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Optimal scaling of the ADMM algorithm for distributed quadratic programming
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-5491-4068
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-1835-2963
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2013 (English)In: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC), IEEE conference proceedings, 2013, 6868-6873 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper addresses the optimal scaling of the ADMM method for distributed quadratic programming. Scaled ADMM iterations are first derived for generic equalityconstrained quadratic problems and then applied to a class of distributed quadratic problems. In this setting, the scaling corresponds to the step-size and the edge-weights of the underlying communication graph. We optimize the convergence factor of the algorithm with respect to the step-size and graph edge-weights. Explicit analytical expressions for the optimal convergence factor and the optimal step-size are derived. Numerical simulations illustrate our results.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2013. 6868-6873 p.
Series
IEEE Conference on Decision and Control. Proceedings, ISSN 0743-1546
Keyword [en]
Algorithms, Analytical expressions, Communication graphs, Convergence factor, Edge weights, Optimal convergence, Optimal step-size, Quadratic problem, Step size, Quadratic programming
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-150985DOI: 10.1109/CDC.2013.6760977ISI: 000352223507114Scopus ID: 2-s2.0-84902327025ISBN: 978-146735717-3 (print)OAI: oai:DiVA.org:kth-150985DiVA: diva2:746356
Conference
52nd IEEE Conference on Decision and Control, CDC 2013, 10 December 2013 through 13 December 2013, Florence, Italy
Note

QC 20140912

Available from: 2014-09-12 Created: 2014-09-12 Last updated: 2015-12-08Bibliographically approved

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preprint(926 kB)97 downloads
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Teixeira, AndréSandberg, Henrik

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