An emigration genetic algorithm and its application to multiobjective optimal designs of electromagnetic devices

Yuhuai Wang; Shiyou Yang; Guangzheng Ni; Siu Lau Ho; Z. J. Liu

doi:10.1109/TMAG.2004.824780

An emigration genetic algorithm and its application to multiobjective optimal designs of electromagnetic devices

Yuhuai Wang, Shiyou Yang, Guangzheng Ni, Siu Lau Ho, Z. J. Liu

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

Abstract

The emigration genetic algorithm, which is a genetic-based algorithm, is proposed to obtain the Pareto optimal solution of vector optimal designs of electromagnetic devices. The proposed algorithm differs from the traditional ones in its design of an emigration operator as well as the inclusion of some useful approaches such as the fitness sharing, clustering, and elitism strategy. Detailed numerical results on three different multiobjective design problems are reported to demonstrate the effectiveness and advantages of the proposed algorithm for solving practical engineering multi-objective optimal design problems.

Original language	English
Pages (from-to)	1240-1243
Number of pages	4
Journal	IEEE Transactions on Magnetics
Volume	40
Issue number	2 II
DOIs	https://doi.org/10.1109/TMAG.2004.824780
Publication status	Published - 1 Mar 2004

Keywords

Emigration operator
Genetic algorithm (GA)
Numerical method
Vector optimization

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

More information

10.1109/TMAG.2004.824780

http://hdl.handle.net/10397/1109

Cite this

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AU - Wang, Yuhuai

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AU - Ni, Guangzheng

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AU - Liu, Z. J.

PY - 2004/3/1

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AB - The emigration genetic algorithm, which is a genetic-based algorithm, is proposed to obtain the Pareto optimal solution of vector optimal designs of electromagnetic devices. The proposed algorithm differs from the traditional ones in its design of an emigration operator as well as the inclusion of some useful approaches such as the fitness sharing, clustering, and elitism strategy. Detailed numerical results on three different multiobjective design problems are reported to demonstrate the effectiveness and advantages of the proposed algorithm for solving practical engineering multi-objective optimal design problems.

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KW - Genetic algorithm (GA)

KW - Numerical method

KW - Vector optimization

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JO - IEEE Transactions on Magnetics

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An emigration genetic algorithm and its application to multiobjective optimal designs of electromagnetic devices

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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