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• W2732922863 abstract "Due to the possible lack of primal-dual-type error bounds, the superlinear convergence for the Karush-Kuhn-Tucker (KKT) residues of the sequence generated by augmented Lagrangian method (ALM) for solving convex composite conic programming (CCCP) has long been an outstanding open question. In this paper, we aim to resolve this issue by first conducting convergence rate analysis for the ALM with Rockafellar's stopping criteria under only a mild quadratic growth condition on the dual of CCCP. More importantly, by further assuming that the Robinson constraint qualification holds, we establish the R-superlinear convergence of the KKT residues of the iterative sequence under easy-to-implement stopping criteria {for} the augmented Lagrangian subproblems. Equipped with this discovery, we gain insightful interpretations on the impressive numerical performance of several recently developed semismooth Newton-CG based ALM solvers for solving linear and convex quadratic semidefinite programming." @default.
• W2732922863 created "2017-07-14" @default.
• W2732922863 creator A5025630034 @default.
• W2732922863 creator A5064083862 @default.
• W2732922863 creator A5071290891 @default.
• W2732922863 date "2017-06-27" @default.
• W2732922863 modified "2023-09-27" @default.
• W2732922863 title "On the R-superlinear convergence of the KKT residues generated by the augmented Lagrangian method for convex composite conic programming" @default.
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• W2732922863 hasPublicationYear "2017" @default.
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