A truncated Newton algorithm for large scale box constrained optimization

被引：37
作者：
Facchinei, F [1 ]
Lucidi, S [1 ]
Palagi, L [1 ]
机构：
[1] Univ Roma La Sapienza, Dipartimento Informat & Sistemist A Ruberti, I-00185 Rome, Italy
来源：
SIAM JOURNAL ON OPTIMIZATION | 2002年 / 12卷 / 04期
关键词：
bound constrained problem; penalty function; Newton method; conjugate gradient; nonmonotone line search;
D O I：
10.1137/S1052623499359890
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A method for the solution of minimization problems with simple bounds is presented. Global convergence of a general scheme requiring the approximate solution of a single linear system at each iteration is proved and a superlinear convergence rate is established without requiring the strict complementarity assumption. The algorithm proposed is based on a simple, smooth unconstrained reformulation of the bound constrained problem and may produce a sequence of points that are not feasible. Numerical results and comparison with existing codes are reported.
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页码：1100 / 1125
页数：26
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