Selecting a Selection Procedure

Selection procedures are used in a variety of applications to select the best of a finite set of alternatives. "Best" is defined with respect to the largest mean, but the mean is inferred with statistical sampling, as in simulation optimization. There are a wide variety of procedures, whic...

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Bibliographic Details
Published in:Management science 2007-12, Vol.53 (12), p.1916-1932
Main Authors: Branke, Jurgen, Chick, Stephen E, Schmidt, Christian
Format: Article
Language:English
Subjects:
Allocative efficiency
Applied sciences
Approximation
Bayesian analysis
Budget allocation
Business statistics
Business studies
Efficiency metrics
Exact sciences and technology
Frequentism
Management science
Operational research. Management science
Opportunity costs
Research methods
Sampling
Sampling distributions
Selection
Simulation
Simulations
Statistical analysis
Statistical discrepancies
statistics
Studies
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Summary:Selection procedures are used in a variety of applications to select the best of a finite set of alternatives. "Best" is defined with respect to the largest mean, but the mean is inferred with statistical sampling, as in simulation optimization. There are a wide variety of procedures, which begs the question of which selection procedure to select. The main contribution of this paper is to identify, through extensive experimentation, the most effective selection procedures when samples are independent and normally distributed. We also (a) summarize the main structural approaches to deriving selection procedures, (b) formalize new sampling allocations and stopping rules, (c) identify strengths and weaknesses of the procedures, (d) identify some theoretical links between them, and (e) present an innovative empirical test bed with the most extensive numerical comparison 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 new adaptive stopping rules proposed here.
ISSN:0025-1909
1526-5501
DOI:10.1287/mnsc.1070.0721