Optimización Multiobjetivo de Filtros Pasivos

Abstract

Different 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.