计算机工程与应用2025，Vol.61Issue(22)：75-91,17.DOI:10.3778/j.issn.1002-8331.2501-0412
支持代理的元启发算法解决高维计算昂贵问题研究综述
Review of Surrogate-Assisted Meta-Heuristic Algorithms for High-Dimensional Computationally Expensive Optimization Problems
摘要
Abstract
High-dimensional and expensive optimization problems are widely present in fields such as energy and resource optimization,urban and environmental planning,industrial design and manufacturing,aerospace,communication and infor-mation,etc.The increasing of dimension leads to an expansion of the search space,while the computational expense limits the times that the true solution can be evaluated.The aforementioned reasons render traditional optimization algorithms ineffective.Surrogate-assisted meta-heuristic algorithms,which use surrogate models to replace the expensive real fitness evaluations and utilize meta-heuristic algorithms to guide the optimization direction,can significantly reduce computational time and cost while maintaining optimization accuracy.This paper,focusing on the characteristics of high-dimension and expensive computation in optimization problems,organizes recent literature on surrogate-assisted meta-heuristic algo-rithms from six perspectives:generating initial sample points,constructing and updating surrogate models,using evolu-tionary algorithms,balancing exploration and exploitation,designing adaptability,and practical applications.The paper summarizes how surrogate-assisted meta-heuristic algorithms address these two major challenges.Finally,it proposes future research directions for aspects that are currently under-researched.关键词
代理模型/元启发算法/高维度/计算昂贵优化问题/探索与开发Key words
surrogate model/meta-heuristic algorithm/high-dimension/computationally expensive optimization prob-lems/exploration and exploitation分类
信息技术与安全科学引用本文复制引用
王红,康玲,郭雨林..支持代理的元启发算法解决高维计算昂贵问题研究综述[J].计算机工程与应用,2025,61(22):75-91,17.基金项目
大连市科技局科技创新计划(2022JJ12GX017) （2022JJ12GX017）
辽宁省教育厅科学技术一般项目(LJ212413631007). （LJ212413631007）
