上海工程技术大学 机构 管理学院,上海,201620
纸质出版:2019
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肖子雅, 刘升. 黄金正弦混合原子优化算法[J]. 微电子学与计算机, 2019, 36(6): 21-25, 30.
XIAO Zi-ya, LIU Sheng. Atom search optimization based on golden-sine algorithm[J]. 2019, 36(6): 21-25.
原子优化算法是一种基于分子动力学模型的新型智能算法
针对基本原子优化算法收敛速度慢以及易陷入局部最优的局限性
本文将黄金正弦作为局部优化算子嵌入到基本算法中
提出了黄金正弦原子优化算法.原子个体通过黄金正弦操作可以与最优个体进行充分的信息交流
有效改善基本算法的寻优方式
提高算法的收敛速度和寻优精度.通过实验表明
改进后的原子优化算法具有更好的寻优性能.
Atom search optimization is a new intelligent algorithm based on molecular dynamics model. In order to Improve convergence race and overcome the shortcoming of the atom search optimization which is easy to fall into the local extremum and easy to premature convergence
atom search optimization based on Golden-sine algorithm was proposed.It designs golden sine algorithm as a local optimization operator to optimizing the atom agent. The improved algorithm make each atom agent fully absorb information from the best agent
which effectively improve the optimization way of ASO and improve the convergence and accuracy of the optimization. Experiments show that the improved atom optimization algorithm has better performance.
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