遗传算法（Genetic Algorithm，GA）是通过对自然界中生物的遗传和优胜劣汰的进化过程进行模拟与抽象，进而形成的一种自适应全局随机优化搜索方法。遗传算法只需提供目标函数作为寻优信息，它从某一随机生成的初始群体出发，经过选择、交叉和变异等遗传操作后对个体进行适应度评价，保留适应度较强的个体遗传到子代种群中，经过多次的迭代计算求得最优个体，即问题的最优解。本程序采用遗传算法可求解微网优化运行。-Genetic Algorithm is an adaptive global by nature, genetic and biological survival of the fittest evolutionary process simulation and abstract, and thus the formation of stochastic optimization search method. Just provide genetic algorithm optimization objective function as an information, which is generated from a random initial population of departure, after genetic manipulation, such as selection, crossover and mutation of individuals fitness evaluation, retained a strong individual genetic fitness to child on behalf of the population, after several iterations of computing the optimal solution to get the optimal individual, that is the problem. This program uses a genetic algorithm to solve the optimal operation of the micro-network.