首页|期刊导航|复杂系统建模与仿真（英文）|Novel Consensus-Based Particle Swarm Optimization-Guided Surrogate-Enhanced Methodology for Solving Expensive Black-Box Optimization

Novel Consensus-Based Particle Swarm Optimization-Guided Surrogate-Enhanced Methodology for Solving Expensive Black-Box Optimization

Yongfeng Zhang Zhihao Liu Kaili Jia Zhenbin Zhang Hsiaodong Chiang

复杂系统建模与仿真（英文）2025，Vol.5Issue(4)：340-353,14.

复杂系统建模与仿真（英文）2025，Vol.5Issue(4)：340-353,14.DOI:10.23919/CSMS.2025.0006

Novel Consensus-Based Particle Swarm Optimization-Guided Surrogate-Enhanced Methodology for Solving Expensive Black-Box Optimization

Yongfeng Zhang ¹Zhihao Liu ²Kaili Jia ³Zhenbin Zhang ⁴Hsiaodong Chiang⁵

作者信息

1. School of Electrical Engineering,University of Jinan,Jinan 250022,China
2. School of Information Science and Technology,University of Jinan,Jinan 250022,China
3. State Grid Liaocheng Power Supply Company,Liaocheng 252000,China
4. School of Electrical Engineering,Shandong University,Jinan 250061,China
5. School of Electrical and Computer Engineering,Cornell University,Ithaca,NY 14853,USA
折叠

摘要

关键词

black box optimization/consensus-based particle swarm optimization/local cheap surrogate model/high-quality optimal solutions

Key words

black box optimization/consensus-based particle swarm optimization/local cheap surrogate model/high-quality optimal solutions

引用本文复制引用

Yongfeng Zhang,Zhihao Liu,Kaili Jia,Zhenbin Zhang,Hsiaodong Chiang..Novel Consensus-Based Particle Swarm Optimization-Guided Surrogate-Enhanced Methodology for Solving Expensive Black-Box Optimization[J].复杂系统建模与仿真（英文）,2025,5(4):340-353,14.

基金项目

This work was supported in part by the Shandong Province Higher Educational Youth and Innovation Talent Introduction and Education Program,National Key R&D Program of China(No.2022YFB4201700),and Science Fund for Distinguished Young Scholars of Shandong Province(No.ZR2023JQ020). （No.2022YFB4201700）

复杂系统建模与仿真（英文）

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