Abstract

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.