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Perspectives of inventory control models in the Physical Internet: A simulation study

Author

Listed:
  • Shenle Pan

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Michele Nigrelli

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Eric Ballot

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Rochdi Sarraj

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Yanyan Yang

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

Abstract

Classical supply chain design relies on a hierarchical organization to store and distribute products over a given geographical area. Within this framework, a stock shortage affects the entire downstream section of the supply chain, regardless of the stocks kept in other locations. With the implementation of the Physical Internet (PI) approach, of which the aim is to integrate logistics networks into a universal, interconnected system, inventories can be divided among shared hubs that serve the market and allow for Source Substitution. This contribution measures the impact of such an organization on inventory levels and costs, with service level being set as a constraint. The analysis focuses on the resource levels (transportation and inventory) required by the current supply model and by the Physical Internet system to serve a market with a (Q, R) stock policy. Starting with two supply models and with the definition of cost models, as well as inventory policy, the work is based on computer simulation. The analysis tested three different categories of criteria to allow dynamic source selection when an order is placed: Source Substitution, Minimum Ratio and Minimum Sum. Source Substitution, one of the simplest criteria, was determined to be the most efficient and stable according to different scenarios. The main intent of this paper is to define the new research question related to inventory management in a Physical Internet Network and to provide a view of how the PI affects traditional inventory control policies.

Suggested Citation

  • Shenle Pan & Michele Nigrelli & Eric Ballot & Rochdi Sarraj & Yanyan Yang, 2015. "Perspectives of inventory control models in the Physical Internet: A simulation study," Post-Print hal-01112144, HAL.
  • Handle: RePEc:hal:journl:hal-01112144
    DOI: 10.1016/j.cie.2014.11.027
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    Citations

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    Cited by:

    1. Nguyen, Tiep & Duong, Quang Huy & Nguyen, Truong Van & Zhu, You & Zhou, Li, 2022. "Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 244(C).
    2. Leung, Eric K.H. & Lee, Carmen Kar Hang & Ouyang, Zhiyuan, 2022. "From traditional warehouses to Physical Internet hubs: A digital twin-based inbound synchronization framework for PI-order management," International Journal of Production Economics, Elsevier, vol. 244(C).
    3. 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).
    4. Van der Heide, G. & Buijs, P. & Roodbergen, K.J. & Vis, I.F.A., 2018. "Dynamic shipments of inventories in shared warehouse and transportation networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 240-257.
    5. Yanyan Yang & Shenle Pan & Eric Ballot, 2017. "Mitigating supply chain disruptions through interconnected logistics services in the Physical Internet," International Journal of Production Research, Taylor & Francis Journals, vol. 55(14), pages 3970-3983, July.
    6. Yingfeng Zhang & Sichao Liu & Yang Liu & Rui Li, 2016. "Smart box-enabled product–service system for cloud logistics," International Journal of Production Research, Taylor & Francis Journals, vol. 54(22), pages 6693-6706, November.
    7. Tan, Bing Qing & Xu, Su Xiu & Kang, Kai & Xu, Gangyan & Qin, Wei, 2021. "A reverse Vickrey auction for physical internet (PI) enabled parking management systems," International Journal of Production Economics, Elsevier, vol. 235(C).
    8. Fahim, Patrick B.M. & Rezaei, Jafar & Montreuil, Benoit & Tavasszy, Lorant, 2022. "Port performance evaluation and selection in the Physical Internet," Transport Policy, Elsevier, vol. 124(C), pages 83-94.
    9. Yanyan Yang & Shenle Pan & Eric Ballot, 2015. "An inventory control model with interconnected logistic services for vendor inventory management," Post-Print hal-01217344, HAL.
    10. Jianming Yao, 2017. "Optimisation of one-stop delivery scheduling in online shopping based on the physical Internet," International Journal of Production Research, Taylor & Francis Journals, vol. 55(2), pages 358-376, January.
    11. Kim, Nayeon & Montreuil, Benoit & Klibi, Walid & Kholgade, Nitish, 2021. "Hyperconnected urban fulfillment and delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).

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