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An augmented Lagrangian method for distributed optimization
We propose a novel distributed method for convex optimization problems with a certain separability structure. The method is based on the augmented Lagrangian framework. We analyze its convergence and provide an application to two network models, as well as to a two-stage stochastic optimization prob...
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Published in: | Mathematical programming 2015-08, Vol.152 (1-2), p.405-434 |
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creator | Chatzipanagiotis, Nikolaos Dentcheva, Darinka Zavlanos, Michael M. |
description | We propose a novel distributed method for convex optimization problems with a certain separability structure. The method is based on the augmented Lagrangian framework. We analyze its convergence and provide an application to two network models, as well as to a two-stage stochastic optimization problem. The proposed method compares favorably to two augmented Lagrangian decomposition methods known in the literature, as well as to decomposition methods based on the ordinary Lagrangian function. |
doi_str_mv | 10.1007/s10107-014-0808-7 |
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subjects | Algorithms Approximation Calculus of Variations and Optimal Control Optimization Combinatorics Convergence Convex analysis Decomposition Full Length Paper Lagrange multiplier Mathematical analysis Mathematical and Computational Physics Mathematical Methods in Physics Mathematical models Mathematical programming Mathematics Mathematics and Statistics Mathematics of Computing Methods Network management systems Networks Numerical Analysis Optimization Stochasticity Studies Theoretical |
title | An augmented Lagrangian method for distributed optimization |
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