改进的混合粒子群算法

为了能够有效避免搜索过程陷入局部最优,从而增强全局搜索能力,提出一种基于模拟退火的粒子群算法.算法中引入遗传算法中常用的轮盘赌选择算子,能在早期抑制部分超级粒子对种群的控制,增加了群体的多样性.通过测试函数的比较表明,混合算法能很好地保持种群多样性,具有良好的计算精度和全局寻优能力.

Improved Hybrid Particle Swarm Optimization Algorithm

On the basis of simulated annealing,a particle swarm algorithm was put forward to enhances the ability of global searching.The algorithm combines with the roulette wheel selection operator,which provides a mechanism to restrain the predominating of super particles in early stage and can effectively avoid the premature problem.Variety experiments are conducted on several test functions taken from the literature.The simulation results show that the algorithm has better probability of finding global optimum and mean best value and has faster convergence and maintains the population diversity in the process of evolution.