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Scheduling Trucks in a Cross-Dock with Mixed Service Mode Dock Doors

Author

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  • Peter Bodnar

    (CORAL, Department of Economics and Business, Aarhus University, 8000 Aarhus, Denmark)

  • René de Koster

    (Rotterdam School of Management, Erasmus University, 3000 DR Rotterdam, Netherlands)

  • Kaveh Azadeh

    (Rotterdam School of Management, Erasmus University, 3000 DR Rotterdam, Netherlands)

Abstract

The problem considered in this paper is how to schedule inbound and outbound trucks subject to time windows at a multidoor cross-dock. Dock doors can either be dedicated to inbound or outbound trucks or be capable of handling both truck types. In addition, loads are allowed to be temporarily buffered to bridge the time between load arrival and departure. We minimize operational costs consisting of the cost of handling loads in temporary storage, as well as the cost of tardiness caused by processing outbound trucks after their respective due times. A mathematical model is derived and an adaptive large neighborhood search heuristic is proposed to compute near-optimal solutions of real size instances. Computational experiments show that the proposed heuristic algorithm can obtain high-quality solutions within short computation times. We apply the model to cross-dock scheduling and design problems of four warehouses of a large retailer and show that substantially smaller cross-docks can be used by using dock-doors flexibly and properly scheduling the trucks.

Suggested Citation

  • Peter Bodnar & René de Koster & Kaveh Azadeh, 2017. "Scheduling Trucks in a Cross-Dock with Mixed Service Mode Dock Doors," Transportation Science, INFORMS, vol. 51(1), pages 112-131, February.
    • Handle: RePEc:inm:ortrsc:v:51:y:2017:i:1:p:112-131
    DOI: 10.1287/trsc.2015.0612
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    References listed on IDEAS

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    Cited by:

    1. Felix Weidinger & Nils Boysen & Dirk Briskorn, 2018. "Storage Assignment with Rack-Moving Mobile Robots in KIVA Warehouses," Service Science, INFORMS, vol. 52(6), pages 1479-1495, December.
    2. Li, Mingjie & Hao, Jin-Kao & Wu, Qinghua, 2024. "A flow based formulation and a reinforcement learning based strategic oscillation for cross-dock door assignment," European Journal of Operational Research, Elsevier, vol. 312(2), pages 473-492.
    3. Pan, Fei & Zhou, Wei & Fan, Tijun & Li, Shuxia & Zhang, Chong, 2021. "Deterioration rate variation risk for sustainable cross-docking service operations," International Journal of Production Economics, Elsevier, vol. 232(C).
    4. Tadumadze, Giorgi & Boysen, Nils & Emde, Simon & Weidinger, Felix, 2019. "Integrated truck and workforce scheduling to accelerate the unloading of trucks," European Journal of Operational Research, Elsevier, vol. 278(1), pages 343-362.
    5. Wolff, Pascal & Emde, Simon & Pfohl, Hans-Christian, 2021. "Internal resource requirements: The better performance metric for truck scheduling?," Omega, Elsevier, vol. 103(C).
    6. Arpan Rijal & Marco Bijvank & Asvin Goel & René de Koster, 2021. "Workforce Scheduling with Order-Picking Assignments in Distribution Facilities," Transportation Science, INFORMS, vol. 55(3), pages 725-746, May.
    7. Jamili, Negin & van den Berg, Pieter L. & de Koster, René, 2022. "Quantifying the impact of sharing resources in a collaborative warehouse," European Journal of Operational Research, Elsevier, vol. 302(2), pages 518-529.
    8. Xi, Xiang & Changchun, Liu & Yuan, Wang & Loo Hay, Lee, 2020. "Two-stage conflict robust optimization models for cross-dock truck scheduling problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    9. Feifeng Zheng & Yaxin Pang & Yinfeng Xu, 2022. "Heuristics for cross-docking scheduling of truck arrivals, truck departures and shop-floor operations," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1571-1601, July.
    10. Rijal, Arpan & Bijvank, Marco & de Koster, René, 2019. "Integrated scheduling and assignment of trucks at unit-load cross-dock terminals with mixed service mode dock doors," European Journal of Operational Research, Elsevier, vol. 278(3), pages 752-771.

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