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Solving a vehicle-routing problem arising in soft-drink distribution

Author

Listed:
  • J Privé

    (Network Organisation Technology Research Center (CENTOR), Université Laval)

  • J Renaud

    (Network Organisation Technology Research Center (CENTOR), Université Laval)

  • F Boctor

    (Network Organisation Technology Research Center (CENTOR), Université Laval)

  • G Laporte

    (Canada Research Chair in Distribution Management, HEC Montréal, Montréal)

Abstract

The problem studied in this article arises from the distribution of soft drinks and collection of recyclable containers in a Quebec-based company. It can be modelled as a variant of the vehicle routing problem with a heterogeneous vehicle fleet, time windows, capacity and volume constraints, and an objective function combining routing costs and the revenue resulting from the sale of recyclable material. Three construction heuristics and an improvement procedure are developed for the problem. Comparative tests are performed on a real-life instance and on 10 randomly generated instances.

Suggested Citation

  • J Privé & J Renaud & F Boctor & G Laporte, 2006. "Solving a vehicle-routing problem arising in soft-drink distribution," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(9), pages 1045-1052, September.
    • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:9:d:10.1057_palgrave.jors.2602087
    DOI: 10.1057/palgrave.jors.2602087
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    References listed on IDEAS

    as
    1. Tarantilis, C. D. & Kiranoudis, C. T. & Vassiliadis, V. S., 2004. "A threshold accepting metaheuristic for the heterogeneous fixed fleet vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 152(1), pages 148-158, January.
    2. Bruce L. Golden & Edward A. Wasil, 1987. "OR Practice—Computerized Vehicle Routing in the Soft Drink Industry," Operations Research, INFORMS, vol. 35(1), pages 6-17, February.
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    Citations

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    Cited by:

    1. Hoff, Arild & Gribkovskaia, Irina & Laporte, Gilbert & Løkketangen, Arne, 2009. "Lasso solution strategies for the vehicle routing problem with pickups and deliveries," European Journal of Operational Research, Elsevier, vol. 192(3), pages 755-766, February.
    2. Zachariadis, Emmanouil E. & Tarantilis, Christos D. & Kiranoudis, Chris T., 2010. "An adaptive memory methodology for the vehicle routing problem with simultaneous pick-ups and deliveries," European Journal of Operational Research, Elsevier, vol. 202(2), pages 401-411, April.
    3. Santos, Maria João & Jorge, Diana & Ramos, Tânia & Barbosa-Póvoa, Ana, 2023. "Green reverse logistics: Exploring the vehicle routing problem with deliveries and pickups," Omega, Elsevier, vol. 118(C).
    4. Tanksale, Ajinkya N. & Das, Debabrata & Verma, Priyanka & Tiwari, Manoj Kumar, 2021. "Unpacking the role of primary packaging material in designing green supply chains: An integrated approach," International Journal of Production Economics, Elsevier, vol. 236(C).
    5. Ketzenberg, Michael E. & Metters, Richard D., 2020. "Adapting operations to new information technology: A failed “internet of things” application," Omega, Elsevier, vol. 92(C).
    6. Margaretha Gansterer & Murat Küçüktepe & Richard F. Hartl, 2017. "The multi-vehicle profitable pickup and delivery problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 303-319, January.
    7. Santos, Maria João & Curcio, Eduardo & Mulati, Mauro Henrique & Amorim, Pedro & Miyazawa, Flávio Keidi, 2020. "A robust optimization approach for the vehicle routing problem with selective backhauls," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    8. Gutiérrez-Jarpa, Gabriel & Desaulniers, Guy & Laporte, Gilbert & Marianov, Vladimir, 2010. "A branch-and-price algorithm for the Vehicle Routing Problem with Deliveries, Selective Pickups and Time Windows," European Journal of Operational Research, Elsevier, vol. 206(2), pages 341-349, October.

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