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Please use this identifier to cite or link to this item: http://hdl.handle.net/1813/6108
Title: An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds
Authors: Coleman, Thomas F.
Li, Yuying
Keywords: computer science
technical report
Issue Date: May-1993
Publisher: Cornell University
Citation: http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR93-1342
Abstract: We propose a new trust region approach for minimizing a nonlinear function subject to simple bounds. By choosing an appropriate quadratic model and scaling matrix at each iteration, we show that it is not necessary to solve a quadratic programming subproblem, with linear inequalities, to obtain an improved step using the trust region idea. Instead, a solution to a trust region subproblem is defined by minimizing a quadratic function subject only to an ellipsoidal constraint. The iterates generated by these methods are always strictly feasible. Our proposed methods reduce to a standard trust region approach for the unconstrained problem when there are no upper or lower bounds on the variables. Global and quadratic convergence of the methods is established; preliminary numerical experiments are reported.
URI: http://hdl.handle.net/1813/6108
Appears in Collections:Computer Science Technical Reports

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