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Trust-Search Methods for Unconstrained Optimization

Philip E. Gill
UCSD

Abstract:

Recent research on interior methods has re-emphasized the role of sequential unconstrained optimization for the solution of nonlinear programming problems. We focus on the numerical linear algebra associated with a class of "trust-search" methods that combine the best features of line-search and trust-region methods for unconstrained optimization.

Tuesday, October 21, 2008
11:00AM AP&M 2402