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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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https://hal.inria.fr/inria-00077020
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Submitted on : Monday, May 29, 2006 - 11:51:42 AM
Last modification on : Friday, February 4, 2022 - 3:10:09 AM
Long-term archiving on: : Friday, May 13, 2011 - 10:34:37 PM

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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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