Abstract
In the design and analysis of large-scale simulation experiments, It Is generally difficult to estimate model performance parameters with adequate precision at an acceptable sampling cost. This paper provides a state-of-the-art survey of the principal variance reduction techniques that can Improve the efficiency of such experiments.

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