  We consider the constrained assortment optimization problem under the mixed
multinomial logit model. Even moderately sized instances of this problem are
challenging to solve directly using standard mixed-integer linear optimization
formulations. This has motivated recent research exploring customized
optimization strategies and approximation techniques. In contrast, we develop a
novel conic quadratic mixed-integer formulation. This new formulation, together
with McCormick inequalities exploiting the capacity constraints, enables the
solution of large instances using commercial optimization software.
