Abstract: Motivated by the recent success of
integer programming based procedures for computing discrete forecast horizons,
we consider two-product variants of the classical dynamic lot-size model. In the
first variant, we impose a warehouse capacity constraint on the total ending
inventory of the two products in any period. In the second variant, the two
products have both individual and joint setup costs for production. To our
knowledge, there are no known procedures for computing forecast horizons for
these variants.
Under the assumption that future demands are discrete, we characterize forecast
horizons for these two variants as feasibility/optimality questions in 0-1 mixed
integer programs. A detailed computational study establishes the effectiveness
of our approach and enables us to gain valuable insights into the behavior of
minimal forecast horizons.