A modified particle swarm optimization with multiple subpopulations for multimodal function optimization problems

- This paper shows a modified particle swarm optimization (PSO) algorithm with multiple subpopulations for solving multimodal function optimization problems.
- The best particle within each subpopulation is recorded and then applied into the velocity updating formula to update all particles in each subpopulation.
- To show the efficiency of the proposed method, two kinds of function optimizations including a single modal function optimization and a complex multimodal function optimization are provided.
- Simulation results will demonstrate the convergence behavior of particles by the number of iterations, and the global and local system solutions are solved by these best particles of subpopulations.