Genetic Optimization Algorithms In The Design Of Coupled Saw Filters

We have studied genetic optimization algorithms in the design of longitudinally coupled surface acoustic wave filters. We employ a genetic algorithm in the optimization of a symmetric filter structure with 14 simultaneously optimized parameters. The effect of several parameters of the algorithm on the convergence of the optimization is investigated. Our algorithm is compared to a modification of the "cut-and-paste" method often used in genetic optimization. Our results indicate that a genetic optimization routine is suitable for the design of coupled filters.