Robust Design in Multiobjective Systems using Taguchi’s Parameter Design Approach and a Pareto Genetic Algorithm

Enrique Canessa; Gabriel Bielenberg; Héctor Allende

doi:10.17533/udea.redin.15439

Autores/as

Enrique Canessa Universidad Adolfo Ibáñez
Gabriel Bielenberg Universidad Adolfo Ibáñez
Héctor Allende Universidad Adolfo Ibáñez

DOI:

https://doi.org/10.17533/udea.redin.15439

Palabras clave:

algoritmos genéticos de Pareto, algoritmos evolucionarios multiobjetivo, diseño de parámetros

Resumen

Se presenta un Algoritmo Genético de Pareto (AGP), que encuentra la frontera de Pareto en problemas de diseño robusto para sistemas multiobjetivo. El AGP fue diseñado para ser aplicado usando el método de Diseño de Parámetros de Taguchi, el cual es el método más frecuentemente empleado por profesionales para ejecutar diseño robusto. El AGP se probó con datos obtenidos de un sistema real con una respuesta y de un simulador de procesos multiobjetivo con muchos factores de control y ruido. En todos los casos, el AGP entregó soluciones óptimas que cumplen con los objetivos del diseño robusto. Además, la discusión de resultados muestra que tener dichas soluciones ayuda en la selección de las mejores a ser implementadas en el sistema bajo estudio, especialmente cuando el sistema tiene muchos factores de control y salidas.

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Biografía del autor/a

Enrique Canessa, Universidad Adolfo Ibáñez

Facultad de Ingeniería y Ciencias.

Gabriel Bielenberg, Universidad Adolfo Ibáñez

Facultad de Ingeniería y Ciencias.

Héctor Allende , Universidad Adolfo Ibáñez

Departamento de informática, Facultad de Ingeniería y Ciencias. Docente.

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