摘要
提出一种改进的求解非线性方程组的遗传算法。将梯度信息引入遗传算法,通过改变高斯变异参数不断调整搜索范围,逐渐搜索到包含最优解的区域,利用梯度信息提高解的精度。数值模拟结果表明,改进后的算法具有较强的局部搜索能力和全局优化能力,能够提高求解的精度与速度。
An improved genetic algorithm was proposed for solving non-linear equation group. Gradient information was introduced into the genetic algorithm. The search scope was continuously adjusted by changing Gaussian variation parameters. And the region containing the optimal solution was found gradually. The solution precision can be improved by using gradient information. The numerical simulation results show that the improved algorithm is characterized by strong local search ability and global optimization capability, and can improve the accuracy and speed of solution.
出处
《中国石油大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2009年第3期172-174,共3页
Journal of China University of Petroleum(Edition of Natural Science)
关键词
遗传算法
非线性方程组
函数优化
genetic algorithm
non-linear equation group
function optimization
