  Group testing is a well-known search problem that consists in detecting of
$s$ defective members of a set of $t$ samples by carrying out tests on properly
chosen subsets of samples. In classical group testing the goal is to find all
defective elements by using the minimal possible number of tests in the worst
case. In this work, a multistage group testing problem is considered. Our goal
is to construct a multistage search procedure, having asymptotically the same
number of tests as the optimal adaptive algorithm. We propose a new approach to
designing multistage algorithms, which allows us to construct a 5-stage
algorithm for finding 3 defectives with the optimal number $3\log_2t(1+o(1))$
of tests.
