遗传算法 ( Genetic Algorithm , GA) 是借鉴生物界自然选择和群体进化机制形成的一种全局寻优算法 。与传统的优化算法相比 ,遗传算法具有如下优点 [1 ] :1 ) 不是从单个点 ,而是从多个点构成的群体开始搜索 2) 在搜索最优解过程中 ,只需要由目标函数值转换得来的适应值信息 ,而不需要导数等其它辅助信息 3) 搜索过程不易陷入局部最优点 。

数学建模中常用的matlab算法，遗传算法，内容详细，包括PDF版本的详细的算法实现过程；-Genetic Algorithm (based Algorithm, GA) is using biological natural selection and group evolution mechanism to form a global optimization Algorithm is proposed. Compared with the traditional optimization algorithm, genetic algorithm has the following advantages [1] : 1) is not　a single point, but　multiple points of groups began to search　2) in the process of searching the optimal solution, only needs to be derived　the objective function value of fitness information, without the need for a derivative and other auxiliary information　3) the search process is not easy to fall into local optimal point.

Mathematical modeling of the commonly used matlab algorithm, genetic algorithm, and content in detail, including the PDF version of the detailed algorithm implementation process