A decision-theoretic approach to screening and selection with common random numbers

The article describes some recently-proposed procedures that identify the best simulated system when common random numbers are used. The procedures are based on a Bayesian average-case analysis, rather than a worst-case indifference zone formulation. The procedures allow decision makers to focus on reducing either the expected opportunity cost loss associated with potentially selecting an inferior system, or the probability of incorrect selection. Numerical experiments indicate that the new procedures outperform two existing procedures with respect to several criteria for a well-known selection problem