左仲亮, 郭星, 李炜. 一种新颖的改进萤火虫算法[J]. 微电子学与计算机, 2017, 34(9): 15-19.
引用本文: 左仲亮, 郭星, 李炜. 一种新颖的改进萤火虫算法[J]. 微电子学与计算机, 2017, 34(9): 15-19.
ZUO Zhong-liang, GUO Xing, LI Wei. An Original and Improved Swarm Optimization Alogorithm[J]. Microelectronics & Computer, 2017, 34(9): 15-19.
Citation: ZUO Zhong-liang, GUO Xing, LI Wei. An Original and Improved Swarm Optimization Alogorithm[J]. Microelectronics & Computer, 2017, 34(9): 15-19.

一种新颖的改进萤火虫算法

An Original and Improved Swarm Optimization Alogorithm

  • 摘要: 为了克服原始萤火虫算法(Glowworm swarm optimization, GSO)对于多峰函数寻优精度不高和后期收敛速度较慢的问题.为此, 本文针对性的提出了一种改进的动态步长自适应的萤火虫优化算法.采用该算法的改进思想, 能在一定的程度上避免算法因为过早的成熟而陷入局部最优, 并且改进的算法比原始萤火虫算法有着更好的收敛精度.Matlab实验仿真表明, 改进算法在一定程度上提高了收敛速度和寻优精度.

     

    Abstract: In order to overcome the basic artifical firefly algorithm(GSO) in solving problems of low precision for the multi peak function and slow convergence. Thus, this paper comes up with an original and improved Dynamic and adaptive step optimization algorithm. With it, This algorithm can avoid being mature and falling into a local value. As the same time, improved GSO can achieve a higher accuracy during Iterative process. According to the simulation experiment, it shows that to some extent, the improved algorithm on covergence speend and precision are enhanced.

     

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