摘要
为了提高烟花算法的性能,先分析目标函数中的两种欺骗性进化方向,接着给出烟花算法的一个改进版本:基于种群进化速度的动态烟花算法.在改进算法中,参数z根据种群进化速度动态改变.改进算法只改进了烟花算法中参数z的更新方式,没有改变烟花算法的结构,因此那些基于烟花算法改进的算法,可以方便的移植到本文的改进算法中.在9个标准测试函数上的实验表明,该改进算法在搜索精度方面超过原始烟花算法.
In order to enhance the performance of FA, this paper firstly analysed the two deceptive directions in objective function, then accordingly proposed an enhanced version of FA named Dynamic Fireworks Algorithm based on population evolution velocity（DFA）. The parameter z in DFA changes dynamicly according to the population evolution velocity. DFA only changed parameter z＇s updating strategy without changing the structure of FA, thus the improved algorithm based on FA can be transplanted to DFA conveniently. Experimental evaluation on nine benchmark functions shows that DFA outperforms conventional FA in global solution accuracy capabilities.
出处
《微电子学与计算机》
CSCD
北大核心
2016年第10期24-27,共4页
Microelectronics & Computer
关键词
烟花算法
爆炸半径
群体智能
函数优化
fireworks algorithm
explosion amplitude
swarm intelligenee
function optimization
