Methodology Proposal for Multicriteria Optimization Using NSGA-II in Industrial Applications

Abstract

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.