Lanzhou University of Technology Institutional Repository (LUT_IR)
A hierarchical guidance strategy assisted fruit fly optimization algorithm with cooperative learning mechanism | |
Zhao, Fuqing1; Ding, Ruiqing1; Wang, Ling2; Cao, Jie1; Tang, Jianxin1 | |
2021-11-30 | |
发表期刊 | EXPERT SYSTEMS WITH APPLICATIONS |
ISSN | 0957-4174 |
卷号 | 183 |
摘要 | The fruit fly optimization algorithm (FOA) has drawn enormous attention from researchers and practitioners in the computation intelligence domain for the benefits of simple implementation mechanism and few parameters tuning requirement of FOA. However, FOA is hard to adapt directly to address complex continuous problems. A hierarchical guidance strategy assisted fruit fly optimization algorithm with cooperative learning mechanism (HGCLFOA) is proposed in this study. The population is divided into elitist and inferior subpopulations with the fitness of objective function. The population center is re-designed as an elitist subpopulation to maintain the diversity of the population. In the olfaction search stage, the hierarchical guidance strategy is introduced for local search according to the difference of solution qualities to assign inferior individuals to elitist individuals on different levels. Meanwhile, the inferior information is applied by the inferior solutions repairing strategy to deflect the prediction of the elitist subpopulation for preventing HGCLFOA from falling into the local optimum. In the vision search stage, a hybrid Gaussian distribution estimation strategy is adopted to extract the elitist information of previous generations to predict the distribution of potential elitist individuals in the next generation. The exploration and exploitation of the HGCLFOA are balanced by the cooperation between elitist subpopulation and inferior subpopulation. A random walk strategy is activated to assist the elitist solutions to jump out the local optimal. The parameters of the HGCLFOA are calibrated by DOE and ANOVA methods. The experimental results demonstrated that the HGCLFOA outperformed the classical FOA and state-of-arts variants of FOA. |
关键词 | Fruit fly optimization algorithm Gaussian distribution estimation algorithm Hierarchical guidance Cooperative learning mechanism |
DOI | 10.1016/j.eswa.2021.115342 |
收录类别 | EI ; CCF ; SCOPUS ; SCIE |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering ; Operations Research & Management Science |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science |
WOS记录号 | WOS:000694989100007 |
出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
EI入藏号 | 20212410510976 |
EI主题词 | Optimization |
EI分类号 | 723.4.2 Machine Learning - 821.4 Agricultural Products - 921.5 Optimization Techniques - 922.1 Probability Theory - 922.2 Mathematical Statistics |
来源库 | WOS |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/148783 |
专题 | 国际合作处(港澳台办) 计算机与通信学院 |
通讯作者 | Zhao, Fuqing |
作者单位 | 1.Lanzhou Univ Technol, Sch Comp & Commun Technol, Lanzhou 730050, Peoples R China; 2.Tsinghua Univ, Dept Automat, Beijing 10084, Peoples R China |
第一作者单位 | 兰州理工大学 |
通讯作者单位 | 兰州理工大学 |
第一作者的第一单位 | 兰州理工大学 |
推荐引用方式 GB/T 7714 | Zhao, Fuqing,Ding, Ruiqing,Wang, Ling,et al. A hierarchical guidance strategy assisted fruit fly optimization algorithm with cooperative learning mechanism[J]. EXPERT SYSTEMS WITH APPLICATIONS,2021,183. |
APA | Zhao, Fuqing,Ding, Ruiqing,Wang, Ling,Cao, Jie,&Tang, Jianxin.(2021).A hierarchical guidance strategy assisted fruit fly optimization algorithm with cooperative learning mechanism.EXPERT SYSTEMS WITH APPLICATIONS,183. |
MLA | Zhao, Fuqing,et al."A hierarchical guidance strategy assisted fruit fly optimization algorithm with cooperative learning mechanism".EXPERT SYSTEMS WITH APPLICATIONS 183(2021). |
条目包含的文件 | 条目无相关文件。 |
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