Skip to main content


eCommons@Cornell >
College of Engineering >
Computer Science >
Computer Science Technical Reports >

Please use this identifier to cite or link to this item:
Title: A Subspace, Interior, and Conjugate Gradient Method for Large-ScaleBound-Constrained Minimization Problems
Authors: Branch, Mary Ann
Coleman, Thomas F.
Li, Yuying
Keywords: computer science
technical report
Issue Date: Jul-1995
Publisher: Cornell University
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.
Appears in Collections:Computer Science Technical Reports

Files in This Item:

File Description SizeFormat
95-1525.pdf257.42 kBAdobe PDFView/Open
95-1525.ps245.46 kBPostscriptView/Open

Refworks Export

Items in eCommons are protected by copyright, with all rights reserved, unless otherwise indicated.


© 2014 Cornell University Library Contact Us