A novel genetic search scheme based on nature-inspired evolutionary algorithms for binary self-dual codes
dc.contributor.author | Korban, Adrian | |
dc.contributor.author | Şahinkaya, Serap | |
dc.contributor.author | Ustun, Deniz | |
dc.date.accessioned | 2022-05-14T01:04:47Z | |
dc.date.available | 2022-05-14T01:04:47Z | |
dc.date.issued | 2022-05-01 | |
dc.identifier | doi: 10.3934/amc.2022033 | |
dc.identifier.citation | Korban,A., Şahinkaya, S., & Ustun, D. (2022). A novel genetic search scheme based on nature-inspired evolutionary algorithms for binary self-dual codes. Advances in Mathematics of Communications. https://doi.org/10.3934/amc.2022033 | |
dc.identifier.issn | 1930-5346 | |
dc.identifier.doi | 10.3934/amc.2022033 | |
dc.identifier.uri | http://hdl.handle.net/10034/626861 | |
dc.description | This article is not available on ChesterRep | |
dc.description.abstract | 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. | |
dc.publisher | American Institute of Mathematical Sciences | |
dc.relation.url | https://www.aimsciences.org/article/doi/10.3934/amc.2022033 | |
dc.source | pissn: 1930-5346 | |
dc.source | eissn: 1930-5338 | |
dc.subject | Applied Mathematics | |
dc.subject | Discrete Mathematics and Combinatorics | |
dc.subject | Computer Networks and Communications | |
dc.subject | Algebra and Number Theory | |
dc.subject | Microbiology | |
dc.title | A novel genetic search scheme based on nature-inspired evolutionary algorithms for binary self-dual codes | |
dc.type | Article | |
dc.identifier.eissn | 1930-5338 | |
dc.contributor.department | University of Chester; Tarsus University | |
dc.identifier.journal | Advances in Mathematics of Communications | |
dc.date.updated | 2022-05-14T01:04:47Z |