Optimal scaling of the ADMM algorithm for distributed quadratic programming
2013 (English)In: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC), IEEE conference proceedings, 2013, 6868-6873 p.Conference paper (Refereed)
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.
, IEEE Conference on Decision and Control. Proceedings, ISSN 0743-1546
Algorithms, Analytical expressions, Communication graphs, Convergence factor, Edge weights, Optimal convergence, Optimal step-size, Quadratic problem, Step size, Quadratic programming
Other Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-150985DOI: 10.1109/CDC.2013.6760977ISI: 000352223507114ScopusID: 2-s2.0-84902327025ISBN: 978-146735717-3OAI: oai:DiVA.org:kth-150985DiVA: diva2:746356
52nd IEEE Conference on Decision and Control, CDC 2013, 10 December 2013 through 13 December 2013, Florence, Italy
QC 201409122014-09-122014-09-122015-12-08Bibliographically approved