• DocumentCode
    1658321
  • Title

    A recursive approach to stochastic optimization via infinitesimal perturbation analysis

  • Author

    Chong, Edwin K P

  • Author_Institution
    Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
  • Volume
    2
  • fYear
    1994
  • Firstpage
    1984
  • Abstract
    We present a general recursive framework for analyzing gradient optimization algorithms driven by infinitesimal perturbation analysis estimates. We give sufficient conditions that guarantee convergence of the algorithm to the optimizing point. We illustrate our results via examples from queueing systems
  • Keywords
    conjugate gradient methods; discrete event systems; mathematical programming; perturbation techniques; stochastic programming; convergence; general recursive framework; gradient optimization algorithms; infinitesimal perturbation analysis; infinitesimal perturbation analysis estimates; queueing systems; stochastic optimization; Algorithm design and analysis; Costs; Equations; Optimization methods; Performance analysis; Process control; Queueing analysis; Recursive estimation; Stochastic processes; Sufficient conditions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
  • Conference_Location
    Lake Buena Vista, FL
  • Print_ISBN
    0-7803-1968-0
  • Type

    conf

  • DOI
    10.1109/CDC.1994.411085
  • Filename
    411085
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1658321