Biogeography-based optimization with covariance matrix based migration

Xu Chen, Huaglory Tianfield, Wenli Du, Guohai Liu

    Research output: Contribution to journalArticle

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    Abstract

    Biogeography-based optimization (BBO) is a new evolutionary algorithm. The major problem of basic BBO is that its migration operator is rotationally variant, which leaves BBO performing poorly in non-separable problems. To overcome this drawback of BBO, in this paper, we propose the covariance matrix based migration (CMM) to relieve BBO’s dependence upon the coordinate system so that BBO’s rotational invariance is enhanced. By embedding the CMM into BBO, we put forward a new BBO approach, namely biogeography-based optimization with covariance matrix based migration, called CMM-BBO. Specifically, CMM-BBO algorithms are developed by the CMM operator being randomly combined with the original migration in various existing BBO variants. Numeric simulations on 37 benchmark functions show that our CMM-BBO approach effectively improves the performance of the existing BBO algorithms.
    Original languageEnglish
    Pages (from-to)71–85
    Number of pages15
    JournalApplied Soft Computing
    Volume45
    Early online date26 Apr 2016
    DOIs
    Publication statusPublished - Aug 2016

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    Covariance matrix
    Mathematical operators
    Invariance
    Evolutionary algorithms

    Keywords

    • biogeography-based optimization
    • covariance matrix based migration
    • global numeric optimization
    • evolutionary algorithm
    • rotational invariance

    Cite this

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    title = "Biogeography-based optimization with covariance matrix based migration",
    abstract = "Biogeography-based optimization (BBO) is a new evolutionary algorithm. The major problem of basic BBO is that its migration operator is rotationally variant, which leaves BBO performing poorly in non-separable problems. To overcome this drawback of BBO, in this paper, we propose the covariance matrix based migration (CMM) to relieve BBO’s dependence upon the coordinate system so that BBO’s rotational invariance is enhanced. By embedding the CMM into BBO, we put forward a new BBO approach, namely biogeography-based optimization with covariance matrix based migration, called CMM-BBO. Specifically, CMM-BBO algorithms are developed by the CMM operator being randomly combined with the original migration in various existing BBO variants. Numeric simulations on 37 benchmark functions show that our CMM-BBO approach effectively improves the performance of the existing BBO algorithms.",
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    author = "Xu Chen and Huaglory Tianfield and Wenli Du and Guohai Liu",
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    language = "English",
    volume = "45",
    pages = "71–85",
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    Biogeography-based optimization with covariance matrix based migration. / Chen, Xu; Tianfield, Huaglory; Du, Wenli; Liu, Guohai.

    In: Applied Soft Computing, Vol. 45, 08.2016, p. 71–85.

    Research output: Contribution to journalArticle

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    AU - Tianfield, Huaglory

    AU - Du, Wenli

    AU - Liu, Guohai

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    AB - Biogeography-based optimization (BBO) is a new evolutionary algorithm. The major problem of basic BBO is that its migration operator is rotationally variant, which leaves BBO performing poorly in non-separable problems. To overcome this drawback of BBO, in this paper, we propose the covariance matrix based migration (CMM) to relieve BBO’s dependence upon the coordinate system so that BBO’s rotational invariance is enhanced. By embedding the CMM into BBO, we put forward a new BBO approach, namely biogeography-based optimization with covariance matrix based migration, called CMM-BBO. Specifically, CMM-BBO algorithms are developed by the CMM operator being randomly combined with the original migration in various existing BBO variants. Numeric simulations on 37 benchmark functions show that our CMM-BBO approach effectively improves the performance of the existing BBO algorithms.

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    KW - global numeric optimization

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