  In this paper it is shown that the compact linearization approach, that has
been previously proposed only for binary quadratic problems with assignment
constraints, can be generalized to arbitrary linear equations with positive
coefficients which considerably enlarges its applicability. We discuss special
cases of prominent quadratic combinatorial optimization problems where the
obtained compact linearization yields a continuous relaxation that is provably
as least as strong as the one obtained with an ordinary linearization.
