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    A novel genetic search scheme based on nature-inspired evolutionary algorithms for binary self-dual codes

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    Authors
    Korban, Adrian
    Şahinkaya, Serap
    Ustun, Deniz
    Publication Date
    2022
    
    Metadata
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    Abstract
    <p style='text-indent:20px;'>In this paper, a genetic algorithm, one of the evolutionary algorithm optimization methods, is used for the first time for the problem of computing extremal binary self-dual codes. We present a comparison of the computational times between the genetic algorithm and a linear search for different size search spaces and show that the genetic algorithm is capable of computing binary self-dual codes significantly faster than the linear search. Moreover, by employing a known matrix construction together with the genetic algorithm, we are able to obtain new binary self-dual codes of lengths 68 and 72 in a significantly short time. In particular, we obtain 11 new binary self-dual codes of length 68 and 17 new binary self-dual codes of length 72.</p>
    Citation
    Advances in Mathematics of Communications, volume 0, issue 0, page 0
    Publisher
    American Institute of Mathematical Sciences (AIMS)
    URI
    http://hdl.handle.net/10034/626861
    Type
    article
    Description
    From Crossref journal articles via Jisc Publications Router
    Publication status: Published
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