An implicit trust region algorithm for constrained optimization

Abstract : In this paper we study the convergence of sequential quadratic programming algorithms for the nonlinear programming problems. Assuming only that the direction is a stationary point of the current quadratic program we study the local convergence properties without strict complementarity. We obtain some global and superlinearly convergent algorithm. As a particular case we formulate an extension of Newton's method that is quadratically convergent to a point satisfying a strong sufficient second order condition.
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Rapport
[Research Report] RR-1780, INRIA. 1992
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https://hal.inria.fr/inria-00077020
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Soumis le : lundi 29 mai 2006 - 11:51:42
Dernière modification le : vendredi 25 mai 2018 - 12:02:05
Document(s) archivé(s) le : vendredi 13 mai 2011 - 22:34:37

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  • HAL Id : inria-00077020, version 1

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J. Frederic Bonnans, Geneviève Launay. An implicit trust region algorithm for constrained optimization. [Research Report] RR-1780, INRIA. 1992. 〈inria-00077020〉

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