这是一个非常简单的遗传算法源代码，是由Denis Cormier (North Carolina State University)开发的，Sita S.Raghavan (University of North Carolina at Charlotte)修正。代码保证尽可能少，实际上也不必查错。对一特定的应用修正此代码，用户只需改变常数的定义并且定义“评价函数”即可。注意代码的设计是求最大值，其中的目标函数只能取正值；且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂交和均匀变异。如果用Gaussian变异替换均匀变异，可能得到更好的效果。代码没有任何图形，甚至也没有屏幕输出，主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu,目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’；系统产生的输出文件为‘galog.txt’。输入的文件由几行组成：数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界，第二行为第二个变量提供上下界，等等。-This is a very simple genetic algorithm source code is determined by Denis Cormier (North Carolina State University) developed, Sita S. Raghavan (University of North Carolina at Charlotte) amendment. Code to ensure as little as possible, in fact there is no need troubleshooting. The application of a specific amendment to this code, the user simply by changing the definition of constants, and the definition of "evaluation function" can be. Note that the code is designed to seek maximum value, where the objective function can only take on positive values　and the function values and individuals there is no difference between the values of adaptation. The system uses the ratio option, essence model, a single point of hybridization, and uniform mutation. If we replace the uniform Gaussian mutation variation, may get better results. Code without any graphics, or even no screen output, mainly to ensure a high portability between platforms. Readers can ftp.uncc.edu, directory coe/evol file pr