计算机工程与应用2026，Vol.62Issue(16)：42-57,16.DOI:10.3778/j.issn.1002-8331.2509-0104
面向昂贵优化问题的代理辅助进化算法综述
Review of Surrogate-Assisted Evolutionary Algorithms for Expensive Optimization Problems
摘要
Abstract
Many practical engineering problems can be categorized as expensive optimization problems(EOPs),charac-terized by high and sometimes prohibitive costs associated with evaluating candidate solutions.Surrogate-assisted evolu-tionary algorithms(SAEAs)have gained attention in recent years as a solution to EOPs due to their ability to reduce com-putational costs and increase solving efficiency.This paper provides a systematic overview of the research achievements in SAEAs from both algorithmic and application perspectives.It starts by explaining the necessity of studying SAEAs,then introduces several commonly used surrogate models.Next,it classifies and discusses existing SAEAs according to the problem types.Additionally,it summarizes current applications of SAEAs across various fields.Finally,it highlights the current challenges in SAEAs and offers insights into future trends and research directions in this field.关键词
昂贵优化问题/代理辅助进化算法/机器学习/协同进化/代理模型Key words
expensive optimization problem/surrogate-assisted evolutionary algorithm(SAEA)/machine learning/co-evolution/surrogate model分类
信息技术与安全科学引用本文复制引用
姚佳兴,季新芳,王晓峰,贾璟伟..面向昂贵优化问题的代理辅助进化算法综述[J].计算机工程与应用,2026,62(16):42-57,16.基金项目
宁夏自然科学基金(2024AAC03169,2024AAC03167) （2024AAC03169,2024AAC03167）
国家自然科学基金(62563001) （62563001）
北方民族大学青年人才培育项目(2024QNPY04) （2024QNPY04）
广东省基础与应用基础研究基金(2022A1515110055) （2022A1515110055）
中央高校基本科研业务费专项资金(FRF-TP-22-030A1). （FRF-TP-22-030A1）
