Evolutionary Optimization Methods for High-Dimensional Expensive Problems: A Survey

doi:10.1109/JAS.2024.124320

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	Evolutionary Optimization Methods for High-Dimensional Expensive Problems: A Survey
	MengChu Zhou; Meiji Cui; Dian Xu; Shuwei Zhu; Ziyan Zhao; Abdullah Abusorrah
发表期刊	IEEE/CAA Journal of Automatica Sinica
ISSN	2329-9266
	2024
卷号	11 期号:5 页码:1092-1105
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.
关键词	Evolutionary algorithm (EA) high-dimensional expensive problems (HEPs) industrial applications surrogate-assisted optimization
DOI	10.1109/JAS.2024.124320
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/55701
专题	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.

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