Evolutionary Performance of Graded Emigration in BBO for Yagi-Uda Antenna Design Optimization

Biogeography Based Optimization (BBO) is one of the most popular swarm based optimization algorithms that has shown impressive performance over other Evolutionary Algorithms (EAs). A new algorithm is proposed in this paper by making migration variations in BBO, i.e., Graded Emigration Biogeography Based Optimization (GE-BBO) to improve the performance of BBO.Yagi-Uda is one of most widely antenna designs used at Very High Frequency (VHF) and Ultra High Frequency (UHF) due its high gain,low cost and constructional ease. Designing a Yagi-Uda antennainvolves determination of wire-element lengths and spacings in between them. Antenna geometry bear highly complex and nonlinear relationships with antenna gain, impedance and Single Lobe Level(SLL) at a particular frequency of operation. In this paper, a comparative study between BBO and GE-BBO is presented for faster optimization of antenna designs for maximum gain. The best antenna designs are tabulated and average of 10 monte-carlo simulations areplotted for these stochastic algorithms iterative performances in the ending sections.