摘要
研究标准粒子群优化算法在经验区域的各个子区域内的收敛和发散行为,分析系统特征根与算法参数的关系,得到一系列结论.数值仿真实验展示不同子区域内的算法参数对粒子位置和粒子速度运动轨迹的不同影响,进一步验证本文结论的正确性.
The convergence and divergence properties of the standard particle swarm optimization algorithm are studied in detail. At the same time, the relationship between the characteristic roots and algorithm parameters are analyzed. A series of conclusions are deduced. Finally,numerical simulation demonstrates the different effects of different algorithm parameters on the loci of particle position and particle velocity,which further illustrates the validity of conclusions given in this paper.
出处
《应用数学》
CSCD
北大核心
2011年第1期187-194,共8页
Mathematica Applicata
基金
Supported by National Natural Science Foundation of China (60672057,60471012)
关键词
标准粒子群优化
粒子收敛
参数选择
特征根
数值仿真
Standard particle swarm optimization
Particle convergence
Parameterselection
Characteristic root
Numerical simulation
