We study practically efficient methods for performing combinatorial group testing. We present efficient nonadaptive and two-stage combinatorial group testing algorithms, which identify the at most d items out of a given set of n items that are defective, using fewer tests for all practical set sizes. For example, our two-stage algorithm matches the information-theoretic lower bound for the number of tests in a combinatorial group testing regimen. © 2007 Society for Industrial and Applied Mathematics.
CITATION STYLE
Eppstein, D., Goodrich, M. T., & Hirschberg, D. S. (2006). Improved combinatorial group testing algorithms for real-world problem sizes. SIAM Journal on Computing, 36(5), 1360–1375. https://doi.org/10.1137/050631847
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