结合SA算法的快速微粒群优化算法

Rapid partical swarm optimization combined simulated annealing algorithm

理论上已经证明PSO算法用所有微粒的当前位置与全体最好位置相同时算法停止作为收敛准则是有缺陷的,不能保证全局收敛。而已经证明模拟退火算法依概率1收敛于全局最优解集,因此可将模拟退火算法作为PSO算法的收敛判据。将模拟退伙算法和微利群优化算法结合起来,保证PSO算法的全局收敛性,提高了收敛的速度和效率。实验结果证明了其有效性。

Theory has proved that the convergence criterion of the algorithms ceasing is flawed when using the current location as the best location of all particles,and the global convergence is not guaranteed.Simulated annealing algorithm has been proven to be a global optimal solution set under the probability of 1,so the simulated annealing algorithm can be used as the convergence criterion of PSO algorithm.The paper combines the simulated annealing algorithm with the particle swarm optimization algorithm to ensure the global convergence of the PSO algorithm and improve the convergence speed and efficiency.Experimental results show its effectiveness.