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Inventory control in a two-level supply chain with risk pooling effect

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  • Kang, Jae-Hun
  • Kim, Yeong-Dae

Abstract

We consider an inventory control problem in a supply chain consisting of a single supplier, with a central distribution center (CDC) and multiple regional warehouses, and multiple retailers. We focus on the problem of selecting warehouses to be used among a set of candidate warehouses, assigning each retailer to one of the selected warehouses and determining replenishment plans for the warehouses and the retailers. For the problem with the objective of minimizing the sum of warehouse operation costs, inventory holding costs at the warehouses and the retailers, and transportation costs from the CDC to warehouses as well as from warehouses to retailers, we present a non-linear mixed integer programming model and develop a heuristic algorithm based on Lagrangian relaxation and subgradient optimization methods. A series of computational experiments on randomly generated test problems shows that the heuristic algorithm gives relatively good solutions in a reasonable computation time.

Suggested Citation

  • Kang, Jae-Hun & Kim, Yeong-Dae, 2012. "Inventory control in a two-level supply chain with risk pooling effect," International Journal of Production Economics, Elsevier, vol. 135(1), pages 116-124.
    • Handle: RePEc:eee:proeco:v:135:y:2012:i:1:p:116-124
    DOI: 10.1016/j.ijpe.2010.11.014
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    3. Aaron Guerrero Campanur & Elias Olivares-Benitez & Pablo A. Miranda & Rodolfo Eleazar Perez-Loaiza & Jose Humberto Ablanedo-Rosas, 2018. "Design of a Logistics Nonlinear System for a Complex, Multiechelon, Supply Chain Network with Uncertain Demands," Complexity, Hindawi, vol. 2018, pages 1-16, November.
    4. Edirisinghe, Chanaka & Atkins, Derek, 2017. "Lower bounding inventory allocations for risk pooling in two-echelon supply chains," International Journal of Production Economics, Elsevier, vol. 187(C), pages 159-167.
    5. Schlaich, Tim & Hoberg, Kai, 2024. "When is the next order? Nowcasting channel inventories with Point-of-Sales data to predict the timing of retail orders," European Journal of Operational Research, Elsevier, vol. 315(1), pages 35-49.
    6. Darmawan, Agus & Wong, Hartanto & Thorstenson, Anders, 2021. "Supply chain network design with coordinated inventory control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    7. Peeyush Vats & Gunjan Soni & Ajay Pal Singh Rathore & Surya Prakash Yadav, 2019. "A demand aggregation approach for inventory control in two echelon supply chain under uncertainty," OPSEARCH, Springer;Operational Research Society of India, vol. 56(3), pages 840-868, September.
    8. Hêris Golpîra, 2017. "Robust bi-level optimization for an opportunistic supply chain network design problem in an uncertain and risky environment," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(1), pages 21-41.
    9. Fahimnia, Behnam & Jabbarzadeh, Armin & Ghavamifar, Ali & Bell, Michael, 2017. "Supply chain design for efficient and effective blood supply in disasters," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 700-709.
    10. Williams, Brent D. & Waller, Matthew A. & Ahire, Sanjay & Ferrier, Gary D., 2014. "Predicting retailer orders with POS and order data: The inventory balance effect," European Journal of Operational Research, Elsevier, vol. 232(3), pages 593-600.
    11. Taleizadeh, Ata Allah & Shokr, Iman & Konstantaras, Ioannis & VafaeiNejad, Mahyar, 2020. "Stock replenishment policies for a vendor-managed inventory in a retailing system," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).

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