Academic Editor: Eric J. Beh
Copyright © 2010 E. Jack Chen and Min Li. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
A solution to the ranking and selection problem of determining a subset of size containing at least of the best from 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.