An efficient multiobjective optimizer based on genetic algorithm and approximation techniques for electromagnetic design

Siu Lau Ho, S. Y. Yang, G. Z. Ni, K. F. Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

To provide an efficient multiobjective optimizer, an approximation technique based on the moving least squares approximation is integrated into an improved genetic algorithm. In order to use fully, both the a posteriori information gathered from the latest searched nondominated solutions and the a priori knowledge about the search space and individuals, in guiding the search towards more and better Pareto solutions, a gradient direction based perturbation search strategy and a preference function based fitness penalization scheme are proposed. Numerical results are reported to validate the proposed work.
Original languageEnglish
Pages (from-to)1605-1608
Number of pages4
JournalIEEE Transactions on Magnetics
Volume43
Issue number4
DOIs
Publication statusPublished - 1 Apr 2007

Keywords

  • Approximation technique
  • Evolutionary computation
  • Genetic algorithm (GA)
  • Multiobjective optimization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Physics and Astronomy (miscellaneous)

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