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

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

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  • 国家科技期刊平台
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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 prob-lems(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 tra-verse the huge search space within reasonable resource as prob-lem dimension increases.Traditional evolutionary algorithms(EAs)tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satis-factory results.To reduce such evaluations,many novel surro-gate-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 compre-hensive 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 evolution-ary algorithms for HEPs from four main aspects.We also give comparative results of some representative algorithms and appli-cation examples.Finally,we indicate open challenges and several promising directions to advance the progress in evolutionary opti-mization algorithms for HEPs.

Evolutionary algorithm(EA)high-dimensional expensive problems(HEPs)industrial applicationssurrogate-assisted optimization

MengChu Zhou、Meiji Cui、Dian Xu、Shuwei Zhu、Ziyan Zhao、Abdullah Abusorrah

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Department of Electrical and Computer Engineering,New Jersey Institute of Technology,Newark,NJ 07102 USA

School of Information and Electronic Engineering,Zhejiang Gongshang University,Hangzhou 310018,China

School of Intelligent Manufacturing,Nanjing University of Science and Technology,Nanjing 210094,China

Institute of Systems Engineering,Macau University of Science and Technology,Macau 999078,China

School of Artificial Intelligence and Computer,Jiangnan University,Wuxi 214122,China

School of Information Science and Engineering,Northeastern University,Shenyang 110819,China

Center of Research Excellence in Renewable Energy and Power Systems,Department of Electrical and Computer Engineering,Faculty of Engineering,and K.A.CARE Energy Research and Innovation Center,King Abdulaziz University,Jeddah 21589,Saudi Arabia

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江苏省自然科学基金江苏省自然科学基金国家自然科学基金国家自然科学基金Institutional Fund Projects Provided by the Ministry of Education and King Abdulaziz UniversityFDCT(Fundo para o Desenvolvimento das Ciencias e da Tecnologia)

BK20230923BK202210676220611362203093IFPIP-1532-135-14430047/2021/A1

2024

10.1109/JAS.2024.124320

自动化学报(英文版)
中国自动化学会,中国科学院自动化研究所,中国科技出版传媒股份有限公司

自动化学报(英文版)

CSTPCDEI
ISSN：2329-9266
年,卷(期)：2024.11(5)
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