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Persistent URL http://purl.org/net/epubs/work/29804
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Record Id 29804
Title A filter-trust-region method for unconstrained optimization
Abstract A new filter-trust-region algorithm for solving unconstrained nonlinear optimization problems is introduced. Based on the filter technique introduced by Fletcher and Leyffer, it extends an existing technique of Gould, Leyffer and Toint (SIAM J. Optim., to appear, 2004) for non-linear equations and non-linear least-squares to the fully general unconstrained optimization problem. The new algorithm is shown to be globally convergent to at least one second-order critcal point, and numerical experiments indicate that it is very competitive with more classical trust-region algorithms.
Organisation CCLRC
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Related Research Object(s): 40545
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Language English (EN)
Type Details URI(s) Local file(s) Year
Report RAL Technical Reports RAL-TR-2004-009. 2004. raltr-2004009.pdf 2004