Surface Acoustic Wave Devices for Mobil and Wireless Communications
Surface Acoustic Wave Devices for Mobil and Wireless Communications
Journal of Global Optimization
Simulation modeling and optimization technique for balanced surface acousticwave filters
SMO'07 Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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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.