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

    16 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

    Fingerprint

    Magnetostatics
    Shape optimization
    Evolutionary algorithms
    Shielding
    Genetic algorithms
    Magnetic materials
    Heuristic algorithms
    Conceptual design
    Engineers

    Keywords

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

    ASJC Scopus subject areas

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

    Cite this

    Binary-based topology optimization of magnetostatic shielding by a hybrid evolutionary algorithm combining genetic algorithm and extended compact genetic algorithm. / Tominaga, Yusuke; Okamoto, Yoshifumi; Wakao, Shinji; Sato, Shuji.

    In: IEEE Transactions on Magnetics, Vol. 49, No. 5, 6514632, 2013, p. 2093-2096.

    Research output: Contribution to journalArticle

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