  In this paper we introduce a new column selection strategy, named here
``Deviation Maximization", and apply it to compute rank-revealing QR
factorizations as an alternative to the well known block version of the QR
factorization with the column pivoting method, called QP3 and currently
implemented in LAPACK's xgeqp3 routine. We show that the resulting algorithm,
named QRDM, has similar rank-revealing properties of QP3 and better execution
times. We present numerical test results on a wide data set of numerically
singular matrices, which has become a reference in the recent literature.
