中文说明：
遗传算法（Genetic Algorithm，GA）最早是由美国的 John holland于20世纪70年代提出,该算法是根据大自然中生物体进化规律而设计提出的。是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法。该算法通过数学的方式,利用计算机仿真运算,将问题的求解过程转换成类似生物进化中的染色体基因的交叉、变异等过程。在求解较为复杂的组合优化问题时,相对一些常规的优化算法,通常能够较快地获得较好的优化结果。遗传算法已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。
English Description：
Genetic algorithm (GA) was first proposed by John Holland of the United States in the 1970s. The algorithm is designed and proposed according to the evolution law of organisms in nature. It is a computational model simulating the natural selection and genetic mechanism of Darwin's theory of biological evolution. It is a method to search the optimal solution by simulating the natural evolution. The algorithm transforms the process of solving the problem into a process similar to the crossover and mutation of chromosome genes in biological evolution by means of mathematics and computer simulation. When solving complex combinatorial optimization problems, compared with some conventional optimization algorithms, they usually can get better optimization results quickly. Genetic algorithm has been widely used in combinatorial optimization, machine learning, signal processing, adaptive control and artificial life.