  The minimum aberration criterion has been frequently used in the selection of
fractional factorial designs with nominal factors. For designs with
quantitative factors, however, level permutation of factors could alter their
geometrical structures and statistical properties. In this paper uniformity is
used to further distinguish fractional factorial designs, besides the minimum
aberration criterion. We show that minimum aberration designs have low
discrepancies on average. An efficient method for constructing uniform minimum
aberration designs is proposed and optimal designs with 27 and 81 runs are
obtained for practical use. These designs have good uniformity and are
effective for studying quantitative factors.
