Mutation effects on BBO evolution in optimizing Yagi-Uda antenna design

Abstract

Biogeography-Based Optimization (BBO) is one of the recently developed population based algorithms which has shown impressive performance over other Evolutionary Algorithms (EAs). BBO is based on the study of geographical distribution of biological organism over space and time. The solutions for problem under consideration are named as habitats whereas features sharing among them is called migration. Migration operation is carried out by copying the value(s) of constituent variables, termed as Suitability Index Variables (SIVs), from one to another candidate solution, i.e. habitat, based on Habitat Suitability Index (HSI). Migration may lead to same types of habitats that number is to be reduced with the help of mutation operator. Mutation is a probabilistic operator that randomly modifies SIVs based on the habitats a priori species count. Therefore, mutation operator plays a very vital role in BBO convergence. In this paper, BBO algorithm is applied to optimize the length and spacing for Yagi-Uda antenna for maximum gain with different mutation options. The results obtained with mutation operators and rates are compared for faster convergence of BBO algorithm and the best results are tabulated in the ending sections of the paper.