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A real-time vehicle-dispatching system for consolidating milk runs

Author

Listed:
  • Du, Timon
  • Wang, F.K.
  • Lu, Pu-Yun

Abstract

This study investigates the parameter settings of a real-time vehicle-dispatching system for consolidating milk runs. Seven modules are used to implement the real-time system and the parameters are determined by a comprehensive experimental design. The real-time vehicle-dispatching system will be demonstrated in different milk run scenarios. The results of the experiments suggest that the system should have an initial vehicle dispatching module and an inter-route improvement module. It is also recommended that the Best Fit algorithm for initial vehicle dispatch and the 2-Exchange algorithm for inter-route improvement are most suitable for the real-time system.

Suggested Citation

  • Du, Timon & Wang, F.K. & Lu, Pu-Yun, 2007. "A real-time vehicle-dispatching system for consolidating milk runs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(5), pages 565-577, September.
    • Handle: RePEc:eee:transe:v:43:y:2007:i:5:p:565-577
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    Citations

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    Cited by:

    1. François Fulconis & Gérard Roveillo & Gilles Paché, 2008. "Transport, poor relation or pillar of contemporary supply networks? [Le transport, parent pauvre ou pièce maîtresse des schémas d’approvisionnement contemporains ?]," Post-Print hal-02491721, HAL.
    2. Boysen, Nils & Emde, Simon & Hoeck, Michael & Kauderer, Markus, 2015. "Part logistics in the automotive industry: Decision problems, literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 242(1), pages 107-120.
    3. Timo Gschwind & Stefan Irnich & Christian Tilk & Simon Emde, 2020. "Branch-cut-and-price for scheduling deliveries with time windows in a direct shipping network," Journal of Scheduling, Springer, vol. 23(3), pages 363-377, June.
    4. Xuan Qiu & Jasmine Siu Lee Lam, 2018. "The Value of Sharing Inland Transportation Services in a Dry Port System," Transportation Science, INFORMS, vol. 52(4), pages 835-849, August.
    5. Timo Gschwind & Stefan Irnich & Simon Emde & Christian Tilk, 2018. "Branch-Cut-and-Price for the Scheduling Deliveries with Time Windows in a Direct Shipping Network," Working Papers 1805, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    6. Pillac, Victor & Gendreau, Michel & Guéret, Christelle & Medaglia, Andrés L., 2013. "A review of dynamic vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 225(1), pages 1-11.
    7. Zhaofang Mao & Dian Huang & Kan Fang & Chengbo Wang & Dandan Lu, 2020. "Milk-run routing problem with progress-lane in the collection of automobile parts," Annals of Operations Research, Springer, vol. 291(1), pages 657-684, August.
    8. Sara Martins & Pedro Amorim & Bernardo Almada-Lobo, 2018. "Delivery mode planning for distribution to brick-and-mortar retail stores: discussion and literature review," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 785-812, December.
    9. Qiu, Xuan & Huang, George Q., 2016. "Transportation service sharing and replenishment/delivery scheduling in Supply Hub in Industrial Park (SHIP)," International Journal of Production Economics, Elsevier, vol. 175(C), pages 109-120.
    10. Shi, Wen & Shang, Jennifer & Liu, Zhixue & Zuo, Xiaolu, 2014. "Optimal design of the auto parts supply chain for JIT operations: Sequential bifurcation factor screening and multi-response surface methodology," European Journal of Operational Research, Elsevier, vol. 236(2), pages 664-676.
    11. Ziqi Wang & Peihan Wen, 2020. "Optimization of a Low-Carbon Two-Echelon Heterogeneous-Fleet Vehicle Routing for Cold Chain Logistics under Mixed Time Window," Sustainability, MDPI, vol. 12(5), pages 1-22, March.

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