HUANG Yan,WU Zezhong.An Improved Whale Algorithm based on Lévy Flight[J].Journal of Chengdu University of Information Technology,2021,36(01):24-31.[doi:10.16836/j.cnki.jcuit.2021.01.005]
基于Lévy飞行的一种改进鲸鱼算法
- Title:
- An Improved Whale Algorithm based on Lévy Flight
- 文章编号:
- 2096-1618(2021)01-0024-08
- Keywords:
- applied mathematics; optimization algorithm; whale optimization algorithm; normal mutation operator; lévy flight
- 分类号:
- TP301.6
- 文献标志码:
- A
- 摘要:
- 针对鲸鱼优化算法种群初始位置不均匀、后期容易陷入局部搜索,以及收敛精度慢较差等情况,利用正态变异方案提高收敛速度与收敛精度。利用基于正弦函数的螺旋更新位置与非线性改进策略相互配合提高全局搜索能力。最后,使用Lévy航行战略在迭代后期增强全局搜查才能,使算法收敛到最优解。再选取23个测试函数对算法收敛速度与收敛精度进行研究。实验结果表明,LMWOA算法在收敛精度上是优于原始算法及本文选取的对比算法,阐明LMWOA算法有显著的改进成果。
- Abstract:
- In order to improve the convergence speed and convergence accuracy of whale optimization algorithm,the normal variation scheme is used to solve the following problems: the initial position of whale population is not uniform,it is easy to fall into local search later,and the convergence accuracy is slow. The sinusoidal updating strategy and the nonlinear improving strategy are used to improve the global searching capability. Finally,Lévy navigation strategy is used to enhance the global search ability in the late iteration to make the algorithm converge to the optimal solution. In addition,23 test functions are selected to study the convergence speed and accuracy of the algorithm. Experimental results show that LMWOA algorithm is superior to the original algorithm and the comparison algorithm selected in this paper in convergence accuracy,and LMWOA algorithm has significant improvement results.
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备注/Memo
收稿日期:2020-07-27
基金项目:国家自然科学基金资助项目(71672013)