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Setting safety stocks in multi-stage inventory systems under rolling horizon mathematical programming models

In: Supply Chain Planning

Author

Listed:
  • Youssef Boulaksil

    (Technische Universiteit Eindhoven)

  • Jan C. Fransoo

    (Technische Universiteit Eindhoven)

  • Ernico N. G. van Halm

    (Organon N.V.)

Abstract

This paper considers the problem of determining safety stocks in multi-item multi-stage inventory systems that face demand uncertainties. Safety stocks are necessary to make the supply chain, which is driven by forecasts of customer orders, responsive to (demand) uncertainties and to achieve predefined target service levels. Although there exists a large body of literature on determining safety stock levels, this literature does not provide an effective methodology that can address complex multi-constrained supply chains. In this paper, the problem of determining safety stocks is addressed by a simulation based approach, where the simulation studies are based on solving the supply chain planning problem (formulated as a mathematical programming model) in a rolling horizon setting. To demonstrate the utility of the proposed approach, an application of the approach at Organon, a worldwide operating biopharmaceutical company, will be discussed.

Suggested Citation

  • Youssef Boulaksil & Jan C. Fransoo & Ernico N. G. van Halm, 2009. "Setting safety stocks in multi-stage inventory systems under rolling horizon mathematical programming models," Springer Books, in: Herbert Meyr & Hans-Otto Günther (ed.), Supply Chain Planning, pages 199-218, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-93775-3_8
    DOI: 10.1007/978-3-540-93775-3_8
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    Citations

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    Cited by:

    1. Boulaksil, Youssef, 2016. "Safety stock placement in supply chains with demand forecast updates," Operations Research Perspectives, Elsevier, vol. 3(C), pages 27-31.
    2. Barros, Júlio & Cortez, Paulo & Carvalho, M. Sameiro, 2021. "A systematic literature review about dimensioning safety stock under uncertainties and risks in the procurement process," Operations Research Perspectives, Elsevier, vol. 8(C).
    3. Lejeune, Miguel A., 2013. "Probabilistic modeling of multiperiod service levels," European Journal of Operational Research, Elsevier, vol. 230(2), pages 299-312.
    4. Osman, Hany & Demirli, Kudret, 2012. "Integrated safety stock optimization for multiple sourced stockpoints facing variable demand and lead time," International Journal of Production Economics, Elsevier, vol. 135(1), pages 299-307.
    5. Moncayo-Martínez, Luis A. & Zhang, David Z., 2013. "Optimising safety stock placement and lead time in an assembly supply chain using bi-objective MAX–MIN ant system," International Journal of Production Economics, Elsevier, vol. 145(1), pages 18-28.
    6. Boulaksil, Youssef & Fransoo, Jan C., 2009. "Order release strategies to control outsourced operations in a supply chain," International Journal of Production Economics, Elsevier, vol. 119(1), pages 149-160, May.

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