Article ID: | iaor20082533 |
Country: | United States |
Volume: | 55 |
Issue: | 4 |
Start Page Number: | 733 |
End Page Number: | 752 |
Publication Date: | Jul 2007 |
Journal: | Operations Research |
Authors: | Helmberg C., Rhl S. |
Keywords: | inventory |
For a real-world problem – transporting pallets between warehouses 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 five to 12 minutes for up to three warehouses and 40,000 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.