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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.
90C31 Sensitivity, stability, parametric optimization
65K99 Numerical methods for mathematical programming, optimization and variational techniques
49J52 Nonsmooth analysis
49J53 Set-valued and variational analysis
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