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

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