• DocumentCode
    239114
  • Title

    Efficient stratified sampling implementations in multiresponse simulation

  • Author

    Basoglu, Ismail ; Hormann, Wolfgang

  • Author_Institution
    Dept. of Int. Logistics Manage., Kemerburgaz Univ., Istanbul, Turkey
  • fYear
    2014
  • fDate
    7-10 Dec. 2014
  • Firstpage
    757
  • Lastpage
    768
  • Abstract
    Often the accurate estimation of multiple values from a single simulation is of practical importance. Among the many variance reduction methods known in the literature, stratified sampling is especially useful for such a task as the allocation fractions can be used as decision variables to minimize the overall error of all estimates. Two different classes of overall error functions are proposed. The first, including the mean squared absolute and the mean squared relative error, allows for a simple closed-form solution. For the second class of error functions, including the maximal absolute and the maximal relative error, a simple and fast heuristic is proposed. The application of the new method, called “multiresponse stratified sampling”, and its performance are demonstrated with numerical examples.
  • Keywords
    Monte Carlo methods; mean square error methods; sampling methods; simulation; allocation fraction; closed-form solution; decision variable; maximal absolute error; maximal relative error; mean squared absolute error; mean squared relative error; multiresponse simulation; multiresponse stratified sampling; overall error function; stratified sampling implementation; variance reduction method; Linear programming; Mathematical model; Monte Carlo methods; Nickel; Optimization; Resource management; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference (WSC), 2014 Winter
  • Conference_Location
    Savanah, GA
  • Print_ISBN
    978-1-4799-7484-9
  • Type

    conf

  • DOI
    10.1109/WSC.2014.7019938
  • Filename
    7019938