遗传算法的应用研究进展  

The Evolvement of Genetic Algorithm's Application Research

作　　者：许斗[1] 钱峰[1] 

机构地区：[1]芜湖职业技术学院计算机系,安徽芜湖241001

出　　处：《芜湖职业技术学院学报》2003年第1期1-4,共4页Journal of Wuhu Institute of Technology

摘　　要：遗传算法是一类借鉴生物界的进化规律演化而来的随机化搜索方法,其主要特点是直接对结构对象进行操作,不存在求导和函数连续性的限定;具有内在的隐并行性和更好的全局导优能力;采用概率化的导优方法,能自动获取和指导优化的搜索空间,自适应地调整搜索方向,不需要确定的规则。遗传算法的这些性质,已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。The Genetic Algorithm(GA) is a random-search method imitating the rules of the organic world. The main distinguishing features are as following: operating on the composition target, requesting no guide and function continuance; having intrinsically conceal concurrence and splendid capability with the better situation as a whole; adopting approximately the guiding of the most splendid means of leading, being able to gain voluntarily and the searching room that the direction optimizes, self-adopting the regulation direction of search, not needing certain regulation. The features of GA have been widely used applied in territories such as optimization, machine learning, treatment of signal, self-adoption control, artificial existence and so on.

关 键 词：遗传算法 应用研究进展 函数连续性 自适应控制 搜索方法 进化规律 主要特点 搜索空间 自动获取 搜索方向 组合优化 机器学习 信号处理 人工生命 随机化 生物界 并行性 概率化 对象 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置] O242.23[自动化与计算机技术—控制科学与工程]