A share historical and global best particle swarm optimization algorithm
Zhigang Lian, Hu Keyi, Jiang Zhibin, Zheng Dongbiao · 2011
This article advances a share historical and global best particle swarm optimization algorithm (SGHPSO). In SGHPSO model, particles fully inherit the information of historical and global optimum particles in previous operation, which increases the search efficiency of particles. Ten typical nonlinear functions are given to test the efficiency of the improved algorithm. Simulation results clearly demonstrate superiority of the improved algorithm.