Doctoral thesis, 2013

Group testing (GT) was originally proposed during the World War II in an attempt to minimize the \emph{cost} and \emph{waiting time} in performing identical blood tests of the soldiers for a low-prevalence disease.
Formally, the GT problem asks to find $d\ll n$ \emph{defective} elements out of $n$ elements by querying subsets (pools) for the presence of defectives.
By the information-theoretic lower bound, essentially $d\log_2 n$ queries are needed in the worst-case.
An \emph{adaptive} strategy proceeds sequentially by performing one query at a time, and it can achieve the lower bound. In various applications, nothing is known about $d$ beforehand and a strategy for this scenario is called \emph{competitive}. Such strategies are usually adaptive and achieve query optimality within a constant factor called the \emph{competitive ratio}.
In many applications, queries are time-consuming. Therefore, \emph{minimal-adaptive} strategies which run in a small number $s$ of stages of parallel
queries are favorable.
This work is mainly devoted to the design of minimal-adaptive strategies combined with other demands of both theoretical and practical interest. First we target unknown $d$ and show that actually competitive GT is possible in as few as $2$ stages only.
The main ingredient is our randomized estimate of a previously unknown $d$ using nonadaptive queries.
In addition, we have developed a systematic approach to obtain optimal competitive ratios for our strategies.
When $d$ is a known upper bound,
we propose randomized GT strategies which asymptotically achieve query optimality in just $2$, $3$ or $4$ stages depending upon the growth of $d$ versus $n$.
Inspired by application settings, such as at American Red Cross, where in most cases GT is applied to small instances, \textit{e.g.}, $n=16$. We extended our study of query-optimal GT strategies to solve a given problem instance with fixed values $n$, $d$ and $s$. We also considered the situation when
elements to test cannot be divided physically (electronic devices), thus the pools must be disjoint. For GT with \emph{disjoint} simultaneous pools, we show that $\Theta (sd(n/d)^{1/s})$ tests are sufficient, and also necessary for certain ranges of the parameters.

strict group testing

disjoint pools

randomization

competitive group testing

minimal-adaptive group testing

exact bounds

competitive ratio

Chalmers, Computer Science and Engineering (Chalmers), Computing Science (Chalmers)

Algorithmica,; Vol. 67(2013)p. 324-354

**Journal article**

Lecture Notes in Computer Science,; Vol. 7147(2012)p. 214-225

**Paper in proceedings**

Discrete Mathematics, Algorithms and Applications,; Vol. 2(2010)p. 291-311

**Journal article**

19th International Computing and Combinatorics Conference COCOON 2013, Lecture Notes in Computer Science,; Vol. 7936(2013)p. 446-457

**Paper in proceedings**

Discrete Mathematics, Algorithms and Applications,; Vol. 3(2011)p. 517-536

**Journal article**

Information and Communication Technology

Sustainable development

Basic sciences

Computer Science

978-91-7385-913-4

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 3594

Technical report D - Department of Computer Science and Engineering, Chalmers University of Technology and Göteborg University: 98D

Room EF, EDIT building, Chalmers.

Opponent: Prof. Dr. Ingo Althöfer