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Optimizing the Door Assignment in LTL-Terminals

Author

Listed:
  • Annette Chmielewski

    (Transportation Systems and Logistics, TU Dortmund University, 44221 Dortmund, Germany)

  • Boris Naujoks

    (Login GmbH, 58332 Schwelm, Germany)

  • Michael Janas

    (Algorithm Engineering, TU Dortmund University, 44221 Dortmund, Germany)

  • Uwe Clausen

    (Transportation Systems and Logistics, TU Dortmund University, 44221 Dortmund, Germany)

Abstract

In less-than-truckload (LTL) terminals, arriving trucks have to be assigned to inbound doors and to suitable time slots for unloading. Simultaneously, waiting trucks have to be allocated to outbound doors. During a couple of hours, shipments from all incoming trucks are unloaded, sorted according to their relation, transported to the right outbound door, and loaded on the outgoing truck. (The term “relation” is an equivalent for destination; it originates from the German logistics vocabulary that uses the term to specify a certain transport offered between a source and a sink.) The first and the most important optimization aim is to minimize the total distance when transshipping units, because this leads to reduction in operational costs, which are usually very high. The second, and minor, aim is to minimize the waiting time for each truck. Usually the operator of an LTL transshipment building works with subcontractors when collecting and delivering goods. Therefore, no penalties have to be paid by the operators in case waiting times are too long. The logistical optimization task is modeled as a time-discrete, multicommodity flow problem with side constraints. Based on the applicable model, a decomposition approach and a modified column-generation approach are developed. In parallel, an evolutionary algorithm (EA) was implemented to tackle the problem at hand. Both algorithms---from the field of discrete mathematics, as well as from the field of computational intelligence---are applied to 10 test scenarios. A comparison of the solution process, as well as a comparison of the solution quality, concludes the work.

Suggested Citation

  • Annette Chmielewski & Boris Naujoks & Michael Janas & Uwe Clausen, 2009. "Optimizing the Door Assignment in LTL-Terminals," Transportation Science, INFORMS, vol. 43(2), pages 198-210, May.
  • Handle: RePEc:inm:ortrsc:v:43:y:2009:i:2:p:198-210
    DOI: 10.1287/trsc.1090.0271
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    References listed on IDEAS

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    1. Huisman, D. & Jans, R.F. & Peeters, M. & Wagelmans, A.P.M., 2003. "Combining Column Generation and Lagrangian Relaxation," ERIM Report Series Research in Management ERS-2003-092-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Kevin R. Gue, 1999. "The Effects of Trailer Scheduling on the Layout of Freight Terminals," Transportation Science, INFORMS, vol. 33(4), pages 419-428, November.
    3. Dennis Huisman & Raf Jans & Marc Peeters & Albert P.M. Wagelmans, 2005. "Combining Column Generation and Lagrangian Relaxation," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 247-270, Springer.
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    Cited by:

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    4. 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.
    5. Maknoon, M.Y. & Soumis, F. & Baptiste, P., 2016. "Optimizing transshipment workloads in less-than-truckload cross-docks," International Journal of Production Economics, Elsevier, vol. 179(C), pages 90-100.
    6. Saeid Rezaei & Amirsaman Kheirkhah, 2018. "A comprehensive approach in designing a sustainable closed-loop supply chain network using cross-docking operations," Computational and Mathematical Organization Theory, Springer, vol. 24(1), pages 51-98, March.
    7. Castellucci, Pedro B. & Toledo, Franklina M.B. & Costa, Alysson M., 2019. "Output maximization container loading problem with time availability constraints," Operations Research Perspectives, Elsevier, vol. 6(C).
    8. Buijs, Paul & Vis, Iris F.A. & Carlo, Héctor J., 2014. "Synchronization in cross-docking networks: A research classification and framework," European Journal of Operational Research, Elsevier, vol. 239(3), pages 593-608.
    9. 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).
    10. Dirk Briskorn & Malte Fliedner & Martin Tschöke, 2021. "Vehicle Sequencing at Transshipment Terminals with Handover Relations," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 477-494, May.
    11. Maxim A. Dulebenets, 2018. "A Diploid Evolutionary Algorithm for Sustainable Truck Scheduling at a Cross-Docking Facility," Sustainability, MDPI, vol. 10(5), pages 1-23, April.
    12. Van Belle, Jan & Valckenaers, Paul & Cattrysse, Dirk, 2012. "Cross-docking: State of the art," Omega, Elsevier, vol. 40(6), pages 827-846.
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