Advances in Decision Sciences
Volume 2010 (2010), Article ID 948359, 12 pages
doi:10.1155/2010/948359
A new approach to estimate the critical constant of selection procedures
E.Jack Chen1
and Min Li2
1Business Systems, BASF Corporation, 333 Mount Hope Avenue, Rockaway, NJ 07866-0909, USA
2College of Business Administration, California State University, Sacramento, 6000 J Street, Sacramento, CA 95819-6088, USA
Abstract
A solution to the ranking and selection problem of determining a subset of size m containing at least c of the v best from k normal distributions has been developed. The best distributions are those having, for example, (i) the smallest means, or (ii) the smallest variances. This paper reviews various applicable algorithms and supplies the operating constants needed to apply these solutions. The constants are computed using a histogram approximation algorithm and Monte Carlo integration.