IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v265y2023ics092552732300244x.html
   My bibliography  Save this article

Simultaneous planning of purchase orders, production, and inventory management under demand uncertainty

Author

Listed:
  • Zamani Dadaneh, Dariush
  • Moradi, Sajad
  • Alizadeh, Behrooz

Abstract

This paper focuses on the issues of the purchase of bill of materials, production planning, and inventory management in materials and products warehouses under demand uncertainty, simultaneously. The purpose of this study is to determine the optimal volume of purchasing the raw materials from different vendors, transportation methods, and production planning over the time horizon so that with proper inventory management in the warehouses of materials and manufactured products, the total cost is minimized. This issue is defined as a multi-region, multi-supplier, multi-component, multi-product, and multi-period problem. There is a time interval between ordering and delivering the bill of materials, which depends on the region where the supplier is located. Customer demands are not predetermined, and robust optimization is employed to handle this uncertainty. Three numerical examples, based on increasing or decreasing the nominal customer demands, are presented to evaluate the robustness of the solutions and to examine the effect of conservatism level on the performance of the proposed model. Finally, the price and importance of proposed robust planning are evaluated based on random data.

Suggested Citation

  • Zamani Dadaneh, Dariush & Moradi, Sajad & Alizadeh, Behrooz, 2023. "Simultaneous planning of purchase orders, production, and inventory management under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 265(C).
  • Handle: RePEc:eee:proeco:v:265:y:2023:i:c:s092552732300244x
    DOI: 10.1016/j.ijpe.2023.109012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S092552732300244X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2023.109012?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. Boonmee, Atiwat & Sethanan, Kanchana, 2016. "A GLNPSO for multi-level capacitated lot-sizing and scheduling problem in the poultry industry," European Journal of Operational Research, Elsevier, vol. 250(2), pages 652-665.
    2. Oussama Ben-Ammar & Belgacem Bettayeb & Alexandre Dolgui, 2019. "Optimization of multi-period supply planning under stochastic lead times and a dynamic demand," Post-Print hal-02415332, HAL.
    3. Aouam, Tarik & Brahimi, Nadjib, 2013. "Integrated production planning and order acceptance under uncertainty: A robust optimization approach," European Journal of Operational Research, Elsevier, vol. 228(3), pages 504-515.
    4. Roberto Rossi & S. Armagan Tarim & Ramesh Bollapragada, 2012. "Constraint-Based Local Search for Inventory Control Under Stochastic Demand and Lead Time," INFORMS Journal on Computing, INFORMS, vol. 24(1), pages 66-80, February.
    5. Zhang, Ju-liang & Zhang, Ming-yu, 2011. "Supplier selection and purchase problem with fixed cost and constrained order quantities under stochastic demand," International Journal of Production Economics, Elsevier, vol. 129(1), pages 1-7, January.
    6. Thevenin, Simon & Ben-Ammar, Oussama & Brahimi, Nadjib, 2022. "Robust optimization approaches for purchase planning with supplier selection under lead time uncertainty," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1199-1215.
    7. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    8. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    9. S C H Leung & K K Lai & W-L Ng & Y Wu, 2007. "A robust optimization model for production planning of perishable products," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(4), pages 413-422, April.
    10. Harvey M. Wagner & Thomson M. Whitin, 1958. "Dynamic Version of the Economic Lot Size Model," Management Science, INFORMS, vol. 5(1), pages 89-96, October.
    11. Ben-Ammar, Oussama & Bettayeb, Belgacem & Dolgui, Alexandre, 2019. "Optimization of multi-period supply planning under stochastic lead times and a dynamic demand," International Journal of Production Economics, Elsevier, vol. 218(C), pages 106-117.
    12. Helber, Stefan & Sahling, Florian, 2010. "A fix-and-optimize approach for the multi-level capacitated lot sizing problem," International Journal of Production Economics, Elsevier, vol. 123(2), pages 247-256, February.
    13. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    14. Minner, Stefan, 2009. "A comparison of simple heuristics for multi-product dynamic demand lot-sizing with limited warehouse capacity," International Journal of Production Economics, Elsevier, vol. 118(1), pages 305-310, March.
    15. Wei, Cansheng & Li, Yongjian & Cai, Xiaoqiang, 2011. "Robust optimal policies of production and inventory with uncertain returns and demand," International Journal of Production Economics, Elsevier, vol. 134(2), pages 357-367, December.
    16. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    17. Varas, Mauricio & Maturana, Sergio & Pascual, Rodrigo & Vargas, Ignacio & Vera, Jorge, 2014. "Scheduling production for a sawmill: A robust optimization approach," International Journal of Production Economics, Elsevier, vol. 150(C), pages 37-51.
    18. Amy Lee & He-Yau Kang & Chun-Mei Lai, 2013. "Solving lot-sizing problem with quantity discount and transportation cost," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(4), pages 760-774.
    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. Sena Keskin & Alev Taskin, 2024. "A Novel Autoencoder-Integrated Clustering Methodology for Inventory Classification: A Real Case Study for White Goods Industry," Sustainability, MDPI, vol. 16(21), pages 1-36, October.

