Solving Multi-Objective Problems Using Bird Swarm Algorithm

This paper introduces an effective method by combining the multi-objective technique with bird swarm algorithm (BSA) to obtain a new called MBSA. The MBSA obtains some of different non-dominated techniques that maintain variety amongst optimal solutions. To verify and evaluate effectiveness MBSA, collections constrained, unconstrained, engineering problems are measured. These have various Pareto front (PF) properties, including non-convex, convex, discrete PFs. results show has good ability both better solution spread convergence near true PF. Furthermore, quantitative qualitative indicate provides high in all experiments real-world against well-known algorithms literature.