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An integrated model for the production-inventory-distribution problem in the Physical Internet

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  • Shou-feng Ji
  • Xiao-shuai Peng
  • Rong-juan Luo

Abstract

In contrast to traditional supply chain networks, Physical Internet (PI) is an interconnected open global logistics network based on open PI hubs and standard PI-containers that has the potential to achieve ground-breaking improvements in integrated production-inventory-distribution management. In this paper, to quantify the advantages of PI from a cost performance perspective, we propose a mixed-integer linear programming (MILP) formulation for addressing the problem that combines an integrated production-inventory-distribution decision with PI, which has been addressed separately in the existing literature. The results of computational experiments show that while achieving a comparable or better service level, PI can achieve significant cost savings compared to a traditional supply chain network with a dynamic configuration and a hybrid configuration. Moreover, we investigate the impact of several problem parameter changes on the total costs under each network setting, and managerial insights are derived.

Suggested Citation

  • Shou-feng Ji & Xiao-shuai Peng & Rong-juan Luo, 2019. "An integrated model for the production-inventory-distribution problem in the Physical Internet," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1000-1017, February.
  • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:4:p:1000-1017
    DOI: 10.1080/00207543.2018.1497818
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    Citations

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    Cited by:

    1. Hisatoshi Naganawa & Enna Hirata & Nailah Firdausiyah & Russell G. Thompson, 2024. "Logistics Hub and Route Optimization in the Physical Internet Paradigm," Logistics, MDPI, vol. 8(2), pages 1-18, April.
    2. 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).
    3. Maheshwari, Pratik & Kamble, Sachin & Belhadi, Amine & Venkatesh, Mani & Abedin, Mohammad Zoynul, 2023. "Digital twin-driven real-time planning, monitoring, and controlling in food supply chains," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    4. 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).
    5. Li, Ming & Shao, Saijun & Li, Yang & Zhang, Hua & Zhang, Nianwu & He, Yandong, 2022. "A Physical Internet (PI) based inland container transportation problem with selective non-containerized shipping requests," International Journal of Production Economics, Elsevier, vol. 245(C).

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