• DocumentCode
    702446
  • Title

    Randomized algorithms for semi-infinite programming problems

  • Author

    Tadic, Vladislav B. ; Meyn, Sean P. ; Tempo, Roberto

  • Author_Institution
    Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
  • fYear
    2003
  • fDate
    1-4 Sept. 2003
  • Firstpage
    3011
  • Lastpage
    3015
  • Abstract
    In this paper, we explore the possibility of applying Monte Carlo methods (i.e., randomization) to semi-infinite programming problems. Equivalent stochastic optimization problems are derived for a general class of semi-infinite programming problems. For the equivalent stochastic optimization problems, algorithms based on stochastic approximation and Monte Carlo sampling methods are proposed. The asymptotic behavior of the proposed algorithms is analyzed and sufficient conditions for their almost sure convergence are obtained.
  • Keywords
    Algorithm design and analysis; Approximation algorithms; Approximation methods; Monte Carlo methods; Optimization; Programming; Stochastic processes; Monte Carlo methods; Randomized algorithms; semi-infinite programming; stochastic approximation; stochastic optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    European Control Conference (ECC), 2003
  • Conference_Location
    Cambridge, UK
  • Print_ISBN
    978-3-9524173-7-9
  • Type

    conf

  • Filename
    7086500
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=702446