OPTIMIZATION OF ANTENNA CONFIGURATION WITH A FITNESS-ADAPTIVE DIFFERENTIAL EVOLUTION ALGORITHM

In this article, a novel numerical technique, called Fitness Adaptive Difierential Evolution (FiADE) for optimizing certain pre-deflned antenna conflguration to attain best possible radiation characteristics is presented. Difierential Evolution (DE), inspired by the natural phenomenon of theory of evolution of life on earth, employs the similar computational steps as by any other Evolutionary Algorithm (EA). Scale Factor and Crossover Probability are two very important control parameter of DE.This article describes a very competitive yet very simple form of adaptation technique for tuning the scale factor, on the run, without any user intervention. The adaptation strategy is based on the fltness function value of individuals in DE population. The feasibility, e-ciency and efiectiveness of the proposed algorithm in the fleld of electromagnetism are examined over a set of well-known antenna conflgurations optimization problems. Comparison with the some very popular and powerful metaheuristics re∞ects the superiority of this simple parameter automation strategy in terms of accuracy, convergence speed, and robustness.