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解大规模无约束优化的自适应过滤信赖域法
引用本文:周群艳. 解大规模无约束优化的自适应过滤信赖域法[J]. 计算机工程与应用, 2011, 47(20): 47-49. DOI: 10.3778/j.issn.1002-8331.2011.20.014
作者姓名:周群艳
作者单位:江苏技术师范学院 数理学院,江苏 常州 213001
摘    要:提出一种解大规模无约束优化问题的自适应过滤信赖域法。用目标函数的梯度及迭代点的信息来构造目标函数海赛矩阵的近似数量矩阵,引进了过滤技术和自适应技术,大大提高了计算效率。从理论上证明了新算法的全局收敛性,数值试验结果也表明了新算法的有效性。

关 键 词:大规模无约束优化  过滤技术  梯度法  自适应信赖域法  全局收敛性  
修稿时间: 

Adaptive filter trust region method for large scale unconstrained optimization
ZHOU Qunyan. Adaptive filter trust region method for large scale unconstrained optimization[J]. Computer Engineering and Applications, 2011, 47(20): 47-49. DOI: 10.3778/j.issn.1002-8331.2011.20.014
Authors:ZHOU Qunyan
Affiliation:School of Mathematics and Physics,Jiangsu Teachers University of Technology,Changzhou,Jiangsu 213001,China
Abstract:An adaptive filter trust region method for large scale unconstrained optimization is proposed.This new algorithm uses the function and its gradients to determine a scale matrix as an approximation of its Hessian matrix in the subproblem.The adaptive technique and filter technique are introduced to improve the behavior of the method.The new algorithm is shown to be globally convergent and numerical experiments indicate that it is very effective for large scale unconstrained minimization problems.
Keywords:large scale unconstrained optimization  filter technique  gradient method  adaptive trust region method  global convergence
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