A spectral conjugate gradient method for unconstrained optimization

被引：243
|
作者：
Birgin, EG
Martínez, JM
机构：
[1] Univ Sao Paulo, IME, Dept Comp Sci, BR-05508900 Sao Paulo, SP, Brazil
[2] Univ Estadual Campinas, UNICAMP, IMECC, Dept Appl Math, BR-13081970 Campinas, SP, Brazil
来源：
APPLIED MATHEMATICS AND OPTIMIZATION | 2001年 / 43卷 / 02期
关键词：
unconstrained minimization; spectral gradient method; conjugate gradients;
D O I：
10.1007/s00245-001-0003-0
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A family of scaled conjugate gradient algorithms for large-scale unconstrained minimization is defined. The Ferry, the Polak-Ribiere and the Fletcher-Reeves formulae are compared using a spectral scaling derived from Raydan's spectral gradient optimization method. The best combination of formula, scaling and initial choice of step-length is compared against well known algorithms using a classical set of problems. An additional comparison involving an ill-conditioned estimation problem in Optics is presented.
引用
收藏
页码：117 / 128
页数：12
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