基于模拟退火算法的可逃逸粒子群算法

Escapable particle swarm optimization based on simulated annealing algorithm

通过引入模拟退火算法来保证PSO的全局收敛性,在群体最优信息陷入停滞时引入位置逃逸机制保持前期搜索速度快的特性。仿真结果表明本算法不但具有好的全局收敛性,而且有好的收敛速度。

This paper guaranteed to converge to the globe optimum by using the simulated annealing algorithm, when the optimum information of the warm was stagnant, the position escapable mechanism could maintain the characteristic of fast speed in the early convergence phase. Experimental simulations show that the proposed method can not only effectively converge to the globe optimum, but also significantly speed up the convergence.