Optimum Design of Balanced SAW Filters Using Evolutionary Multi-objective Optimization

The frequency response characteristics of the balanced Surface Acoustic Wave (SAW) filters are governed primarily by their geometrical structures. Therefore, in order to realize desirable frequency response characteristics, the structural design of the balanced SAW filter is formulated as a constrained multi-objective optimization problem. Then a recent Evolutionary Multi-objective Optimization (EMO) method, which is called Generalized Differential Evolution 3 (GED3), is applied to the multi-objective optimization problem. Furthermore, in order to clarify the tradeoff relationship among the objective functions of the multi-objective optimization problem, Principal Component Analysis (PCA) is used to assess the set of the non-dominated solutions obtained by GDE3. Key–Words: Surface acoustic wave filter, evolutionary algorithm, optimum design