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A Subspace, Interior, and Conjugate Gradient Method for Large-ScaleBound-Constrained Minimization Problems

Author
Branch, Mary Ann; Coleman, Thomas F.; Li, Yuying
Abstract
A subspace adaptation of the Coleman-Li trust region and interior
method is proposed for solving large-scale bound-constrained
minimization problems. This method can be implemented with either
sparse Cholesky factorization or conjugate gradient computation.
Under reasonable conditions the convergence properties of this
subspace trust region method are as strong as those of its full-space
version.
Computational performance on various large-scale test problems are
reported; advantages of our approach are demonstrated. Our experience
indicates our proposed method represents an efficient way to solve
large-scale bound-constrained minimization problems.
Date Issued
1995-07Publisher
Cornell University
Subject
computer science; technical report
Previously Published As
http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR95-1525
Type
technical report