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Title: A subspace, interior, and conjugate gradient method for large-scale bound-constrained minimization problems

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 test problems is reported; advantages of the approach are demonstrated. The experience indicates that the proposed method represents an efficient way to solve large bound-constrained minimization problems.

Authors:
; ;
Publication Date:
Research Org.:
MathWorks, Inc., Natick, MA (US)
Sponsoring Org.:
USDOE; National Science Foundation (NSF); US Department of the Navy, Office of Naval Research (ONR)
OSTI Identifier:
20015654
Resource Type:
Journal Article
Journal Name:
SIAM Journal on Scientific Computing
Additional Journal Information:
Journal Volume: 21; Journal Issue: 1; Other Information: PBD: Sep 1999; Journal ID: ISSN 1064-8275
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; BOUNDARY-VALUE PROBLEMS; ITERATIVE METHODS; FACTORIZATION; CONVERGENCE; PERFORMANCE; ALGORITHMS

Citation Formats

Branch, M.A., Coleman, T.F., and Li, Y. A subspace, interior, and conjugate gradient method for large-scale bound-constrained minimization problems. United States: N. p., 1999. Web. doi:10.1137/S1064827595289108.
Branch, M.A., Coleman, T.F., & Li, Y. A subspace, interior, and conjugate gradient method for large-scale bound-constrained minimization problems. United States. doi:10.1137/S1064827595289108.
Branch, M.A., Coleman, T.F., and Li, Y. Wed . "A subspace, interior, and conjugate gradient method for large-scale bound-constrained minimization problems". United States. doi:10.1137/S1064827595289108.
@article{osti_20015654,
title = {A subspace, interior, and conjugate gradient method for large-scale bound-constrained minimization problems},
author = {Branch, M.A. and Coleman, T.F. and Li, Y.},
abstractNote = {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 test problems is reported; advantages of the approach are demonstrated. The experience indicates that the proposed method represents an efficient way to solve large bound-constrained minimization problems.},
doi = {10.1137/S1064827595289108},
journal = {SIAM Journal on Scientific Computing},
issn = {1064-8275},
number = 1,
volume = 21,
place = {United States},
year = {1999},
month = {9}
}