Estimates for Optimal Multistage Group Partition Testing

Guojiang Shao
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Abstract

In multistage group testing, the tests within the same stage are considered nonadaptive, while those conducted across different stages are adaptive. Specifically, when the pools within the same stage are disjoint, meaning that the entire set is divided into several disjoint subgroups, it is referred to as a multistage group partition testing problem, denoted as the (n, d, s) problem, where n, d, and s represent the total number of items, defectives, and stages respectively. This paper presents exact solutions for the (n, 1, s) and (n, d, 2) problems for the first time. Additionally, a general dynamic programming approach is developed for the (n, d, s) problem. Significantly I give the sharp upper and lower bounds estimates. If the defective number in unknown but bounded, I can provide an algorithm with an optimal competitive ratio in the asymptotic sense. While assuming the prior distribution of the defective items, I also establish a well performing upper and lower bound estimate to the expectation of optimal strategy
最优多阶段分组分区测试的估计值
在多阶段分组测试中,同一阶段内的测试被认为是非自适应的,而在不同阶段间进行的测试则是自适应的。具体来说,当同一阶段内的集合是不相交的,即整个集合被分成几个不相交的子组,则称为多阶段分组分区测试问题,表示为(n,d,s)问题,其中 n、d 和 s 分别代表项目总数、缺陷数和阶段数。本文首次提出了 (n, 1, s) 和 (n, d, 2) 问题的精确解。此外,还针对(n,d,s)问题提出了一种通用的动态编程方法。重要的是,我给出了尖锐的上界和下界估计值。如果缺陷数未知但有界,我可以提供一种在渐近意义上具有最优竞争率的算法。在假定缺陷项的先验分布的同时,我还建立了一个性能良好的上下限估计值,以估计最优策略的期望值
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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