遗传算法(Genetic Algorithm, GA)是近几年发展起来的一种崭新的全局优化算法，它借

用了生物遗传学的观点，通过自然选择、遗传、变异等作用机制，实现各个个体的适应性

的提高。这一点体现了自然界中"物竞天择、适者生存"进化过程。1962年Holland教授首次

提出了GA算法的思想，从而吸引了大批的研究者，迅速推广到优化、搜索、机器学习等方

面，并奠定了坚实的理论基础。 用遗传算法解决问题时，首先要对待解决问题的模型结构

和参数进行编码，一般用字符串表示，这个过程就将问题符号化、离散化了。也有在连续

空间定义的GA(Genetic Algorithm in Continuous Space, GACS)，暂不讨论。-genetic algorithm (Genetic Algorithm. GA) is developed in recent years a new global optimization algorithm, it borrows from the biological point of view of genetics, through natural selection, genetic variation, such as mechanisms to achieve the adaptability of various individuals raised. This is reflected in the natural world, "the process of natural selection and survival of the fittest" evolutionary process. In 1962, Professor Holland first proposed the idea of the algorithm, thereby attracting a large number of researchers, to promote rapid optimization, search, machine learning, and to lay a solid foundation in theory. Using genetic algorithms to solve the problem, we must first solve the problem of the treatment of the model structure and coding parameters, general string,