A new design technique for antennas, namely the Structure-based Evolutionary Design (SED), is introduced and described in detail. SED is a new global random search method derived by the “genetic programming”, a strategy proposed by Koza. The proposed technique will be compared with the genetic algorithms (GA), a widely used design technique, showing the numerous advantages of our approach with respect to standard ones. SED assumes no “a priori” structure, but it builds up the structure of the individuals as the procedure evolves. Therefore SED is able to determine both the structure shape and dimensions as an outcome of the procedure (infinite-dimensional solution space), acting on subparts of the whole structure, and allowing to explore effectively the far more vast solution space.
We thoroughly discuss both the general features of SED and its application to wire antenna design. The antenna internal representation, which is a key to the successful implementation of SED, and the construction of fitness functions from the antenna specifications will be described in detail.
The proposed approach has been assessed with many different cases, using as design requirements both Gain and VSWR in a frequency band as wide as possible, and with the smallest size. The results obtained with SED are finally compared with other popular algorithms like Particle Swarm Optimization (PSO) and Differential Evolution (DE), showing that both the computational cost and the complexity are of the same order of magnitude, but the performances obtained by SED are significantly higher
