• DocumentCode
    2826235
  • Title

    On the rate of convergence of distributed subgradient methods for multi-agent optimization

  • Author

    Nedic, Angelia ; Ozdaglar, Asuman

  • Author_Institution
    Univ. of Illinois Urbana-Champaign, Urbana
  • fYear
    2007
  • fDate
    12-14 Dec. 2007
  • Firstpage
    4711
  • Lastpage
    4716
  • Abstract
    We study a distributed computation model for optimizing the sum of convex (nonsmooth) objective functions of multiple agents. We provide convergence results and estimates for convergence rate. Our analysis explicitly characterizes the tradeoff between the accuracy of the approximate optimal solutions generated and the number of iterations needed to achieve the given accuracy.
  • Keywords
    control system analysis; control system synthesis; convergence; decentralised control; multi-robot systems; convergence rate; distributed subgradient methods; multi-agent optimization; Algorithm design and analysis; Computational modeling; Computer industry; Convergence; Distributed computing; Electrical equipment industry; Industrial control; Optimization methods; Resource management; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2007 46th IEEE Conference on
  • Conference_Location
    New Orleans, LA
  • ISSN
    0191-2216
  • Print_ISBN
    978-1-4244-1497-0
  • Electronic_ISBN
    0191-2216
  • Type

    conf

  • DOI
    10.1109/CDC.2007.4434693
  • Filename
    4434693