Optimization of Yagi array by hierarchical genetic algorithms

Abstract

A method of hierarchical genetic algorithms (HGA) is used for optimizing the element spacing and lengths of Yagi-Uda antennas. This scheme has the ability of handling multiobjective functions as well as the discrete constraints in the numerical optimizing process. Together with the technique of Pareto ranking scheme, more than one possible solution can be obtained. It has been found that the number of dipoles of the antenna can be minimally identified with multi-facet design criteria as well as the imposed stringent constraints on the antenna design. Furthermore, this added feature also enables a design tradeoff between cost and performance without extra computational effort.