层次粒子群算法及其在优化问题上的研究

Hierarchy Particle Swarm Algorithm on Optimization Problem

使用粒子群优化算法解决最优化问题是解决优化问题的一个重要方面,针对标准粒子群算法易陷入局部最优的问题,在协作粒子群算法和标准粒子群算法的基础上,论文提出了一种层次协作粒子群算法。该算法使用多组协作粒子群算法组合的方式来提供跳出局部最优能力的。通过对9组Benchmark Functions进行仿真实验表明,该改进算法在优化精度和鲁棒性方面均优于PSO算法和CPSO-H6算法,对于解决优化问题是一种有效的方法。

The use of particle swarm optimization algorithm is an important way to solve the optimization problem.Aiming at the problem that the standard particle swarm algorithm is easy to fall into local optimum,a hierarchical cooperative particle swarm optimization algorithm is proposed based on the cooperative particle swarm algorithm and the standard particle swarm algorithm.The algorithm uses a combination of multi cooperative particle swarm algorithms to provide the ability of jumping out of local optima.Simulation results on nine Benchmark Functions show that the improved algorithm is superior to PSO algorithm and CPSO-H6 algorithm in optimizing accuracy and robustness,which is an effective method to solve the optimization problem.