Preconditioned spectral gradient method

被引:20
作者
Luengo, F
Raydan, M
Glunt, W
Hayden, TL
机构
[1] Univ Zulia, Dept Matemat & Computac, Fac Ciencias, Maracaibo 4011, Venezuela
[2] Cent Univ Venezuela, Dept Computac, Caracas 1041A, Venezuela
[3] Austin Peay State Univ, Dept Math & Comp Sci, Clarksville, TN 37044 USA
基金
美国国家科学基金会;
关键词
spectral gradient method; preconditioning techniques; multidimensional scaling; nonmonotone line search; Poisson-type equations;
D O I
10.1023/A:1020181927999
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The spectral gradient method is a nonmonotone gradient method for large-scale unconstrained minimization. We strengthen the algorithm by modifications which globalize the method and present strategies to apply preconditioning techniques. The modified algorithm replaces a condition of uniform positive definitness of the preconditioning matrices, with mild conditions on the search directions. The result is a robust algorithm which is effective on very large problems. Encouraging numerical experiments are presented for a variety of standard test problems, for solving nonlinear Poisson-type equations, an also for finding molecular conformations by distance geometry.
引用
收藏
页码:241 / 258
页数:18
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