### 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 |

### Empreinte digitale

### Citer ceci

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*SIOPT Views and News*, VOL. 17, Numéro 1, p. 11-18.

**Using Problem Structure in Derivative-free Optimization.** / Toint, Philippe.

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 -