基于粒子群算法的布谷鸟搜索算法

Cuckoo search algorithm based on particle swarm optimization algorithm

为进一步提高布谷鸟搜索算法(Cuckoo Search)的收敛速度和计算精度,将PSO算法用于CS算法的位置更新过程,提出了基于PSO算法的布谷鸟搜索算法(CSPSO).最后,通过6个典型测试函数进行仿真实验.结果表明,CSPSO算法比CS算法和自适应步长布谷鸟搜索算法(ASCS)具有更快的收敛速度,更高的收敛精度和稳定性.

In order to make further improvement on the convergence speed and computational accuracy of cuckoo search algorithm ,a new cuckoo search algorithm based on particle swarm optimization algorithm is propased ,which uses particle swarm optimization instead of the original Levy flight mechanism into the location update process of CS algorithm .The simulation results show that the CSPSO can search for global optimization more quickly ,precisely and stably than original CS algorithm and self-adaptive step cuckoo search algorithm .