This research article studies the performance of three metaheuristics processes: Particle Swarm Optimization (PSO), Biogeography Based Optimization (BBO) and Hybrid BBO_PSO approach for FIR filter design. The three approaches employ different strategies and computational effort to find a solution to a given objective function. BBO is more recently proposed population-based search method than PSO. Some researchers believed in the convergence superiority of BBO over the PSO and approved it due to its capacity to solve complex problems due to its ease of implementation. In this paper, for FIR filter design PSO, BBO and BBO_PSO schemes are compared. BBO_PSO generally outperform standard PSO and BBO schemes. The study also underlines the importance of introducing hybridization of two heuristics optimizations to make them more efficient. Furthermore, it establishes the potential complementary of the approaches while solving this optimization problem.