Evolutionary Optimization Methods for High-Dimensional Expensive Problems: A Survey
文献类型：期刊论文
| 作者 | MengChu Zhou; Meiji Cui; Dian Xu; Shuwei Zhu; Ziyan Zhao; Abdullah Abusorrah |
| 刊名 | IEEE/CAA Journal of Automatica Sinica
 |
| 出版日期 | 2024 |
| 卷号 | 11期号:5页码:1092-1105 |
| 关键词 | Evolutionary algorithm (EA) high-dimensional expensive problems (HEPs) industrial applications surrogate-assisted optimization |
| ISSN号 | 2329-9266 |
| DOI | 10.1109/JAS.2024.124320 |
| 英文摘要 | Evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization problems. The past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems (HEPs). The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer simulations. Moreover, it is hard to traverse the huge search space within reasonable resource as problem dimension increases. Traditional evolutionary algorithms (EAs) tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satisfactory results. To reduce such evaluations, many novel surrogate-assisted algorithms emerge to cope with HEPs in recent years. Yet there lacks a thorough review of the state of the art in this specific and important area. This paper provides a comprehensive survey of these evolutionary algorithms for HEPs. We start with a brief introduction to the research status and the basic concepts of HEPs. Then, we present surrogate-assisted evolutionary algorithms for HEPs from four main aspects. We also give comparative results of some representative algorithms and application examples. Finally, we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HEPs. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/55701]  |
| 专题 | 自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica |
| 推荐引用方式 GB/T 7714 | MengChu Zhou,Meiji Cui,Dian Xu,et al. Evolutionary Optimization Methods for High-Dimensional Expensive Problems: A Survey[J]. IEEE/CAA Journal of Automatica Sinica,2024,11(5):1092-1105. |
| APA | MengChu Zhou,Meiji Cui,Dian Xu,Shuwei Zhu,Ziyan Zhao,&Abdullah Abusorrah.(2024).Evolutionary Optimization Methods for High-Dimensional Expensive Problems: A Survey.IEEE/CAA Journal of Automatica Sinica,11(5),1092-1105. |
| MLA | MengChu Zhou,et al."Evolutionary Optimization Methods for High-Dimensional Expensive Problems: A Survey".IEEE/CAA Journal of Automatica Sinica 11.5(2024):1092-1105. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。