Incorporating minimum Frobenius norm models in direct search

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Abstract

The goal of this paper is to show that the use of minimum Frobenius norm quadratic models can improve the performance of direct-search methods. The approach taken here is to maintain the structure of directional direct-search methods, organized around a search and a poll step, and to use the set of previously evaluated points generated during a direct-search run to build the models. The minimization of the models within a trust region provides an enhanced search step. Our numerical results show that such a procedure can lead to a significant improvement of direct search for smooth, piecewise smooth, and noisy problems.
Original languageUnknown
Pages (from-to)265-278
JournalComputational Optimization And Applications
Volume46
Issue number2
DOIs
Publication statusPublished - 1 Jan 2010

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