摘要
研究了一类含有有限个离散型随机变量的随机广义线性互补问题的数值求解方法.利用期望均值重构和对称扰动的互补函数,将该问题重构成光滑方程组,并提出了一种具有新的非单调线搜索的光滑牛顿算法用来求解重构后问题.在一定条件下,此算法是全局收敛的,且其收敛速度是局部二次的.
A class of stochastic generalized linear complementarity problems with finitely many realizations is studied. Based on Expected value formulation and smoothing symmetric perturbed Fischer function,the stochastic generalized linear complementarity problems are reformulated as a system of smoothing equations. Then, a smoothing Newton method with nonmonotone line search strategy is presented to solve the new formulation. Moreover, it’s proved that this nonmonotone smoothing algorithm is globally and local quadratically convergent under suitable assumptions.
作者
张静
张颖
Zhang Jing;Zhang Ying({School of Mathematics,Tianjin University,Tianjin 300072,China)
出处
《南开大学学报（自然科学版）》
CAS
CSCD
北大核心
2020年第2期29-37,共9页
Acta Scientiarum Naturalium Universitatis Nankaiensis
基金
Supported by Nature Science Foundation of China(11471241)。
关键词
随机广义线性互补问题
期望均值重构
光滑牛顿算法
非单调线搜索
stochastic generalized complementarity problems
expected value formulation
smoothing Newton algorithm
nonmonotone line search
