用于函数式自动生成的改进遗传算法

Improved genetic algorithm applying to automatic generation of function

针对编码和优化对象的特点,提出了一种改进的遗传算法。算法中采用了基于最优保持的父子竞争的选择和交叉机制;提出了对整个种群进行自适应变异和对优良个体大变异的双变异法;引入了滤除相似个体的过滤操作。通过对测试函数的拟合试验,算法的收敛频率和收敛速度都好于其它的改进遗传算法。与其它拟合方法的拟合结果比较,用该算法拟合得到的拟合函数有着较高的拟合精度,说明该方法有着较高的拟合效率。

An improved genetic algorithm based on the characteristic of coding and target＇s optimizing is given. In this algorithm a selection and crossover mechanisms of competition among father and son based on the optimal maintaining operation are adopted. The dual mutation is introduced, which are that an adaptive mutation method is adopted by the whole population and the fine individual greatly. The operation that filters the similar individual is employed. Via the fitting experiment, the convergence frequency and the convergence rate of these algorithms is superior to any other improved genetic algorithm. Compared with the fitting result of other fitting methods, the function obtained with this algorithm has higher fitting precision, which shows this method has higher fitting efficiency.