摘要
利用基本粒子群优化算法求解特征值互补问题,构造了求解特征值互补问题的基本粒子群算法,并且证明了该算法的收敛性,运用数值例子验证了求解特征值互补问题的基本粒子群算法的有效性.求解不同阶矩阵的特征值互补问题的测试结果表明:基本粒子群优化算法与半光滑牛顿法相比具有较快的收敛速度.
A basic particle swarm optimization algorithm for solving eigenvalue complementarity problems is constructed,and the convergence of the algorithm is proved. Numerical examples are given to verify the effectiveness of the basic particle swarm optimization algorithm for solving the eigenvalue complementarity problem. The results of eigenvalue complementarity problem for solving different order matrixes show that the basic particle swarm optimization algorithm has faster convergence speed than the Semi-smooth Newton Method.
作者
赵锐
韩海山
ZHAO Rui;HAN Hai-shan(College of Mathematics and Physics,Inner Mongolia University for Nationalities,Tongliao 028043,China)
出处
《内蒙古民族大学学报（自然科学版）》
2020年第3期191-197,共7页
Journal of Inner Mongolia Minzu University：Natural Sciences
关键词
特征值互补问题
粒子群优化算法
NCP函数
Eigenvalue complementarity problem
Particle swarm optimization algorithm
NCP function
