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A Case Study of Joint Online Truck Scheduling and Inventory Management for Multiple Warehouses

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  • C. Helmberg

    (Fakultät für Mathematik, Technische Universität Chemnitz, D-09107 Chemnitz, Germany)

  • S. Röhl

    (Vorarlberg University of Applied Sciences, A-6850 Dornbirn, Austria)

Abstract

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.

Suggested Citation

  • C. Helmberg & S. Röhl, 2007. "A Case Study of Joint Online Truck Scheduling and Inventory Management for Multiple Warehouses," Operations Research, INFORMS, vol. 55(4), pages 733-752, August.
    • Handle: RePEc:inm:oropre:v:55:y:2007:i:4:p:733-752
    DOI: 10.1287/opre.1060.0374
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    References listed on IDEAS

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    2. Eduardo Pérez & Lewis Ntaimo & César Malavé & Carla Bailey & Peter McCormack, 2013. "Stochastic online appointment scheduling of multi-step sequential procedures in nuclear medicine," Health Care Management Science, Springer, vol. 16(4), pages 281-299, December.

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