Subgradient methods and consensus Algorithms for solving convex optimization problems

B Johansson, T Keviczky, M Johansson, K.H Johansson

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientific

209 Citations (Scopus)


In this paper we propose a subgradient method for solving coupled optimization problems in a distributed way given restrictions on the communication topology. The iterative procedure maintains local variables at each node and relies on local subgradient updates in combination with a consensus process. The local subgradient steps are applied simultaneously as opposed to the standard sequential or cyclic procedure. We study convergence properties of the proposed scheme using results from consensus theory and approximate subgradient methods. The framework is illustrated on an optimal distributed finite-time rendezvous problem.
Original languageEnglish
Title of host publicationProceedings of the 47th conference on decision and control
Editors Abdallah, Chaouki .T
Place of PublicationCancun, Mexico
Number of pages6
ISBN (Print)978-1-4244-3124-3
Publication statusPublished - 2008
Event47th conference on decision and control - Cancun, Mexico
Duration: 9 Dec 200811 Dec 2008

Publication series



Conference47th conference on decision and control


  • Conf.proc. > 3 pag


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