Group testing: Revisiting the ideas

被引:1
|
作者
Skorniakov, Viktor [1 ]
Leipus, Remigijus [1 ]
Juzeliunas, Gediminas [2 ]
Staliunas, Kestutis [3 ,4 ,5 ]
机构
[1] Vilnius Univ, Inst Appl Math, Naugarduko 24, LT-03225 Vilnius, Lithuania
[2] Vilnius Univ, Inst Theoret Phys & Astron, Sauletekio 3, LT-10257 Vilnius, Lithuania
[3] Vilnius Univ, Fac Phys, Laser Reseach Ctr, Sauletekio 9,Bldg 3, LT-10222 Vilnius, Lithuania
[4] Inst Catalana Recerca & Estudis Avancats ICREA, Passeig Lluis Companys 23, Barcelona 08010, Spain
[5] Univ Politecn Cataluna, Dept Fis, Barcelona 08034, Spain
来源
NONLINEAR ANALYSIS-MODELLING AND CONTROL | 2021年 / 26卷 / 03期
关键词
group testing; quick sort algorithm; COVID-19; DISEASE; PREVALENCE; TIME;
D O I
10.15388/namc.2021.26.23933
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The task of identification of randomly scattered "bad" items in a fixed set of objects is a frequent one, and there are many ways to deal with it. "Group testing" (GT) refers to the testing strategy aiming to effectively replace the inspection of single objects by the inspection of groups spanning more than one object. First announced by Dorfman in 1943, the methodology has underwent vigorous development, and though many related research still take place, the ground ideas remain the same. In the present paper, we revisit two classical GT algorithms: the Dorfman's algorithm and the halving algorithm. Our fresh treatment of the latter and expository comparison of the two is devoted to dissemination of GT ideas, which are so important in the current COVID-19 induced pandemic situation.
引用
收藏
页码:534 / 549
页数:16
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