In this paper, several methods for optimization of a 5-elements Yagi antenna are proposed using genetic algorithm, genetic algorithm inspired by simulated annealing, genetic algorithm based on fuzzy decision making, and particle swarm method. High speed run time of Supe
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In this paper, several methods for optimization of a 5-elements Yagi antenna are proposed using genetic algorithm, genetic algorithm inspired by simulated annealing, genetic algorithm based on fuzzy decision making, and particle swarm method. High speed run time of SuperNEC software, it has been used for analyzing the presented methods. The use of genetic algorithm or genetic algorithm inspired by simulated annealing for antenna optimization in a specific frequency band, needs long run time. Besides, reduction of the number of population and the amount of repetition, causes decrease in optimization precision. So, an optimization system base on fuzzy decision making is proposed. In addition, the particle swarm method which has a good convergence rate and good performance has been proposed to obtain a better optimization. The comparison between the proposed optimization methods shows that the genetic based on fuzzy decision making and the particle swarm methods have the best performance and functionality and the least run time.
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