HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation

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.
Complete list of metadata

Contributor : Rapport de Recherche Inria Connect in order to contact the contributor
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


  • HAL Id : inria-00077020, version 1



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



Record views


Files downloads