arrow
返回

Compound improved Harris hawks optimization for global and engineering optimization

delete2024-04-24
delete3
PRE
AI
C
Chengtian Ouyang
L
Liao Chang
D
Donglin Zhu
Y
Yangyang Zheng
C
Changjun Zhou *
C
Chengye Zou *
DOI:10.1007/s10586-024-04348-zdelete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Meta-heuristic algorithms, due to their high search speed and strong generalization ability, are frequently applied in programs mainly to discover the corresponding optimal strategy for any problem in view of their defined rules. After years of collision evolution, they have been continuously used to solve the complex, unordered and diverse optimization problems and improve efficiency. Aiming at the problems of low convergence accuracy and easy to fall into local optima of the traditional Harris hawks optimization algorithm, a compound improved Harris Hawks Optimization algorithm (CIHHO) is proposed. Firstly, the early circling exploration and later attack exploitation phase of the dynamic adjustment algorithm for environmental factors is introduced to regulate the energy of Harris hawks; Secondly, the concept of Versoria function is introduced to modify the random jump strength and raise the data grabbing ability of local space; Introducing the Levy flight function to adjust the factor and reduce the disturbance impact of Levy flight is beneficial for getting rid of the local space after entering the exploitation phase, and introducing random white noise to reduce step size and improve algorithm accuracy. Taking CEC 2017 test function suite set as the core, the performance of CIHHO algorithm is analyzed. Firstly, the performance of CIHHO algorithm is compared with HHO, HHO_JOS, LHHO, LMHHO and NCHHO. Secondly, the performance of unimodal function, multimodal function, mixed function and compound function is compared with other 7 improved algorithms. Finally, ablation experiments are carried out. The convergence value of the iterative curve obtained is more quantitative than the improved algorithm, The generality of the improved CIHHO algorithm in solving multiple optimization problems with different dimensions is verified. Further applying the CIHHO algorithm to three different engineering experiments, the minimum cost calculation results directly demonstrate that the CIHHO algorithm obtained has certain advantages in dealing with search space problems.
Keyword:
Compound improved Harris hawks optimization
Environmental factor
Versoria function
Levy flight

期刊

C
Cluster Computing-The Journal of Networks Software Tools and Applications
IF:
4.1
论文数:
5.1K
被引数:
7.5K

机构

J
jiangxi university of science & technology
学者数:
6.7K
论文数: 4.5K
被引数: 3
Y
Yanshan University
学者数:
1.7W
论文数: 1.1W
被引数: 1.3W
Z
Zhejiang Normal University
学者数:
1.3W
论文数: 8.4K
被引数: 1.2W
学者 查看更多机构
引用论文

引用论文

Hierarchical Harris hawks optimizer for feature selection用于特征选择的分层Harris hawks优化器
err2023-11-01
err41
errOAAI
errPeng, Lemin; Cai, Zhennao; Heidari, Ali Asghar; Zhang, Lejun; Chen, Huiling
err分享
err收藏
Decomposition and Harris hawks optimized multivariate wind speed forecasting utilizing sequence2sequence-based spatiotemporal attention
errENERGY
IF9.4
err2023-09-01
err8
PREAI
errBashir, Hassan; Sibtain, Muhammad; Hanay, Ozge; Azam, Muhammad Imran; Qurat-ul-Ain; Saleem, Snoober
err分享
err收藏
err分享
err收藏
err分享
err收藏
学者 查看更多内容