Grid based dynamic particle population particle swarm optimization

Particle swarm optimization(PSO) is easy to be trapped by the local optimum. Therefore, the grid based dynamic particle population PSO (GB-DPPPSO) is proposed. GB-DPPPSO has three strategies, grid information update strategy, particle generalization strategy and particle vanishing strategy, which keep the diversity of swarm through convergence and enhance the global searching ability. Simulation tests on four benchmark functions prove that the method performs better than DPPPSO on global successful searching probability and searching efficiency.