Optimization of antenna configuration with a fitness-adaptive differential evolution algorithm

In this article, a novel numerical technique, called Fitness Adaptive Differential Evolution (FiADE) for optimizing certain pre-defined antenna configuration to attain best possible radiation characteristics is presented. Differential 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 fitness function value of individuals in DE population. The feasibility, efficiency and effectiveness of the proposed algorithm in the field of electromagnetism are examined over a set of well-known antenna configurations optimization problems. Comparison with the some very popular and powerful metaheuristics reflects the superiority of this simple parameter automation strategy in terms of accuracy, convergence speed, and robustness.