遗传算法应用于方程求根的一点改进

在牛顿法与遗传算法的基础上,将方程求根问题转化为函数的优化问题，提出了一种新的求解非线性方程的遗传－牛顿法.算法一方面克服了遗传算法局部搜索能力差的缺陷,另一方面解决了单独使用牛顿法时难以找到合适的初始值的问题.数值实验结果表明,遗传－牛顿法能以较高的效率和精度得到方程的数值解.

A Improvement on Solving Nonlinear Equation by Genetic Algorithm

In this paper,combining with the advantages of genetic algorithm and Newton  algorithm,a new method for solving equations was provided which turned the problem of finding the equation’s roots into the optimization problem.On the one hand,the algorithm overcame the genetic algorithm’s disadvantage which the local search’s ability is not well;on the other hand,the algorithm also solved the problem of difficulty in  finding the proper initialization point.Based on a lot of numerical experiments,the results showed that the algorithm is more preponderant than traditional algorithm genetic on solving nonlinear equations.