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A genetic algorithm for the optimal design of microwave filters

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This paper presents a multiple objective genetic algorithm for determining the component parameters in the design of a microwave filter. In this approach, we first propose a set of fuzzy-based membership functions for modeling the five design specifications (objective functions) of the microwave filter design problem. The five objective functions are then aggregated into a single-valued fitness function. Finally, a set of near-optimal component parameters for the microwave filter can be found by applying the proposed genetic algorithm. A large number of experiments were performed and demonstrated satisfactory results. This approach has three principal merits. First, it counteracts entrapment in a local optimal solution. Second, the processing of multiple objectives is relatively easy. Third, the generated solution is independent of the initial estimate. Significance: This paper presents a multiple objective genetic algorithm for determining the component parameters in the design of a microwave filter.

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