论文标题
一种基于自然的新型遗传搜索方案 - 自偶联代码的灵感进化算法
A Novel Genetic Search Scheme Based on Nature -- Inspired Evolutionary Algorithms for Self-Dual Codes
论文作者
论文摘要
在本文中，首次将遗传算法（进化算法优化方法之一）用于查找极端二进制自我双重代码的问题。我们介绍了遗传算法与对不同尺寸搜索空间的线性搜索之间的计算时间的比较，并表明遗传算法能够找到比线性搜索更快的二进制自偶像代码。此外，通过采用已知的矩阵结构以及遗传算法，我们能够在很短的时间内获得68和72的新二进制自偶代码。特别是，我们获得了长度68和17的11个新的极端二进制自动偶数代码，长度为72。
In this paper, a genetic algorithm, one of the evolutionary algorithms optimization methods, is used for the first time for the problem of finding extremal binary self-dual codes. We present a comparison of the computational times between a genetic algorithm and a linear search for different size search spaces and show that the genetic algorithm is capable of finding 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 extremal binary self-dual codes of length 68 and 17 new binary self-dual codes of length 72.
