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On decentralized convex optimization in a multi-agent setting with separable constraints and its application to optimal charging of electric vehicles

Abstract:

We develop a decentralized algorithm for multiagent, convex optimization programs, subject to separable constraints, where the constraint function of each agent involves only its local decision vector, while the decision vectors of all agents are coupled via a common objective function. We construct a variant of the so called Jacobi algorithm and show that, when the objective function is quadratic, convergence to some minimizer of the centralized problem counterpart is achieved. Our algorithm...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/CDC.2016.7799197

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
Proceedings of the IEEE Conference on Decision & Control / IEEE Control Systems Society. IEEE Conference on Decision & Control Journal website
Host title:
Proceedings of the IEEE Conference on Decision & Control / IEEE Control Systems Society. IEEE Conference on Decision & Control
Publication date:
2016-12-01
Acceptance date:
2016-09-12
DOI:
ISSN:
0743-1546
Source identifiers:
642279
Pubs id:
pubs:642279
UUID:
uuid:5121b8c3-53e3-4da4-82b3-3c3797945323
Local pid:
pubs:642279
Deposit date:
2016-09-12

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