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Physical Internet, conventional and hybrid logistic systems: a routing optimisation-based comparison using the Eastern Canada road network case study

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  • Mehran Fazili
  • Uday Venkatadri
  • Pemberton Cyrus
  • Mahdi Tajbakhsh

Abstract

The Physical Internet (PI) logistics system is an innovative logistics concept that has been gathering a lot of attention lately. This system consists of open, modular and shared containers and transit hubs to move goods globally. The purpose of this paper is to compare the performance of PI with regard to the conventional (CO) logistics system in order to quantify the advantages and disadvantages of PI from a truck and driver routing perspective with an explicit constraint on maximum return time for drivers. The comparison presented in this work is carried out through Monte-Carlo simulation within a sequential three-phase optimisation framework. Based on our analysis, PI reduces driving distance (and time), GHG (greenhouse gas) emissions and the social cost of truck driving. On the other hand, it increases the number of container transfers within the PI logistics centres. This insight is a contribution of the paper and reinforces the current literature on PI. The other main contribution of the paper is a validation of the claim that the number of drivers who can go back home at the end of a work day remains consistently high in PI, regardless of the traffic level.

Suggested Citation

  • Mehran Fazili & Uday Venkatadri & Pemberton Cyrus & Mahdi Tajbakhsh, 2017. "Physical Internet, conventional and hybrid logistic systems: a routing optimisation-based comparison using the Eastern Canada road network case study," International Journal of Production Research, Taylor & Francis Journals, vol. 55(9), pages 2703-2730, May.
  • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:9:p:2703-2730
    DOI: 10.1080/00207543.2017.1285075
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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. Shoufeng Ji & Pengyun Zhao & Tingting Ji, 2023. "A Hybrid Optimization Method for Sustainable and Flexible Design of Supply–Production–Distribution Network in the Physical Internet," Sustainability, MDPI, vol. 15(7), pages 1-34, April.
    3. Patricio Gallardo & Rua Murray & Susan Krumdieck, 2021. "A Sequential Optimization-Simulation Approach for Planning the Transition to the Low Carbon Freight System with Case Study in the North Island of New Zealand," Energies, MDPI, vol. 14(11), pages 1-24, June.
    4. Arnau, Quim & Barrena, Eva & Panadero, Javier & de la Torre, Rocio & Juan, Angel A., 2022. "A biased-randomized discrete-event heuristic for coordinated multi-vehicle container transport across interconnected networks," European Journal of Operational Research, Elsevier, vol. 302(1), pages 348-362.
    5. Orenstein, Ido & Raviv, Tal, 2022. "Parcel delivery using the hyperconnected service network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    6. Chih-Hung Hsu & Xu He & Ting-Yi Zhang & An-Yuan Chang & Wan-Ling Liu & Zhi-Qiang Lin, 2022. "Enhancing Supply Chain Agility with Industry 4.0 Enablers to Mitigate Ripple Effects Based on Integrated QFD-MCDM: An Empirical Study of New Energy Materials Manufacturers," Mathematics, MDPI, vol. 10(10), pages 1-35, May.
    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. Lin, Meiyan & Lin, Shaodan & Ma, Lijun & Zhang, Lianmin, 2022. "The value of the Physical Internet on the meals-on-wheels delivery system," International Journal of Production Economics, Elsevier, vol. 248(C).

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