探索者变异樽海鞘算法及其应用
Explorer Variation Salp Swarm Algorithm and Its Application
李辉 1殷文明1
作者信息
- 1. 福建水利电力职业技术学院,福建 永安 366000;福建水利电力职业技术学院院士专家工作站,福建永安 366000
- 折叠
摘要
针对樽海鞘算法搜索性能不高的缺陷,提出探索者变异樽海鞘算法,将种群分为领导者、跟随者和探索者三部分,通过改进跟随者更新策略并引进探索者变异机制,提高算法搜索性能.数值实验表明,该算法搜索速度和精度比基本算法和文献中的算法都有大幅度提高.将该算法应用于压力容器设计问题进行参数优化,得到了明显改善的最优成本.
Abstract
in view of the low search performance of the salp swarm algorithm,the explorer variation salp swarm algorithm is proposed,which divides the population into three parts:leader,followers and explorers.By improving the update strategy of followers and introduc-ing the explorer variation mechanism,the search performance of the algorithm is improved.Numerical experiments show that the search speed and accuracy of this algorithm are signif-icantly higher than the basic algorithm and the algorithm in the literature.The algorithm is applied to the pressure vessel design problem for parameter optimization,and the optimal cost is significantly improved.
关键词
樽海鞘算法/探索者变异/压力容器设计Key words
salp swarm algorithm/explorer variation/pressure vessel design引用本文复制引用
基金项目
福建省教育厅资助项目(JAT201136)
出版年
2024
NETL
NSTL
万方数据