Approaching the Minimum Distance Problem by Algebraic Swarm-Based Optimizations

dc.authoridhttps://orcid.org/0000-0002-5229-4018en_US
dc.authoridhttps://orcid.org/0000-0002-2084-6260en_US
dc.authorscopusid36728602600en_US
dc.authorscopusid55420759300en_US
dc.authorwosidG-2829-2015en_US
dc.authorwosidABB-4228-2020en_US
dc.contributor.authorŞahinkaya, Serap
dc.contributor.authorÜstün, Deniz
dc.date.accessioned2024-08-01T14:33:04Z
dc.date.available2024-08-01T14:33:04Z
dc.date.issued2021en_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractIn 1948, Claude Shannon, published ”A Mathematical Theory of Communication,” a seminal paper, which was about reliable data transmission over noisy channels [12]. Efficient and reliable data transmission, which can be done by some error-control techniques, are one of the main interests of coding theory. Error detecting and correcting capability are very important feature of a code and it is determined by the minimum distance of the code. Computing the minimum distance of a linear code C of large length is a difficult problem in coding theory. In [14], Vardy showed that this computation is an NP-hard type. The problem of finding minimum distance is getting harder when the size of the code grows. Therefore, some meta-heuristic algorithms have been used to approach the problem. In most of the existing literature, genetic algorithms are used for the considered problem. As far as our knowledge, among the algorithms in the literature that are based on swarm intelligence, only the ant colony algorithm (ACO) was used for the minimum-weight codeword problem [4,5]. It is well known that there is no heuristic algorithm which can perform good enough to solve optimization problems, please see [13] for details. . Therefore, it is natural to try the other swarm-based optimization techniques for the considered problem. In this paper, bat algorithm (BA) and firefly algorithm (FA) are applied to the minimum distance problem by integrating the algebraic operator to the handled algorithms. Most of the papers in the literature uses codewords as a search space for the minimum distance problem. Recently, generator matrices were considered as a search space, which turned out to be a better approach than using the codewords as a search space, please see [1] for details. In this work, we also consider generator matrices as a search space. In coding theory, the BCH codes or BoseOCoChaudhuriOCoHocquenghemcodes form a class of cyclic error-correcting codes that are constructed using polynomials over a finite field. Effectiveness of the presented algorithm is controlled by running the algorithm on BCH codes since they are the standard codes with known minimum distance values [3, 9]en_US
dc.identifier.citationŞahinkaya, S., ve Üstün, D. (2021). Approaching the Minimum Distance Problem by Algebraic Swarm-Based Optimizations. Turkish Journal of Mathematics and Computer Science, 13(1), 129-134. https://doi.org/10.47000/tjmcs.825565en_US
dc.identifier.doi10.47000/tjmcs.825565en_US
dc.identifier.endpage134en_US
dc.identifier.issue1en_US
dc.identifier.startpage129en_US
dc.identifier.urihttps://doi.org/10.47000/tjmcs.825565
dc.identifier.urihttps://hdl.handle.net/20.500.13099/320
dc.identifier.volume13en_US
dc.institutionauthorÜstün, Deniz
dc.language.isoengen_US
dc.publisherDergiparken_US
dc.relation.ispartofTurkish Journal of Mathematics and Computer Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMinimum distanceen_US
dc.subjectminimum-weight codeworden_US
dc.subjectBCH codesen_US
dc.subjectoptimizationen_US
dc.subjectheuristicen_US
dc.subjectbat algorithmen_US
dc.subjectfirefly algorithmen_US
dc.titleApproaching the Minimum Distance Problem by Algebraic Swarm-Based Optimizationsen_US
dc.typearticleen_US

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