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Applying Genetic Algorithm to Optimization Second-Order Bandpass MGMFB Filter

In this paper, we have applied the genetic algorithm to the selection of the true values for RC (resistors/capacitors) as an essential role in the development of analogue active filters. The classic method of incorporating passive elements is a complex situation and can attend to errors. In order to reduce the frequency of errors and the human effort, evolutionary optimization methods are employed to select the RC values. In this study, Genetic algorithm (GA) is proposed to optimize the second-order active filter. It must find the values of the passive elements RC to get a filter configuration that reduces the sensitivities to variations as well as reduces design errors less than a defined height value, concerning certain specifications. The optimization problem which is one of the problems that must be solved by GA is a multi-objective optimization problem (MOOP). GA was carried out taking into account two possible situations about the values that resistors and capacitors could adopt. The obtained experimental results show that GA can be used to obtain filter configurations that meet the specified standard.