| 引用本文: | 陈雷,蔺悦,康志龙.基于衰减因子和动态学习的改进樽海鞘群算法[J].控制理论与应用,2020,37(8):1766~1780.[点击复制] |
| CHEN Lei,LIN Yue,KANG Zhi-long.Improved salp swarm algorithm based on reduction factor and dynamic learning[J].Control Theory and Technology,2020,37(8):1766~1780.[点击复制] |
|
| 基于衰减因子和动态学习的改进樽海鞘群算法 |
| Improved salp swarm algorithm based on reduction factor and dynamic learning |
| 摘要点击 2900 全文点击 832 投稿时间：2019-09-11 修订日期：2020-02-25 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2020.90766 |
| 2020,37(8):1766-1780 |
| 中文关键词 樽海鞘群算法 衰减因子 动态学习 群智能 优化算法 |
| 英文关键词 salp swarm algorithm reduction factor dynamic learning swarm intelligence optimization algorithm |
| 基金项目 国家自然科学基金项目(61401307), 河北省高等学校科学技术研究项目(ZD2018045), 天津市企业科技特派员项目(18JCTPJC57500)资助. |
|
| 中文摘要 |
| 樽海鞘群算法是一种新型的群智能优化算法. 与其他智能优化算法相比, 樽海鞘群算法的优化求解策略仍
有待改进, 以进一步提高该算法的求解精度和寻优效率. 本文提出一种基于衰减因子和动态学习的改进樽海鞘群算
法, 通过在领导者更新阶段添加衰减因子, 提高算法的局部开发能力, 在跟随者更新阶段引入动态学习策略, 提高算
法的全局搜索能力. 本文对16个测试函数进行实验, 将提出的改进算法与其他智能优化算法比较, 实验结果表明,
本文提出的改进算法在收敛精度和收敛速度方面有较大提升, 具有良好的优化性能. |
| 英文摘要 |
| Salp swarm algorithm is one of the most recently proposed swarm intelligent optimization algorithms. Compared
with other intelligent optimization algorithms, the optimization strategy of salp swarm algorithm needs to be improved
to enhance the convergence accuracy and speed. This paper proposes an improved salp swarm algorithm based on reduction
factor and dynamic learning. Firstly, reduction factor is added in the update stage of leader salps, in order to improve the
local exploitation ability. Next, dynamic learning strategy is imported in the update stage of follower salps, aiming to improve
the global search ability. In this paper, 16 test functions are conducted in the experiment of comparison between the
proposed improved algorithm and other intelligent optimization algorithms. The results show that the proposed improved
algorithm has a good improvement in convergence accuracy and speed, which has good optimization performance. |
|
|
|
|
|