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Vehicle Routing with Shipment Consolidation

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  • Cortes, Juan David
  • Suzuki, Yoshinori

Abstract

The Vehicle Routing Problem with Split Deliveries (VRPSD) is a decision model that is increasingly used in practice to enhance the efficiency of last-mile distribution, an important task which all manufacturing, distribution, and retail firms must perform. In its current form, however, the VRPSD is missing an important cost saving opportunity by not allowing interactions among multiple vehicles that visit the same customer. In this paper, we introduce an extended version of the VRPSD, called the Vehicle Routing Problem with Shipment Consolidation (VRPC), a model that considers not only split deliveries, but also shipment exchanges (transfers) between different vehicles at certain customer locations (a process referred to as mid-route shipment consolidation). We conduct a series of numerical experiments, as well as a case study, to show that VRPC solutions match or outperform those of the VRPSD. Results indicate that up to 10 percent savings may be attained through the VRPC in lieu of the VRPSD, which implies that the efficiency of last-mile delivery may be improved by allowing mid-route shipment consolidation at select customer locations.

Suggested Citation

  • Cortes, Juan David & Suzuki, Yoshinori, 2020. "Vehicle Routing with Shipment Consolidation," International Journal of Production Economics, Elsevier, vol. 227(C).
    • Handle: RePEc:eee:proeco:v:227:y:2020:i:c:s0925527320300104
    DOI: 10.1016/j.ijpe.2020.107622
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    2. Peng, Xiaoshuai & Zhang, Lele & Thompson, Russell G. & Wang, Kangzhou, 2023. "A three-phase heuristic for last-mile delivery with spatial-temporal consolidation and delivery options," International Journal of Production Economics, Elsevier, vol. 266(C).
    3. Shejun Deng & Yingying Yuan & Yong Wang & Haizhong Wang & Charles Koll, 2020. "Collaborative multicenter logistics delivery network optimization with resource sharing," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-31, November.
    4. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    5. Amin Abbasi-Pooya & Michael T. Lash, 2024. "The third party logistics provider freight management problem: a framework and deep reinforcement learning approach," Annals of Operations Research, Springer, vol. 339(1), pages 965-1024, August.
    6. Radislav Vaisman & Ilya B. Gertsbakh, 2023. "Optimal balanced chain decomposition of partially ordered sets with applications to operating cost minimization in aircraft routing problems," Public Transport, Springer, vol. 15(1), pages 199-225, March.
    7. Lyu, Zefeng & Yu, Andrew Junfang, 2023. "The pickup and delivery problem with transshipments: Critical review of two existing models and a new formulation," European Journal of Operational Research, Elsevier, vol. 305(1), pages 260-270.

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