Globalizing Stabilized Sequential Quadratic Programming Method by Smooth Primal-Dual Exact Penalty Function

An iteration of the stabilized sequential quadratic programming method consists in solving a certain quadratic program in the primal-dual space, regularized in the dual variables. The advantage with respect to the classical sequential quadratic programming is that no constraint qualifications are re...

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Vydané v:	Journal of optimization theory and applications Ročník 169; číslo 1; s. 148 - 178
Hlavní autori:	Izmailov, A. F., Solodov, M. V., Uskov, E. I.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.04.2016 Springer Nature B.V
Predmet:	Algorithms Applications of Mathematics Calculus of Variations and Optimal Control; Optimization Convergence Engineering Globalization Lagrange multiplier Mathematical analysis Mathematical models Mathematics Mathematics and Statistics Methods Operations Research/Decision Theory Optimization Penalty function Preserves Quadratic programming Studies Tasks Theory of Computation Global convergence 65K15 65K05 90C30 Stabilized sequential quadratic programming Exact penalty function Second-order sufficiency Superlinear convergence Noncritical Lagrange multiplier
ISSN:	0022-3239, 1573-2878
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