Research on Hybrid Improved PSO Algorithm

In order to overcome the inherent deficiency in particle swarm optimization algorithm such as premature convergence, this paper presents crossover operator and mutation operator to improve particle swarm optimization algorithm, which is called IPSO. At the meantime, a new hybrid algorithm model is presented, which combine improved PSO algorithm and simulated annealing (SA) algorithm. The experimental results show that the proposed algorithm can reach the goal completely and the speed of convergence was greatly fast for optimization of Sphere, Griewank and Rastrigrin functions. The stability and robustness of proposed algorithm have been enhanced greatly. Its performance is superior to the standard PSO obviously.

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