Structural topology optimization of magnetic actuators using genetic algorithms and ON/OFF sensitivity

Jae Seok Choi, Jeonghoon Yoo

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

In genetic algorithm (GA) based topology optimization problems, characteristics of an initial population are important for the rapid and stable convergence. This paper introduces an algorithm generating randomly an initial population with superior hereditary characteristics. To avoid the generation of small structural spots, the blurring technique is proposed. The connectivity of seed elements considerging the magnetic flux flow in the design domain is focused. Differently from the classical GA by linear strings, this study deals with two-dimensonal chromosomes and the geographic crossover method to increase the diversity of offspring. The proposed design algorithm is applied to the yoke optimization of magnetic actuators.

Original languageEnglish
Article number4816002
Pages (from-to)2276-2279
Number of pages4
JournalIEEE Transactions on Magnetics
Volume45
Issue number5
DOIs
Publication statusPublished - 2009 May 1

Fingerprint

Magnetic actuators
Structural optimization
Shape optimization
Genetic algorithms
Magnetic flux
Chromosomes
Seed

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

Cite this

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Structural topology optimization of magnetic actuators using genetic algorithms and ON/OFF sensitivity. / Choi, Jae Seok; Yoo, Jeonghoon.

In: IEEE Transactions on Magnetics, Vol. 45, No. 5, 4816002, 01.05.2009, p. 2276-2279.

Research output: Contribution to journalArticle

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