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A demand aggregation approach for inventory control in two echelon supply chain under uncertainty

Author

Listed:
  • Peeyush Vats

    (Malaviya National Institute of Technology)

  • Gunjan Soni

    (Malaviya National Institute of Technology)

  • Ajay Pal Singh Rathore

    (Malaviya National Institute of Technology)

  • Surya Prakash Yadav

    (BML Munjal University)

Abstract

In this paper it is discussed that the demand aggregation is an effective approach for reducing inventory levels and the number of facilities under the uncertain supply and demand conditions. Therefore in this paper, an inventory control model is developed incorporating demand aggregation approach for two staged supply chain distribution network under uncertain demand conditions. The two stage of distribution network mainly consists of distributors and retailers. This inventory control model is developed as non-linear programming model with in the different alternatives of distribution networks. The main decision variables of the system are reorder point and the ordering quantity. The prime objective function in this paper is the total cost of system which mainly consists of ordering cost, inventory carrying cost, facility cost, facility operating cost and the cost of shipment. The model is solved for total cost minimization which provides the optimum inventory policy (reorder point and ordering quantity) and the minimum cost. Through this problem best alternative of distribution network is also suggested along with optimum reorder point, ordering quantity and total cost of the system. Some other vital inventory performance parameters besides of ordering quantity and reorder point are also evaluated for the system. These performance parameters are safety stocks, expected shortages per cycle, fill rates, cycle service level, average inventory etc. These performance parameters are evaluated with total cost of the system under different uncertainty levels for a desired service level. This problem also yielded the best network options in given uncertain conditions of demand and supply. This model is formulated for single product and single period. This study mainly focused on the small part of supply chain i.e. distribution network for implementing demand aggregation approach. A case study of a sugar mill distribution network has been performed for validating the industrial applications of the proposed model.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:opsear:v:56:y:2019:i:3:d:10.1007_s12597-019-00389-w
    DOI: 10.1007/s12597-019-00389-w
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    References listed on IDEAS

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    1. Yue Dai & Shu-Cherng Fang & Xiaoli Ling & Henry Nuttle, 2008. "Risk pooling strategy in a multi-echelon supply chain with price-sensitive demand," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 67(3), pages 391-421, June.
    2. Ferrer, Geraldo, 2010. "Open architecture, inventory pooling and maintenance modules," International Journal of Production Economics, Elsevier, vol. 128(1), pages 393-403, November.
    3. Weber, Charles A. & Current, John R. & Benton, W. C., 1991. "Vendor selection criteria and methods," European Journal of Operational Research, Elsevier, vol. 50(1), pages 2-18, January.
    4. Snyder, Lawrence V. & Daskin, Mark S. & Teo, Chung-Piaw, 2007. "The stochastic location model with risk pooling," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1221-1238, June.
    5. Amit Eynan & Thierry Fouque, 2005. "Benefiting from the risk-pooling effect: internal (component commonality) vs. external (demand reshape) efforts," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 1(1), pages 90-99.
    6. Gary D. Eppen, 1979. "Note--Effects of Centralization on Expected Costs in a Multi-Location Newsboy Problem," Management Science, INFORMS, vol. 25(5), pages 498-501, May.
    7. Kevin Weng, Z., 1999. "Risk-pooling over demand uncertainty in the presence of product modularity," International Journal of Production Economics, Elsevier, vol. 62(1-2), pages 75-85, May.
    8. Gerald Oeser, 2015. "Risk Pooling in Business Logistics," SpringerBriefs in Business, in: Risk-Pooling Essentials, edition 127, chapter 0, pages 5-23, Springer.
    9. Ravi Anupindi & Yehuda Bassok, 1999. "Centralization of Stocks: Retailers vs. Manufacturer," Management Science, INFORMS, vol. 45(2), pages 178-191, February.
    10. Md. Abdul Wazed & Shamsuddin Ahmed & Yusoff Nukman, 2010. "Commonality in manufacturing resources planning – issues and models: a review," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 4(2), pages 167-188.
    11. 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.
    12. Fernando Bernstein & Gregory A. DeCroix & Yulan Wang, 2011. "The Impact of Demand Aggregation Through Delayed Component Allocation in an Assemble-to-Order System," Management Science, INFORMS, vol. 57(6), pages 1154-1171, June.
    13. Schmitt, Amanda J. & Sun, Siyuan Anthony & Snyder, Lawrence V. & Shen, Zuo-Jun Max, 2015. "Centralization versus decentralization: Risk pooling, risk diversification, and supply chain disruptions," Omega, Elsevier, vol. 52(C), pages 201-212.
    14. C-T Lin & C-B Chen & H-J Hsieh, 2001. "Effects of centralization on expected profits in a multi-location newsboy problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(7), pages 839-841, July.
    15. Ganeshan, Ram, 1999. "Managing supply chain inventories: A multiple retailer, one warehouse, multiple supplier model," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 341-354, March.
    16. Yang, Hongsuk & Schrage, Linus, 2009. "Conditions that cause risk pooling to increase inventory," European Journal of Operational Research, Elsevier, vol. 192(3), pages 837-851, February.
    17. Braglia, M. & Frosolini, M., 2013. "Virtual pooled inventories for equipment-intensive industries. An implementation in a paper district," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 26-37.
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    3. Najoung Lim & Seojin Kim & Rajshree Agarwal, 2023. "Weathering a demand shock: The impact of prior vertical scope on post‐shock firm response," Strategic Management Journal, Wiley Blackwell, vol. 44(8), pages 1965-2004, August.

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