摘要
为提高多元宇宙优化算法求解实际问题的能力,提出了一种黏菌觅食的多元宇宙优化算法。该算法利用黏菌觅食行为在局部最优和全局最优之间寻求最优解。通过与其他10种同类算法在12个函数上的测试比较表明:本文算法收敛速度及解的质量优于其他算法,具有更好的求解能力和优化性能,可作为问题优化的有效工具。
In order to improve the ability of multi-verse optimization algorithm to solve practical problems,a modified multi-verse optimization algorithm with slime mould foraging is proposed. The algorithm uses slime foraging behavior to further seek optimal solutions between local optimum and global optimum. By comparing with 10 other similar algorithms tested on 12 benchmark-functions, the results show that the convergence speed and solution quality of the proposed algorithm in this paper are better than other algorithms, with better solving ability and optimization performance, and can be used as an effective tool for problem optimization.
作者
任丽莉
王志军
闫冬梅
REN Li-li;WANG Zhi-jun;YAN Dong-mei(High Performance Computing Center,Changchun Normal University,Changchun 130032,China;Big Data Network Management Center,Jilin University,Changchun 130012,China)
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2021年第6期2190-2197,共8页
Journal of Jilin University:Engineering and Technology Edition
基金
吉林省产业技术研究与开发项目(2021C045-4)
吉林省教育厅科学技术研究计划项目(JJKH20210886KJ)。
关键词
计算机应用
细菌觅食行为
多元宇宙优化算法
函数优化
computer applications
slime mould foraging behavior
multi-verse optimization(MVO)algorithm
function optimization
