GABP

  遗传算法GA—模拟自然界遗传机制和生物进化论而成的一种并行随机搜索最优化方法。（具有“生存+检测”的迭代过程的搜索算法）基于自然界“优胜劣汰，适者生存”的生物进化原理引入优化参数形成的编码串联群体中，按照所选择的适应度函数并通过遗传中的选择、交叉和变异对个体进行筛选，使适应度值好的个体被保留，适应度差的个体被淘汰，新的群体既继承了上一代的信息，又优于上一代。反复循环，直至满足条件。(GA-A parallel random search optimization method that simulates natural genetic mechanisms and biological evolution. (Search algorithm with "survival + detection" iterative process) Based on the biological evolution principle of "survival of the fittest, survival of the fittest" in the natural world, the coding series formed by optimized parameters is introduced. Individuals are screened according to the selected fitness function and through genetic selection, crossover, and variation, so that individuals with good fitness values are retained, individuals with poor adaptability are eliminated, and new groups inherit the information of the previous generation., Better than the last generation. Repeat until conditions are met.)