IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v56y2019i3d10.1007_s12597-019-00389-w.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-019-00389-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12597-019-00389-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Ferrer, Geraldo, 2010. "Open architecture, inventory pooling and maintenance modules," International Journal of Production Economics, Elsevier, vol. 128(1), pages 393-403, November.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Gerald Oeser, 2015. "Risk Pooling in Business Logistics," SpringerBriefs in Business, in: Risk-Pooling Essentials, edition 127, chapter 0, pages 5-23, Springer.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Ravi Anupindi & Yehuda Bassok, 1999. "Centralization of Stocks: Retailers vs. Manufacturer," Management Science, INFORMS, vol. 45(2), pages 178-191, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Makoena Sebatjane & Olufemi Adetunji, 2022. "Optimal inventory replenishment and shipment policies in a three-echelon supply chain for growing items with expiration dates," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 809-838, September.
    3. Helena Gaspars-Wieloch, 2021. "The Assignment Problem in Human Resource Project Management under Uncertainty," Risks, MDPI, vol. 9(1), pages 1-17, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Kim, Nayeon & Montreuil, Benoit & Klibi, Walid & Zied Babai, M., 2023. "Network inventory deployment for responsive fulfillment," International Journal of Production Economics, Elsevier, vol. 255(C).
    3. Eda Kemahl{i}ou{g}lu-Ziya & John J. Bartholdi, III, 2011. "Centralizing Inventory in Supply Chains by Using Shapley Value to Allocate the Profits," Manufacturing & Service Operations Management, INFORMS, vol. 13(2), pages 146-162, September.
    4. Lingxiu Dong & Nils Rudi, 2004. "Who Benefits from Transshipment? Exogenous vs. Endogenous Wholesale Prices," Management Science, INFORMS, vol. 50(5), pages 645-657, May.
    5. Jiri Chod & Nils Rudi, 2005. "Resource Flexibility with Responsive Pricing," Operations Research, INFORMS, vol. 53(3), pages 532-548, June.
    6. Sahba, Pedram & BalcIog[small tilde]lu, BarIs, 2011. "The impact of transportation delays on repairshop capacity pooling and spare part inventories," European Journal of Operational Research, Elsevier, vol. 214(3), pages 674-682, November.
    7. Daniel Granot & Greys Sošić, 2003. "A Three-Stage Model for a Decentralized Distribution System of Retailers," Operations Research, INFORMS, vol. 51(5), pages 771-784, October.
    8. Hsieh, Ying-Jiun, 2011. "Demand switching criteria for multiple products: An inventory cost analysis," Omega, Elsevier, vol. 39(2), pages 130-137, April.
    9. Zhang, Yi & Hua, Guowei & Cheng, T.C.E. & Zhang, Juliang & Fernandez, Vicenc, 2020. "Risk pooling through physical probabilistic selling," International Journal of Production Economics, Elsevier, vol. 219(C), pages 295-311.
    10. Çömez-Dolgan, Nagihan & Tanyeri, Başak, 2015. "Inventory performance with pooling: Evidence from mergers and acquisitions," International Journal of Production Economics, Elsevier, vol. 168(C), pages 331-339.
    11. Silbermayr, Lena, 2020. "A review of non-cooperative newsvendor games with horizontal inventory interactions," Omega, Elsevier, vol. 92(C).
    12. Guo, Cong & Li, Xueping, 2014. "A multi-echelon inventory system with supplier selection and order allocation under stochastic demand," International Journal of Production Economics, Elsevier, vol. 151(C), pages 37-47.
    13. Soo-Haeng Cho & Xin Wang, 2017. "Newsvendor Mergers," Management Science, INFORMS, vol. 63(2), pages 298-316, February.
    14. Sodero, Annibal C. & Namin, Aidin & Gauri, Dinesh K. & Bhaskaran, Sreekumar R., 2021. "The strategic drivers of drop-shipping and retail store sales for seasonal products," Journal of Retailing, Elsevier, vol. 97(4), pages 561-581.
    15. Yu, Guodong & Zhang, Jie, 2018. "Multi-dual decomposition solution for risk-averse facility location problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 70-89.
    16. Bernhard Fleischmann, 2016. "The impact of the number of parallel warehouses on total inventory," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(4), pages 899-920, October.
    17. Nagihan Çömez & Kathryn E. Stecke & Metin Çakanyildirim, 2012. "In-Season Transshipments Among Competitive Retailers," Manufacturing & Service Operations Management, INFORMS, vol. 14(2), pages 290-300, April.
    18. Chaolin Yang & Zhenyu Hu & Sean X. Zhou, 2021. "Multilocation Newsvendor Problem: Centralization and Inventory Pooling," Management Science, INFORMS, vol. 67(1), pages 185-200, January.
    19. Berman, Oded & Krass, Dmitry & Tajbakhsh, M. Mahdi, 2012. "A coordinated location-inventory model," European Journal of Operational Research, Elsevier, vol. 217(3), pages 500-508.
    20. Escalona, P. & Ordóñez, F. & Marianov, V., 2015. "Joint location-inventory problem with differentiated service levels using critical level policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 141-157.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:opsear:v:56:y:2019:i:3:d:10.1007_s12597-019-00389-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.