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Dynamic lot sizing for multiple products with a new joint replenishment model

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  • Lu, Liang
  • Qi, Xiangtong

Abstract

This paper studies a new multi-product dynamic lot sizing problem, where the inventories of all products are replenished jointly with the same quantity whenever a production occurs. Such problems may occur in poultry and some chemical industries. We first introduce the general problem that allows for demand rejection with lost sales cost, and prove that the problem is NP-hard. Then we study a special case where all demands have to be satisfied immediately, and show that it can be solved in polynomial time. Finally, we develop two heuristic algorithms for the general problem. Through computational experiments, we demonstrate the effectiveness of the heuristics and investigate some insights related to the decision of lost sales.

Suggested Citation

  • Lu, Liang & Qi, Xiangtong, 2011. "Dynamic lot sizing for multiple products with a new joint replenishment model," European Journal of Operational Research, Elsevier, vol. 212(1), pages 74-80, July.
    • Handle: RePEc:eee:ejores:v:212:y:2011:i:1:p:74-80
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Suzanne, Elodie & Absi, Nabil & Borodin, Valeria & van den Heuvel, Wilco, 2020. "A single-item lot-sizing problem with a by-product and inventory capacities," European Journal of Operational Research, Elsevier, vol. 287(3), pages 844-855.
    2. Suzanne, Elodie & Absi, Nabil & Borodin, Valeria, 2020. "Towards circular economy in production planning: Challenges and opportunities," European Journal of Operational Research, Elsevier, vol. 287(1), pages 168-190.
    3. He-Yau Kang & Amy H.I. Lee & Chien-Wei Wu & Cheng-Han Lee, 2017. "An efficient method for dynamic-demand joint replenishment problem with multiple suppliers and multiple vehicles," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1065-1084, February.
    4. Yongjian Li & Xiaoqiang Cai & Lei Xu & Wenxia Yang, 2016. "Heuristic approach on dynamic lot-sizing model for durable products with end-of-use constraints," Annals of Operations Research, Springer, vol. 242(2), pages 265-283, July.
    5. Mohammad Ebrahim Arbabian & Shi Chen & Kamran Moinzadeh, 2021. "Capacity Expansions with Bundled Supplies of Attributes: An Application to Server Procurement in Cloud Computing," Manufacturing & Service Operations Management, INFORMS, vol. 23(1), pages 191-209, 1-2.
    6. Sazvar, Z. & Mirzapour Al-e-hashem, S.M.J. & Govindan, K. & Bahli, B., 2016. "A novel mathematical model for a multi-period, multi-product optimal ordering problem considering expiry dates in a FEFO system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 232-261.
    7. Yilmaz, Dogacan & Büyüktahtakın, İ. Esra, 2024. "An expandable machine learning-optimization framework to sequential decision-making," European Journal of Operational Research, Elsevier, vol. 314(1), pages 280-296.
    8. Lu, Liang & Qi, Xiangtong & Liu, Zhixin, 2014. "On the cooperation of recycling operations," European Journal of Operational Research, Elsevier, vol. 233(2), pages 349-358.

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