Abstract
Biogeography is the study of distribution of biological species, over space and time, among random habitats. Recently developed Biogeography-Based Optimization (BBO) is a technique in which solutions of the problem under consideration are named habitats; just as there are chromosomes in genetic algorithms (GAs) and particles in Particle Swarm Optimization (PSO). Feature sharing among various habitats in other words, exploitation, is made to occur because of the migration operator, whereas exploration of new SIV values, similar to that of GAs, is accomplished with the mutation operator. In this study, the nondominated sorting BBO (NSBBO) and various migration variants of the BBO algorithm, reported to date, are investigated for multiobjective optimization of six-element Yagi–Uda antenna designs to optimize two objectives, viz., gain and impedance, simultaneously. The results obtained with these migration variants are compared, and the best and the average results are presented in the concluding sections of the article.
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