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EnglishIn this paper, starting from the study of the common elements that some globally convergent direct search methods share, a general convergence theory is established for unconstrained minimization methods employing only function values. The introduced convergence conditions are useful for developing and analyzing new derivative-free algorithms with guaranteed global convergence. As examples, we describe three new algorithms which combine pattern and line search approaches.
http://hdl.handle.net/11573/16174| Titolo: | On the Global Convergence of Derivative Free Methods for Unconstrained Optimization |
| Autori interni: | LUCIDI, Stefano |
| Data di pubblicazione: | 2002 |
| Rivista: | SIAM JOURNAL ON OPTIMIZATION |
| Abstract: | In this paper, starting from the study of the common elements that some globally convergent direct search methods share, a general convergence theory is established for unconstrained minimization methods employing only function values. The introduced convergence conditions are useful for developing and analyzing new derivative-free algorithms with guaranteed global convergence. As examples, we describe three new algorithms which combine pattern and line search approaches. |
| Handle: | http://hdl.handle.net/11573/16174 |
| Appare nelle tipologie: | 01.a Pubblicazione su Rivista |
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