Binary-based topology optimization of magnetostatic shielding by a hybrid evolutionary algorithm combining genetic algorithm and extended compact genetic algorithm

Yusuke Tominaga, Yoshifumi Okamoto, Shinji Wakao, Shuji Sato

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

Topology optimization using the binary information of magnetic material is one of the most attractive simulations for the conceptual design of electrical machines. Heuristic algorithms based on random search allow engineers to define general-purpose objects with various constraint conditions. However, it is difficult for topology optimization to realize a practical solution without island and void distribution. In this paper, we propose a hybrid evolutionary algorithm that is composed of a genetic algorithm (GA) and extended compact GA (ECGA). We verify the effectiveness of the proposed algorithm on the binary topology optimization problem for the design of magnetostatic shielding.

Original languageEnglish
Article number6514632
Pages (from-to)2093-2096
Number of pages4
JournalIEEE Transactions on Magnetics
Volume49
Issue number5
DOIs
Publication statusPublished - 2013 May 22

Keywords

  • Binary-based topology optimization
  • extended compact genetic algorithm
  • genetic algorithm (GA)
  • hybrid algorithm
  • magnetostatic shielding

ASJC Scopus subject areas

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

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