  We present some optimal criteria to evaluate model-robustness of non-regular
two-level fractional factorial designs. Our method is based on minimizing the
sum of squares of all the off-diagonal elements in the information matrix, and
considering expectation under appropriate distribution functions for unknown
contamination of the interaction effects. By considering uniform distributions
on symmetric support, our criteria can be expressed as linear combinations of
$B_s(d)$ characteristic, which is used to characterize the generalized minimum
aberration. We give some empirical studies for 12-run non-regular designs to
evaluate our method.
