English, Article, Journal or magazine article edition: Asymptotically Optimal Allocation of Simulation Experiments in Discrete Stochastic Optimization. A. Futschik; G.C. Pflug

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Bookmark: http://trove.nla.gov.au/version/138281
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Asymptotically Optimal Allocation of Simulation Experiments in Discrete Stochastic Optimization.
Author
  • A. Futschik
  • G.C. Pflug
Physical Description
  • preprint
Notes
  • Approximate solutions for discrete stochastic optimization problems are often obtained via simulation. It is reasonable to complement these solutions by confidence regions for the argmin-set. We address the question, how a certain total number of random draws should be distributed among the set of alternatives. We propose a one-step allocation rule which turns out to be asymptotically optimal in the case of normal errors for two goals: To minimize the costs caused by using only an approximate solution and to minimize the expected size of the confidence sets.
  • RePEc:wop:iasawp:wp96023
Language
  • English
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