  In this paper, we consider the problem of finding a maximum cardinality
subset of vectors, given a constraint on the normalized squared length of
vectors sum. This problem is closely related to Problem 1 from (Eremeev,
Kel'manov, Pyatkin, 2016). The main difference consists in swapping the
constraint with the optimization criterion.
  We prove that the problem is NP-hard even in terms of finding a feasible
solution. An exact algorithm for solving this problem is proposed. The
algorithm has a pseudo-polynomial time complexity in the special case of the
problem, where the dimension of the space is bounded from above by a constant
and the input data are integer. A computational experiment is carried out,
where the proposed algorithm is compared to COINBONMIN solver, applied to a
mixed integer quadratic programming formulation of the problem. The results of
the experiment indicate superiority of the proposed algorithm when the
dimension of Euclidean space is low, while the COINBONMIN has an advantage for
larger dimensions.
