A Hybrid Algorithm Based on NSGA-II and MOPSO for Multi-objective Designs of Electromagnetic Devices

被引：1

作者：

Li Yilun ^{[1
]}

Xie Zhengwei ^{[1
]}

Yang Shiyou ^{[2
]}

Ren Zhuoxiang ^{[3
]}

机构：

[1] Donghua Univ, Sch Informat Sci & Technol, Shanghai, Peoples R China

[2] Zhejiang Univ, Coll Elect Engn, Hangzhou, Peoples R China

[3] Sorbonne Univ, Grp Elect & Elect Engn Paris, Paris, France

来源：

TWENTIETH BIENNIAL IEEE CONFERENCE ON ELECTROMAGNETIC FIELD COMPUTATION (IEEE CEFC 2022) | 2022年

关键词：

Multi-objective optimization; electromagnetic optimization; evolutionary algorithms; TEAM; 22; benchmark;

D O I：

10.1109/CEFC55061.2022.9940652

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, a hybrid algorithm is proposed by combining the NSGA-II with MOPSO algorithm. The original NSGA-II is improved by adopting dynamical selection of crossover and mutation operators. The performance of the proposed hybrid algorithm is verified using standard test functions and it is applied to the multi-objective optimization benchmark problem TEAM 22. Numerical results demonstrate the effectiveness and superiority of the proposed hybrid algorithm.

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页数：2

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