An efficient conjugate direction method with orthogonalization for large-scale quadratic optimization problems

被引:0
|
作者
Boudinov, Edouard R. [1 ]
Manevich, Arkadiy I.
机构
[1] FORTIS Bank, Amsterdam, Netherlands
[2] Dniepropetrovsk Natl Univ, Dept Computat Mech & Strength Struct, Dnepropetrovsk, Ukraine
来源
OPTIMIZATION METHODS & SOFTWARE | 2007年 / 22卷 / 02期
关键词
unconstrained minimization; large-scale optimization; conjugate gradients; conjugate direction methods; orthogonalization;
D O I
10.1080/10556780500532209
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
A new conjugate direction (CD) method is proposed, which is based on an orthogonalization procedure and does not make use of line searches for the conjugate vector set construction. This procedure prevents the set of conjugate vectors from degeneracy and eliminates high sensitivity to computation errors pertinent to methods of CDs, resulting in an efficient algorithm for solving large-scale ill-conditioned minimization problems without preconditioning. The advantages of our algorithms are illustrated by results of the extensive numerical experiments with large-scale quadratic functions.
引用
收藏
页码:309 / 328
页数:20
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