一种新的融合粒子群算法的混合蟑螂群算法

A New Hybrid Cockroach Swarm Optimization Fuse with Particle Swarm Optimization

针对连续蟑螂算法存在初始解质量不高和算法评价次数过多的问题,提出了一种融合了粒子群算法的混合蟑螂群算法并应用于函数优化问题。首先由基本粒子群算法快速收敛到解空间内一个相对优的解,然后由一种改进的蟑螂算法完成全局寻优。仿真结果显示:混合蟑螂算法具有收敛速度快、求解精度高的特点,其算法整体性能优于已存在的连续蟑螂算法。

In order to overcome the problems of continuous cockroach swarm optimization （CCSO） , such as the low precision solution and too much function evolutions, a hybrid cockroach swarm optimization （HCSO） is proposed and applied to address function optimization problems. First, the PSO is used to converge to a solution of search space. And then, an improved cockroach swarm optimization is used to search global optimal solution. The experimental results show that HCSO has the characters of high solving precision and convergent rate, which performance is superior to that of CCSO.