IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v217y2012i2p287-299.html

Optimally routing and scheduling tow trains for JIT-supply of mixed-model assembly lines

Author

Listed:
  • Emde, Simon
  • Boysen, Nils

Abstract

In recent years, more and more automobile producers adopted the supermarket-concept to enable a flexible and reliable Just-in-Time (JIT) part supply of their mixed-model assembly lines. Within this concept, a supermarket is a decentralized in-house logistics area where parts are intermediately stored and then loaded on small tow trains. These tow trains travel across the shop floor on specific routes to make frequent small-lot deliveries which are needed by the stations of the line. To enable a reliable part supply in line with the JIT-principle, the interdependent problems of routing, that is, partitioning stations to be supplied among tow trains, and scheduling, i.e., deciding on the start times of each tow train’s tours through its assigned stations, need to be solved. This paper introduces an exact solution procedure which solves both problems simultaneously in polynomial runtime. Additionally, management implications regarding the trade-off between number and capacity of tow trains and in-process inventory near the line are investigated within a comprehensive computational study.

Suggested Citation

  • Emde, Simon & Boysen, Nils, 2012. "Optimally routing and scheduling tow trains for JIT-supply of mixed-model assembly lines," European Journal of Operational Research, Elsevier, vol. 217(2), pages 287-299.
  • Handle: RePEc:eee:ejores:v:217:y:2012:i:2:p:287-299
    DOI: 10.1016/j.ejor.2011.09.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221711008162
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2011.09.013?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Boysen, Nils & Fliedner, Malte, 2010. "Cross dock scheduling: Classification, literature review and research agenda," Omega, Elsevier, vol. 38(6), pages 413-422, December.
    2. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    3. Gilbert Laporte, 2009. "Fifty Years of Vehicle Routing," Transportation Science, INFORMS, vol. 43(4), pages 408-416, November.
    4. Angelelli, Enrico & Grazia Speranza, Maria, 2002. "The periodic vehicle routing problem with intermediate facilities," European Journal of Operational Research, Elsevier, vol. 137(2), pages 233-247, March.
    5. Baita, Flavio & Ukovich, Walter & Pesenti, Raffaele & Favaretto, Daniela, 1998. "Dynamic routing-and-inventory problems: a review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(8), pages 585-598, November.
    6. Vishal Gaur & Marshall L. Fisher, 2004. "A Periodic Inventory Routing Problem at a Supermarket Chain," Operations Research, INFORMS, vol. 52(6), pages 813-822, December.
    Full references (including those not matched with items on IDEAS)

    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. Débora P. Ronconi & João L. V. Manguino, 2025. "GRASP and VNS approaches for a vehicle routing problem with step cost functions," Annals of Operations Research, Springer, vol. 350(1), pages 37-62, July.
    2. Nicolas Rincon-Garcia & Ben J. Waterson & Tom J. Cherrett, 2018. "Requirements from vehicle routing software: perspectives from literature, developers and the freight industry," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 117-138, January.
    3. Schmid, Verena & Doerner, Karl F. & Laporte, Gilbert, 2013. "Rich routing problems arising in supply chain management," European Journal of Operational Research, Elsevier, vol. 224(3), pages 435-448.
    4. Truden, Christian & Hewitt, Mike, 2026. "Multi-objective, multi-attribute fleet sizing in a dynamic and stochastic environment: A data-driven approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 207(C).
    5. A. Mor & M. G. Speranza, 2020. "Vehicle routing problems over time: a survey," 4OR, Springer, vol. 18(2), pages 129-149, June.
    6. Coelho, V.N. & Grasas, A. & Ramalhinho, H. & Coelho, I.M. & Souza, M.J.F. & Cruz, R.C., 2016. "An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints," European Journal of Operational Research, Elsevier, vol. 250(2), pages 367-376.
    7. Jeffrey W. Ohlmann & Michael J. Fry & Barrett W. Thomas, 2008. "Route Design for Lean Production Systems," Transportation Science, INFORMS, vol. 42(3), pages 352-370, August.
    8. Zhenzhen Zhang & Yu Zhang & Roberto Baldacci, 2024. "Generalized Riskiness Index in Vehicle Routing Under Uncertain Travel Times: Formulations, Properties, and Exact Solution Framework," Transportation Science, INFORMS, vol. 58(4), pages 761-780, July.
    9. Zhiping Zuo & Yanhui Li & Jing Fu & Jianlin Wu, 2019. "Human Resource Scheduling Model and Algorithm with Time Windows and Multi-Skill Constraints," Mathematics, MDPI, vol. 7(7), pages 1-18, July.
    10. M. Angélica Salazar-Aguilar & Vincent Boyer & Romeo Sanchez Nigenda & Iris A. Martínez-Salazar, 2019. "The sales force sizing problem with multi-period workload assignments, and service time windows," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(1), pages 199-218, March.
    11. Liu, Yiming & Yu, Yang & Baldacci, Roberto & Tang, Jiafu & Sun, Wei, 2025. "Optimizing carbon emissions in green logistics for time-dependent routing," Transportation Research Part B: Methodological, Elsevier, vol. 192(C).
    12. Shubhechyya Ghosal & Wolfram Wiesemann, 2020. "The Distributionally Robust Chance-Constrained Vehicle Routing Problem," Operations Research, INFORMS, vol. 68(3), pages 716-732, May.
    13. Lin, Yen-Hung & Batta, Rajan & Rogerson, Peter A. & Blatt, Alan & Flanigan, Marie, 2011. "A logistics model for emergency supply of critical items in the aftermath of a disaster," Socio-Economic Planning Sciences, Elsevier, vol. 45(4), pages 132-145, December.
    14. Neves-Moreira, F. & Amorim, P. & Guimarães, L. & Almada-Lobo, B., 2016. "A long-haul freight transportation problem: Synchronizing resources to deliver requests passing through multiple transshipment locations," European Journal of Operational Research, Elsevier, vol. 248(2), pages 487-506.
    15. Gilbert Laporte, 2016. "Scheduling issues in vehicle routing," Annals of Operations Research, Springer, vol. 236(2), pages 463-474, January.
    16. Letchford, Adam N. & Salazar-González, Juan-José, 2019. "The Capacitated Vehicle Routing Problem: Stronger bounds in pseudo-polynomial time," European Journal of Operational Research, Elsevier, vol. 272(1), pages 24-31.
    17. Arpan Rijal & Marco Bijvank & René de Koster, 2023. "Dynamics between warehouse operations and vehicle routing," Production and Operations Management, Production and Operations Management Society, vol. 32(11), pages 3575-3593, November.
    18. Schyns, M., 2015. "An ant colony system for responsive dynamic vehicle routing," European Journal of Operational Research, Elsevier, vol. 245(3), pages 704-718.
    19. Salavati-Khoshghalb, Majid & Gendreau, Michel & Jabali, Ola & Rei, Walter, 2019. "An exact algorithm to solve the vehicle routing problem with stochastic demands under an optimal restocking policy," European Journal of Operational Research, Elsevier, vol. 273(1), pages 175-189.
    20. Yu, Junfang & Dong, Yuanyuan, 2013. "Maximizing profit for vehicle routing under time and weight constraints," International Journal of Production Economics, Elsevier, vol. 145(2), pages 573-583.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:eee:ejores:v:217:y:2012:i:2:p:287-299. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.