New developments in ranking and selection: an empirical comparison of the three main approaches

Selection procedures are used in many applications to select the best of a finite set of alternatives, as in discrete optimization with simulation. There are a wide variety of procedures, which begs the question of which selection procedure to select. This paper (a) summarizes the main structural approaches to deriving selection procedures, (b) describes an innovative empirical testbed, and (c) summarizes results from work in progress that provides the most exhaustive assessment of selection procedures to date. The most efficient and easiest to control procedures allocate samples with a Bayesian model for uncertainty about the means, and use a new expected opportunity cost-based stopping rule.

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