IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v54y2016i2p509-525.html
   My bibliography  Save this article

Particle swarm optimization for the multi-period cross-docking distribution problem with time windows

Author

Listed:
  • Vincent F. Yu
  • Parida Jewpanya
  • Voratas Kachitvichyanukul

Abstract

Cross-docking has emerged as a new technique in supply chain management to replace the warehouse concept in the retail industry. This paper proposes a multi-period cross-docking distribution problem that consists of manufacturers, cross-docks and customers. This model is formulated for cases that consider multiple products, consolidation of customer orders and time windows that are available in multiple periods. The objective function is to minimise the total cost, which includes transportation cost, inventory cost and penalty cost. The penalty cost arises when demand remains in each period that cannot be satisfied. To deal with the complexity of the problem, an algorithm is developed based on particle swarm optimisation (PSO) with multiple social learning terms, GLNPSO, with two solution representations. The solution representations are a one-period solution representation (OP-SR) and a multi-period solution representation (MP-SR). The GLNPSO-based algorithm performs well in solving this problem. Moreover, both representations are proven effective when comparing the solution quality and computational time with those results obtained from CPLEX. In terms of quality, the MP-SR solution is better than the OP-SR solution for both stable and fluctuating demand instances. However, MP-SR requires more computational effort than OP-SR.

Suggested Citation

  • Vincent F. Yu & Parida Jewpanya & Voratas Kachitvichyanukul, 2016. "Particle swarm optimization for the multi-period cross-docking distribution problem with time windows," International Journal of Production Research, Taylor & Francis Journals, vol. 54(2), pages 509-525, January.
  • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:509-525
    DOI: 10.1080/00207543.2015.1037933
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2015.1037933
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2015.1037933?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Miao, Zhaowei & Lim, Andrew & Ma, Hong, 2009. "Truck dock assignment problem with operational time constraint within crossdocks," European Journal of Operational Research, Elsevier, vol. 192(1), pages 105-115, January.
    2. Y Li & A Lim & B Rodrigues, 2004. "Crossdocking—JIT scheduling with time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1342-1351, December.
    3. Van Belle, Jan & Valckenaers, Paul & Cattrysse, Dirk, 2012. "Cross-docking: State of the art," Omega, Elsevier, vol. 40(6), pages 827-846.
    4. Ma, Hong & Miao, Zhaowei & Lim, Andrew & Rodrigues, Brian, 2011. "Crossdocking distribution networks with setup cost and time window constraint," Omega, Elsevier, vol. 39(1), pages 64-72, January.
    5. Tang, Shao-Long & Yan, Hong, 2010. "Pre-distribution vs. post-distribution for cross-docking with transshipments," Omega, Elsevier, vol. 38(3-4), pages 192-202, June.
    6. Boysen, Nils & Fliedner, Malte, 2010. "Cross dock scheduling: Classification, literature review and research agenda," Omega, Elsevier, vol. 38(6), pages 413-422, December.
    7. John J. Bartholdi & Kevin R. Gue, 2000. "Reducing Labor Costs in an LTL Crossdocking Terminal," Operations Research, INFORMS, vol. 48(6), pages 823-832, December.
    8. M Wen & J Larsen & J Clausen & J-F Cordeau & G Laporte, 2009. "Vehicle routing with cross-docking," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1708-1718, December.
    9. John J. Bartholdi & Kevin R. Gue, 2004. "The Best Shape for a Crossdock," Transportation Science, INFORMS, vol. 38(2), pages 235-244, May.
    10. Pisut Pongchairerks & Voratas Kachitvichyanukul, 2009. "Particle Swarm Optimization algorithm with multiple social learning structures," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 6(2), pages 176-194.
    11. Yan, Hong & Tang, Shao-long, 2009. "Pre-distribution and post-distribution cross-docking operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(6), pages 843-859, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Saeid Nasrollahi & Hasan Hosseini-Nasab & Mohamad Bagher Fakhrzad & Mahboobeh Honarvar, 2022. "A developed nonlinear model for the location-allocation and transportation problems in a cross-docking distribution network," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 32(1), pages 127-148.
    2. Yi Zhang & Guowei Hua & T. C. E. Cheng & Juliang Zhang, 2020. "Cold chain distribution: How to deal with node and arc time windows?," Annals of Operations Research, Springer, vol. 291(1), pages 1127-1151, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Van Belle, Jan & Valckenaers, Paul & Cattrysse, Dirk, 2012. "Cross-docking: State of the art," Omega, Elsevier, vol. 40(6), pages 827-846.
    2. 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.
    3. 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.
    4. Ladier, Anne-Laure & Alpan, Gülgün, 2016. "Cross-docking operations: Current research versus industry practice," Omega, Elsevier, vol. 62(C), pages 145-162.
    5. Hans Corsten & Ferdinand Becker & Hagen Salewski, 2020. "Integrating truck and workforce scheduling in a cross-dock: analysis of different workforce coordination policies," Journal of Business Economics, Springer, vol. 90(2), pages 207-237, March.
    6. Gelareh, Shahin & Glover, Fred & Guemri, Oualid & Hanafi, Saïd & Nduwayo, Placide & Todosijević, Raca, 2020. "A comparative study of formulations for a cross-dock door assignment problem," Omega, Elsevier, vol. 91(C).
    7. 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.
    8. Nils Boysen & Stefan Fedtke & Felix Weidinger, 2017. "Truck Scheduling in the Postal Service Industry," Transportation Science, INFORMS, vol. 51(2), pages 723-736, May.
    9. 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.
    10. Konur, Dinçer & Golias, Mihalis M., 2013. "Cost-stable truck scheduling at a cross-dock facility with unknown truck arrivals: A meta-heuristic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 71-91.
    11. H. Khorshidian & M. Akbarpour Shirazi & S. M. T. Fatemi Ghomi, 2019. "An intelligent truck scheduling and transportation planning optimization model for product portfolio in a cross-dock," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 163-184, January.
    12. Hermel, Dror & Hasheminia, Hamed & Adler, Nicole & Fry, Michael J., 2016. "A solution framework for the multi-mode resource-constrained cross-dock scheduling problem," Omega, Elsevier, vol. 59(PB), pages 157-170.
    13. 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.
    14. İlker Küçükoğlu & Nursel Öztürk, 2017. "Two-stage optimisation method for material flow and allocation management in cross-docking networks," International Journal of Production Research, Taylor & Francis Journals, vol. 55(2), pages 410-429, January.
    15. Dulebenets, Maxim A., 2019. "A Delayed Start Parallel Evolutionary Algorithm for just-in-time truck scheduling at a cross-docking facility," International Journal of Production Economics, Elsevier, vol. 212(C), pages 236-258.
    16. Fonseca, Gabriela B. & Nogueira, Thiago H. & Ravetti, Martín Gómez, 2019. "A hybrid Lagrangian metaheuristic for the cross-docking flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 275(1), pages 139-154.
    17. Anne-Laure Ladier & Gülgün Alpan, 2018. "Crossdock truck scheduling with time windows: earliness, tardiness and storage policies," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 569-583, March.
    18. G. Guastaroba & M. G. Speranza & D. Vigo, 2016. "Intermediate Facilities in Freight Transportation Planning: A Survey," Transportation Science, INFORMS, vol. 50(3), pages 763-789, August.
    19. 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.
    20. Wolff, Pascal & Emde, Simon & Pfohl, Hans-Christian, 2021. "Internal resource requirements: The better performance metric for truck scheduling?," Omega, Elsevier, vol. 103(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:509-525. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.