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Integrated lot sizing and safety stock placement in a network of production facilities

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  • Kumar, Kunal
  • Aouam, Tarik

Abstract

In a network of production facilities, safety stock placement is determined at the network level to hedge against uncertainty in demand, while considering the production cycle time (PCT) of each stage as an exogenous parameter. The lot sizing policy at each stage affects setup time, capacity, and is a major determinant of queuing behavior and PCT. This paper integrates strategic safety stock placement and tactical lot sizing, which are typically optimized independently. We model the integrated problem to minimize system-wide production and inventory costs subject to meeting service-level requirements of external customers. We establish bounds for optimal lot sizes and extend existing safety stock placement dynamic programming algorithm to solve the integrated problem. Based on numerical experiments, we assess the value of integrating the two decisions and find that integration leads to smaller lot sizes, shorter lead times, and favors pooling of safety stocks. The setup cost, setup time, and the added value at a production stage are the most significant factors in determining the amount of savings generated through integration. In addition, simulation studies show that integration reduces PCT variability and decreases the fraction of delayed items.

Suggested Citation

  • Kumar, Kunal & Aouam, Tarik, 2018. "Integrated lot sizing and safety stock placement in a network of production facilities," International Journal of Production Economics, Elsevier, vol. 195(C), pages 74-95.
    • Handle: RePEc:eee:proeco:v:195:y:2018:i:c:p:74-95
    DOI: 10.1016/j.ijpe.2017.10.006
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    Citations

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    Cited by:

    1. Aouam, Tarik & Kumar, Kunal, 2019. "On the effect of overtime and subcontracting on supply chain safety stocks," Omega, Elsevier, vol. 89(C), pages 1-20.
    2. Ghadimi, Foad & Aouam, Tarik, 2021. "Planning capacity and safety stocks in a serial production–distribution system with multiple products," European Journal of Operational Research, Elsevier, vol. 289(2), pages 533-552.
    3. Kumar, Kunal & Aouam, Tarik, 2019. "Extending the strategic safety stock placement model to consider tactical production smoothing," European Journal of Operational Research, Elsevier, vol. 279(2), pages 429-448.
    4. Zied Bahroun & Nidhal Belgacem, 2019. "Determination of dynamic safety stocks for cyclic production schedules," Operations Management Research, Springer, vol. 12(1), pages 62-93, June.
    5. 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).
    6. Johnson, Andrew & Carnovale, Steven & Song, Ju Myung & Zhao, Yao, 2021. "Drivers of fulfillment performance in mission critical logistics systems: An empirical analysis," International Journal of Production Economics, Elsevier, vol. 237(C).
    7. Riyadh Jamegh & AllaEldin Kassam & Sawsan Sabih, 2019. "Employment of advanced approach to control inventory level by monitoring Safety Stock in Supply Chain under Uncertain environment," Proceedings of International Academic Conferences 8711585, International Institute of Social and Economic Sciences.

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