This research focuses on the performance comparison of real-coded Genetic Algorithms (GA) and Biogeography-based Optimisation (BBO) algorithms. Specifically, it takes three modified versions of the original algorithms made suitable for continuous operations (real-coded) – the standard real-coded genetic algorithm (SRCGA), the real-coded genetic algorithm with mathematical projection (RCGA-P) and the real coded-biogeography-based optimization algorithm (RCBBO); then conducts a performance-based comparison of these three with respect to convergence, speed and robustness criteria. This comparison was done using 52 standard optimisation benchmark problems over four, ten and twenty dimensions. Results show that overall, SRCGA outperforms the others for speed while RCGA-P was the most robust of the three. The major value-add in performance of RCBBO was mainly from speed as in two dimensions, it delivers better speed than the two real-coded GA