摘要
针对基本粒子群优化算法对复杂函数优化时难以获得最优解的缺陷,提出了一种复形粒子群优化算法。该算法采用复形法来提高粒子的局部搜索能力,从而保证了算法能够跳出局部最优,获得全局最优解。实验结果表明,与文献算法相比,该算法在基准函数优化时具有更强的寻优能力和更高的搜索精度。
To improve the search quality of the standard PSO algorithm for solving complex function,this paper proposed a novel particle swarm optimization algorithm based on complex method.It improved the local search capability of particle by using complex method in proposed algorithm,so that proposed algorithm could jump out of local optimal,and obtained the global optimal solution.Simulations show that proposed algorithm has more powerful optimizing ability and higher optimizing precision in function optimization than literature algorithms.
出处
《计算机应用研究》
CSCD
北大核心
2012年第2期463-464,468,共3页
Application Research of Computers
关键词
粒子群优化算法
复形法
复形法粒子群算法
函数优化
particle swarm optimization algorithm
complex method
complex method particle swarm optimization algorithm
function optimization
