An accelerated augmented Lagrangian method for linearly constrained convex programming with the rate of convergence O(1/k2)

In this paper, we propose and analyze an accelerated augmented Lagrangian method (denoted by AALM) for solving the linearly constrained convex programming. We show that the convergence rate of AALM is O (1/ k 2 ) while the convergence rate of the classical augmented Lagrangian method (ALM) is O (1/...

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Vydané v:	Applied Mathematics-A Journal of Chinese Universities Ročník 32; číslo 1; s. 117 - 126
Hlavní autori:	Ke, Yi-fen, Ma, Chang-feng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Hangzhou Editorial Committee of Applied Mathematics - A Journal of Chinese Universities 01.03.2017 Springer Nature B.V
Predmet:	Applications of Mathematics Convergence Convexity Lagrange multiplier Mathematics Mathematics and Statistics Nonlinear programming convex programming augmented Lagrangian method accelerated technique linearly constrained
ISSN:	1005-1031, 1993-0445
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