Name: Boesel

Firstname: Justin

Title: Sr. Simulation and Modeling Engineer

Institution: The MITRE Corporation

Street: 7515 Colshire Dr

City: McLean, VA

Zip-Code: 22102-7508

Country: USA

Phone: 703 883 6993

Fax: 703 883 1911


Authors: Justin Boesel

Title: Combinations of subset selection and indifference-zone procedures to select the best of a large number of systems.

Abstract: This talk presents statistically valid extensions for combining subset-selection and indifference-zone (IZ) procedures to find the best system among a large number of stochastic systems. These extensions take greater advantage of mean and variance information gained during the course of experimentation. A subset-selection procedure returns a random-sized subset that contains the best of the k systems. An IZ procedure guarantees to select the best system by doing sampling in two or more stages. In a typical IZ procedure, the total sample size required of each system increases with the total number of systems being compared and decreases with the initial sample size. Subset selection and IZ procedures can be combined by "restarting" the experiment by performing a complete two-stage IZ procedure on only those systems returned by the subset procedure. One can also perform a "rolling screen," where second-stage samples of a few systems are taken before subset selecti! on; these systems, with their reduced sample variance due to second-stage sampling, are better able to screen out inferior systems. The first extension described in this talk improves the restart procedure by using variance information from the first-stage data-information that is usually discarded-to optimize the initial sample size for the restarted experiments. The second extension improves the rolling screen procedure by sorting the systems by their first-stage (search) sample means before performing the rolling screen.