• DocumentCode
    2177905
  • Title

    The mathematics of continuous-variable simulation optimization

  • Author

    Kim, Sujin ; Henderson, Shane G.

  • Author_Institution
    Dept. of Ind. & Syst. Eng., Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2008
  • fDate
    7-10 Dec. 2008
  • Firstpage
    122
  • Lastpage
    132
  • Abstract
    Continuous-variable simulation optimization problems are those optimization problems where the objective function is computed through stochastic simulation and the decision variables are continuous. We discuss verifiable conditions under which the objective function is continuous or differentiable, and outline some key properties of two classes of methods for solving such problems, namely sample-average approximation and stochastic approximation.
  • Keywords
    approximation theory; optimisation; stochastic processes; continuous-variable simulation optimization; decision variables; objective function; sample-average approximation; stochastic approximation; stochastic simulation; Analytical models; Approximation algorithms; Computational modeling; Euclidean distance; Mathematics; Operations research; Optimization methods; Stochastic processes; Sufficient conditions; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference, 2008. WSC 2008. Winter
  • Conference_Location
    Austin, TX
  • Print_ISBN
    978-1-4244-2707-9
  • Electronic_ISBN
    978-1-4244-2708-6
  • Type

    conf

  • DOI
    10.1109/WSC.2008.4736062
  • Filename
    4736062