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    Use of the q-Gaussian mutation in evolutionary algorithms.

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    Date
    2011
    Author
    Yang, Shengxiang
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    Abstract
    This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q-Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q-Gaussian mutation is also provided. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.
    Description
    Citation : Tinos, R and Yang, S. (2011) Use of the q-Gaussian mutation in evolutionary algorithms. Soft Computing, 15(8), August 2011, pp. 1523-1549.
    URI
    http://hdl.handle.net/2086/8507
    DOI
    http://dx.doi.org/10.1007/s00500-010-0686-8
    ISSN : 1432-7643
    Research Group : Centre for Computational Intelligence
    Research Institute : Institute of Artificial Intelligence (IAI)
    Peer Reviewed : Yes
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    • School of Computer Science and Informatics [3008]

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