    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. Thevenin, Simon & Ben-Ammar, Oussama & Brahimi, Nadjib, 2022. "Robust optimization approaches for purchase planning with supplier selection under lead time uncertainty," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1199-1215.
    2. Andreas Thorsen & Tao Yao, 2017. "Robust inventory control under demand and lead time uncertainty," Annals of Operations Research, Springer, vol. 257(1), pages 207-236, October.
    3. Varas, Mauricio & Maturana, Sergio & Pascual, Rodrigo & Vargas, Ignacio & Vera, Jorge, 2014. "Scheduling production for a sawmill: A robust optimization approach," International Journal of Production Economics, Elsevier, vol. 150(C), pages 37-51.
    4. Ivanov, Dmitry, 2024. "Supply chain resilience: Conceptual and formal models drawing from immune system analogy," Omega, Elsevier, vol. 127(C).
    5. Dou, Runliang & Liu, Xin & Hou, Yanchao & Wei, Yixin, 2024. "Mitigating closed-loop supply chain risk through assessment of production cost, disruption cost, and reliability," International Journal of Production Economics, Elsevier, vol. 270(C).
    6. Brahimi, Nadjib & Absi, Nabil & Dauzère-Pérès, Stéphane & Nordli, Atle, 2017. "Single-item dynamic lot-sizing problems: An updated survey," European Journal of Operational Research, Elsevier, vol. 263(3), pages 838-863.
    7. Wei, Mingyuan & Qi, Mingyao & Wu, Tao & Zhang, Canrong, 2019. "Distance and matching-induced search algorithm for the multi-level lot-sizing problem with substitutable bill of materials," European Journal of Operational Research, Elsevier, vol. 277(2), pages 521-541.
    8. Charles, Mehdi & Dauzère-Pérès, Stéphane & Kedad-Sidhoum, Safia & Mazhoud, Issam, 2022. "Motivations and analysis of the capacitated lot-sizing problem with setup times and minimum and maximum ending inventories," European Journal of Operational Research, Elsevier, vol. 302(1), pages 203-220.
    9. Qiu, Ruozhen & Sun, Minghe & Lim, Yun Fong, 2017. "Optimizing (s, S) policies for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 880-892.
    10. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    11. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    12. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    13. Holzapfel, Andreas & Potoczki, Tobias & Kuhn, Heinrich, 2023. "Designing the breadth and depth of distribution networks in the retail trade," International Journal of Production Economics, Elsevier, vol. 257(C).
    14. Metzker Soares, Paula & Thevenin, Simon & Adulyasak, Yossiri & Dolgui, Alexandre, 2024. "Adaptive robust optimization for lot-sizing under yield uncertainty," European Journal of Operational Research, Elsevier, vol. 313(2), pages 513-526.
    15. Viktoryia Buhayenko & Dick den Hertog, 2017. "Adjustable Robust Optimisation approach to optimise discounts for multi-period supply chain coordination under demand uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 55(22), pages 6801-6823, November.
    16. Gel, Esma S. & Salman, F. Sibel, 2022. "Dynamic ordering decisions with approximate learning of supply yield uncertainty," International Journal of Production Economics, Elsevier, vol. 243(C).
    17. Garvey, Myles D. & Carnovale, Steven, 2020. "The rippled newsvendor: A new inventory framework for modeling supply chain risk severity in the presence of risk propagation," International Journal of Production Economics, Elsevier, vol. 228(C).
    18. Li, Guo & Xue, Jing & Li, Na & Ivanov, Dmitry, 2022. "Blockchain-supported business model design, supply chain resilience, and firm performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    19. Donya Rahmani & Arash Zandi & Sara Behdad & Arezou Entezaminia, 2021. "A light robust model for aggregate production planning with consideration of environmental impacts of machines," Operational Research, Springer, vol. 21(1), pages 273-297, March.
    20. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).

    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:eee:proeco:v:265:y:2023:i:c:s092552732300244x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.