A dual decomposition algorithm for separable nonconvex optimization using the penalty function framework

We propose a dual decomposition method for solving separable nonconvex optimization problems that arise e.g. in distributed model predictive control over networks. We first derive a new sequential convex programming (SCP) scheme based on penalty function approach to handle nonconvexity. Then, we com...

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Bibliographic Details

Published in:	52nd IEEE Conference on Decision and Control pp. 2372 - 2377
Main Authors:	Quoc Tran Dinh, Necoara, Ion, Diehl, Moritz
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.12.2013
Subjects:	Convergence Convex functions Decentralized control Optimization Prediction algorithms Programming Vectors
ISBN:	1467357146, 9781467357142
ISSN:	0191-2216
Online Access:	Get full text
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