Résumé
| langue originale | Anglais |
|---|---|
| Pages (de - à) | 11-18 |
| Nombre de pages | 8 |
| journal | SIOPT Views and News |
| Volume | 17 |
| Numéro de publication | 1 |
| état | Non publié - 2006 |
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Using Problem Structure in Derivative-free Optimization. / Toint, Philippe.
Dans: SIOPT Views and News, Vol 17, Numéro 1, 2006, p. 11-18.Résultats de recherche: Contribution à un journal/une revue › Article
TY - JOUR
T1 - Using Problem Structure in Derivative-free Optimization
AU - Toint, Philippe
PY - 2006
Y1 - 2006
N2 - Derivative-free unconstrained optimization is the class of optimization methods for which the derivatives of the objective function are unavailable. These methods are already well-studied, but are typically restricted to problems involving a small number of variables. The paper discusses how this restriction may be removed by the use the underlying problems structure, both in the case of pattern-search and interpolation methods. The focus is on partially separable objective function, but it is shown how Hessian sparsity, a weaker structure description, can also be used to advantage.
AB - Derivative-free unconstrained optimization is the class of optimization methods for which the derivatives of the objective function are unavailable. These methods are already well-studied, but are typically restricted to problems involving a small number of variables. The paper discusses how this restriction may be removed by the use the underlying problems structure, both in the case of pattern-search and interpolation methods. The focus is on partially separable objective function, but it is shown how Hessian sparsity, a weaker structure description, can also be used to advantage.
M3 - Article
VL - 17
SP - 11
EP - 18
JO - SIOPT Views and News
JF - SIOPT Views and News
IS - 1
ER -