An Augmented Lagrangian Coordination-Decomposition Algorithm for Solving Distributed Non-Convex Programs

A novel augmented Lagrangian method for solving non-convex programs with nonlinear cost and constraint couplings in a distributed framework is presented. The proposed decomposition algorithm is made of two layers: The outer level is a standard multiplier method with penalty on the nonlinear equality constraints, while the inner level consists of a block-coordinate descent (BCD) scheme. Based on standard results on multiplier methods and recent results on proximal regularised BCD techniques, it is proven that the method converges to a KKT point of the non-convex nonlinear program under a semi-algebraicity assumption. Efficacy of the algorithm is demonstrated on a numerical example.


Published in:
2014 American Control Conference (Acc), 4312-4317
Presented at:
American Control Conference, Portland, OR, DEC 04-06, 2014
Year:
2014
Publisher:
New York, Ieee
ISSN:
0743-1619
ISBN:
978-1-4799-3274-0
Laboratories:




 Record created 2015-04-13, last modified 2018-03-17


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