摘要
本文提出了一种解无约束优化问题的新的非单调自适应信赖域方法.这种方法借助于目标函数的海赛矩阵的近似数量矩阵来确定信赖域半径.在通常的条件下,给出了新算法的全局收敛性以及局部超线性收敛的结果,数值试验验证了新的非单调方法的有效性.
In this paper,a new nonmonotone adaptive trust region method for unconstrained optimization problems is presented.The trust region radius in the new method is determined with the scalar approximation of Hessian matrix of the objective function.Under general conditions,the global and superlinear convergence results of the algorithm are established.Numerical results show that the new method is more efficient.
出处
《应用数学》
CSCD
北大核心
2010年第3期630-637,共8页
Mathematica Applicata
基金
Supported by Jiangsu Teachers University of Technology Foundation(KYY08041)
关键词
无约束优化
自适应信赖域法
非单调技术
全局收敛
Unconstrained optimization
Adaptive trust region method
Nonmonotone technique
Global convergence
