An optimal sequential procedure for selecting the best bernoulli process—a review

This article describes a new closed adaptive sequential procedure proposed by Bechhofer and Kulkarni for selecting the Bernoulli population which has the largest success probability. It can be used effectively for selecting the production process with the largest proportion of conforming items, and thus is applicable in vendor selection situations. The performance of this procedure is compared to that of the Sobel-Huyett single-stage procedure, and to a curtailed version of the single-stage procedure, all of which guarantee the same probability of a correct selection. Optimal properties of the Bechhofer-Kulkarni procedure are stated; quantitative assessments of important performance characteristics of the procedure are given. These demonstrate conclusively the superiority of the new procedure over that of the competing procedures. Relevant areas of application (including clinical trials) are described. Appropriate literature references are provided.