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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
Version:
Accepted Manuscript

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Publisher copy:
10.1109/CDC.2016.7799197

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Department:
Oxford, MPLS, Engineering Science
Role:
Author
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Publication date:
2016-12-05
Acceptance date:
2016-09-12
DOI:
ISSN:
0743-1546
Pubs id:
pubs:642279
URN:
uri:5121b8c3-53e3-4da4-82b3-3c3797945323
UUID:
uuid:5121b8c3-53e3-4da4-82b3-3c3797945323
Local pid:
pubs:642279

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