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Superlinear convergence of the sequential quadratic method in constrained optimization. (English) Zbl 1441.90162
Summary: This paper pursues a twofold goal. Firstly, we aim at deriving novel second-order characterizations of important robust stability properties of perturbed Karush-Kuhn-Tucker systems for a broad class of constrained optimization problems generated by parabolically regular sets. Secondly, the obtained characterizations are applied to establish well-posedness and superlinear convergence of the basic sequential quadratic programming method to solve parabolically regular constrained optimization problems.
Reviewer: Reviewer (Berlin)
MSC:
 90C31 Sensitivity, stability, parametric optimization 65K99 Numerical methods for mathematical programming, optimization and variational techniques 49J52 Nonsmooth analysis 49J53 Set-valued and variational analysis
PLCP; SQPlab
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References:
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