遗传算法的应用研究进展

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 Evolvement of Genetic Algorithm's Application Research

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.