English

An Application of the Virus Optimization Algorithm to the Problem of Finding Extremal Binary Self-Dual Codes

Information Theory 2021-03-16 v1 math.IT

Abstract

In this paper, a virus optimization algorithm, which is one of the metaheuristic optimization technique, is employed for the first time to the problem of finding extremal binary self-dual codes. We present a number of generator matrices of the form [I36  τ3(v)],[I_{36} \ | \ \tau_3(v)], where I36I_{36} is the 36×3636 \times 36 identity matrix, vv is an element in the group matrix ring M3(F2)GM_3(\mathbb{F}_2)G and GG is a finite group of order 12, which we then employ together with the the virus optimization algorithm and the genetic algorithm to search for extremal binary self-dual codes of length 72. We obtain that the virus optimization algorithm finds more extremal binary self-dual codes than the genetic algorithm. Moreover, by employing the above mentioned constructions together with the virus optimization algorithm, we are able to obtain 39 Type I and 19 Type II codes of length 72, with parameters in their weight enumerators that were not known in the literature before.

Keywords

Cite

@article{arxiv.2103.07739,
  title  = {An Application of the Virus Optimization Algorithm to the Problem of Finding Extremal Binary Self-Dual Codes},
  author = {Adrian Korban and Serap Sahinkaya and Deniz Ustun},
  journal= {arXiv preprint arXiv:2103.07739},
  year   = {2021}
}

Comments

arXiv admin note: substantial text overlap with arXiv:2102.12863

R2 v1 2026-06-24T00:06:32.918Z