Korban, AdrianŞahinkaya, SerapÜstün, Deniz2024-08-012024-08-012022Korban A., Şahinkaya S., Ustun D. (2024). A novel genetic search scheme based on nature-inspired evolutionary algorithms for binary self-dual codes. Advances in Mathematics of Communications, 18 (4), 892 - 908. Doi: 10.3934/amc.2022033https://www.aimsciences.org/article/doi/10.3934/amc.2022033?viewType=HTMLhttps://hdl.handle.net/20.500.13099/311In 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.enginfo:eu-repo/semantics/restrictedAccessSelf-dual codesevolutionary algorithmsgenetic search schemegroup ringsarticle10.3934/amc.2022033184892908Q30007930320000012-s2.0-85196850913