遗传算法（Genetic Algorithms，简称 GA）是一种基于自然选择原理和自然遗传机
制的搜索（寻优）算法，它是模拟自然界中的生命进化机制，在人工系统中实现特定目
标的优化。遗传算法的实质是通过群体搜索技术，根据适者生存的原则逐代进化，最终
得到最优解或准最优解。它必须做以下操作：初始群体的产生、求每一个体的适应度、
根据适者生存的原则选择优良个体、被选出的优良个体两两配对，通过随机交叉其染色
体的基因并随机变异某些染色体的基因后生成下一代群体，按此方法使群体逐代进化，
直到满足进化终止条件。(可用于路径优化)(Genetic Algorithms (GA) is a search algorithm based on natural selection principle and natural genetic mechanism. It simulates the mechanism of life evolution in nature and achieves the optimization of specific targets in artificial system. The essence of the genetic algorithm is by the group search technology, according to the principle of survival of the fittest, and finally get the optimal solution or the quasi optimal solution. It must do the following: the generation of initial population, for each individual to adapt to the excellent individual 22 degrees, according to the principle of survival of the fittest, select excellent individuals selected by random chromosome pairing, cross gene and random mutation of some genes on the next generation after generation, according to this method makes the group from generation to generation until the termination condition of evolution, evolution.(it can be used for Path optimization))