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 Reflective Newton Method for Minimizing a Quadratic FunctionSubject to Bounds on Some of The Variables.
Authors: Coleman, Thomas F.
Li, Yuying
Keywords: computer science
technical report
Issue Date: Nov-1992
Publisher: Cornell University
Abstract: We propose a new algorithm, a reflective Newton method, for the minimization of a quadratic function of many variables subject to upper and lower bounds on some of the variables. The method applies to a general (indefinite) quadratic function, for which a local minimizer subject to bounds is required, and is particularly suitable for the large-scale problem. Our new method exhibits strong convergence properties, global and quadratic convergence, and appears to have significant practical potential. Strictly feasible points are generated. Experimental results on moderately large and sparse problems support the claim of practicality for large-scale problems.
Appears in Collections:Computer Science Technical Reports

Files in This Item:

File Description SizeFormat
92-1315.pdf3.04 MBAdobe PDFView/Open
92-1315.ps672.23 kBPostscriptView/Open

Refworks Export

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


© 2014 Cornell University Library Contact Us