For a real world problem – transporting pallets between warehouses in order to
guarantee sufficient supply for known and additional stochastic demand – we propose
a solution approach via convex relaxation of an integer programming formulation,
suitable for online optimization. The essential new element linking routing and
inventory management is a convex piecewise linear cost function that is based on
minimizing the expected number of pallets that still need transportation. For speed,
the convex relaxation is solved approximately by a bundle approach yielding an
online schedule in 5 to 12 minutes for up to 3 warehouses and 40000 articles; in
contrast, computation times of state of the art LP-solvers are prohibitive for online
application. In extensive numerical experiments on a real world data stream, the
approximate solutions exhibit negligible loss in quality; in long term simulations the
proposed method reduces the average number of pallets needing transportation due
to short term demand to less than half the number observed in the data stream.