In view of the limitation of the current kinds of particle swarm optimization(PSO) algorithm, a self-adaptive learning of hybrid strategy algorithm based on parallel particle swarm optimization(HLPSO) is proposed. The algorithm combines four strategies reasonably in the different point of view: Convergence, jump out, exploration and exploitation, which chooses an appropriate strategies to solve the different forms of problems through adjusting the probability of the strategies gradually in the process of optimizing. Moreover, simulation experiment on a suite of 7 benchmark functions is given, ...
