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A Reflective Newton Method for Minimizing a Quadratic Function Subject to Bounds on Some of the Variables

Author
Coleman, Thomas F.; Li, Yuying
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. This 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.
Date Issued
1992-11Publisher
Cornell University
Subject
theory center
Previously Published As
http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.tc/92-111
Type
technical report