Nonlinear stepsize control, trust regions and regularizations for unconstrained optimization

Philippe Toint

doi:10.1080/10556788.2011.610458

Nonlinear stepsize control, trust regions and regularizations for unconstrained optimization

Philippe Toint

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Résumé

A class of algorithms for unconstrained optimization is introduced, which subsumes the classical trust-region algorithm and two of its newer variants, as well as the cubic and quadratic regularization methods. A unified theory of global convergence to first-order critical points is then described for this class. © 2013 Copyright Taylor and Francis Group, LLC.

langue originale	Anglais
Pages (de - à)	82-95
Nombre de pages	14
journal	Optimization Methods and Software
Volume	28
Numéro de publication	1
Les DOIs	https://doi.org/10.1080/10556788.2011.610458
Etat de la publication	Publié - 1 févr. 2013

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10.1080/10556788.2011.610458

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ADALGOPT: ADALGOPT - Algorithmes avancés en optimisation non-linéaire
Sartenaer, A. & TOINT, P.
1/01/87 → …
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Nonlinear stepsize control, trust regions and regularizations for unconstrained optimization

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ADALGOPT: ADALGOPT - Algorithmes avancés en optimisation non-linéaire

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