A Retrospective Trust-Region Method for Unconstrained Optimiation

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Zehtabian, Shohre | 2009

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 40165 (02)
University: Sharif University of Technology
Department: Mathematical Sciences
Advisor(s): Mahdavi-Amiri, Nezamoddin
Abstract:
We explain a new trust-region method for solving unconstrained optimization problems recently introduced in the literature, where the radius update is computed using the information at the current iterate rather than at the preceeding one. The update is then performed according to how well the current model retrospectively predicts the value of the objective function at the last iterate. Global convergence to first- and second-order critical ponits is proved under classical assumptions. Preliminary numerical expriments on CUTEr problems with MATLAB7.7 indicate that the new method is very competitive
Keywords:
Nonlinear Optimization ; Numerical Investigation ; Trust Region ; Unconstrainted Optimization ; Convergence

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