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

Abstract

This article describes a new closed adaptive sequcntial procedure proposed by Bechhofer and Kulkarnit for selecting the Bernoulli population which has the largest success probability. It can be used effectively for selecting the production proccss 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 thc Sobel-Huyettf 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 arcas of application (including clinical trials) are described. Appropriate literature references are provided.

An analytical approximation and a neural network model for optimal sample size in vendor selection

“…The BK, and BK, procedures, and another procedure referred to as Singlastage in which one samples exactly n items from each vendor to select the vendor with the larger number of conforming items, were compared by Bechhofer 1985. It was shown that BK, performs better than the rivals in terms of the total number sampled from both vendors before a decision is reached, as well as the number of items sampled from the vendor with inferior items.…”

Painted network flows with weighted divergence

“…As a good bibliography of these publications, we suggest Gibbons et al (1977). Bechhofer (1985) and Kulkarni (1981) developed an optimal multistage procedure for selecting the best one among k popu lations. Unlike the single-stage procedure of Sobel and Huyett, this multistage procedure minimizes the expected number of observations that need to be sampled before the stopping rule is reached.…”