摘要
针对基本微粒群算法的微分模型,从解的存在惟一性角度出发,发现最大速度常数虽然能保证解的存在性,但却降低了算法的全局搜索性能.为了提高算法的计算效率,提出了一种不含最大速度常数的微分模型,该模型首先将速度向量与位置向量等同对待,两者同时对空间进行搜索,并讨论了该模型解的稳定性条件,给出了相应的改进微粒群算法,能有效地提高算法效率.仿真结果证明了算法的有效性.
Through mechanism analysis of differential model of particle swarm optimization, the effect of the maximum speed constant is analyzed and the results are shown that can guarantee the existence of solution, but decrease the global search capability. A new broaden differential model is proposed, which treats the velocity and position vectors equally and searches the space at the same time. And the stability condition is also discussed, Thus a new modified particle swarm optimization algorithm is given. The optimization computing of some examples is made to show that the new algorithm has better global search capacity and rapid convergence rate.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2006年第4期646-653,共8页
Journal of Computer Research and Development
基金
教育部科学技术研究重点项目(204018)
关键词
微粒群算法
微分模型
速度向量
稳定性
particle swarm optimization
differential model
speed vector
stability
