The hybrid implementation genetic algorithm with particle swarm optimization to solve the unconstrained optimization problems

Genetic algorithm (GA) has an advantage in exploration search. Particle swarm optimization (PSO) has an advantage in sharing movement information between particles. The combining between GA and PSO is proposed in this research. We design hybrid-GA with PSO, and compare the performance with simple GA and simple PSO, which their models will find the solution of five-difference complexity of numerical functions. The experiment result showed that hybrid GA with PSO can find the solution of a multimodal problem and unimodal with noise signal quickly. © 2012 IEEE.