计算机应用研究2025，Vol.42Issue(9)：2607-2613,7.DOI:10.19734/j.issn.1001-3695.2025.03.0037
一种基于行列式点过程的代理模型辅助多目标进化算法
Surrogate-assisted multi-objective evolutionary algorithm based on determinantal point processes
摘要
Abstract
To enhance the diversity and convergence of the solution set used for updating the surrogate models and thereby im-prove the accuracy of the surrogate models,this paper proposed an SAEA based on DPP.Firstly,this paper proposed a surrogate management method based on DPP.The method selected a subset from the non-dominated solution set using DPPs and evalua-ted solutions in the subset with the real objective functions,and then selected another subset from the set of all solutions evalua-ted by the real objective functions to update the surrogate models.Additionally,this paper proposed an environmental selection method based on adaptive DPP.The method focused on improving the convergence of the population in the early stages of the evolutionary process and enhancing the diversity of the population in the later stages.Finally,this paper verified the effective-ness of the proposed algorithm on DTLZ,WFG,and MAF test problems.This paper compared the proposed algorithm with com-monly used algorithms such as K-RVEA,KTA2,and CSEA using the IGD+metric.The experimental results show that the pro-posed algorithm can obtain a better solution set,thereby demonstrating its effectiveness in solving expensive multi-objective op-timization problems.关键词
代理辅助多目标优化/进化算法/模型管理/环境选择/行列式点过程/收敛性/多样性Key words
surrogate-assisted multi-objective optimization/evolutionary algorithm/surrogate management/environmental se-lection/determinantal point processes/convergence/diversity分类
信息技术与安全科学引用本文复制引用
吴子聪,李金龙..一种基于行列式点过程的代理模型辅助多目标进化算法[J].计算机应用研究,2025,42(9):2607-2613,7.基金项目
国家自然科学基金面上项目(61573328) （61573328）
