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Metaheuristics applied to mixed and simultaneous extensions of vehicle routing problems with backhauls

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  • J Crispim

    (University of Minho)

  • J Brandão

    (University of Minho)

Abstract

Metaheuristics are a class of approximate methods designed to solve hard combinatorial optimization problems arising within various different areas. The importance of metaheuristics results from their ability to continue the search beyond a local optimum so that near-optimal or optimal solutions are efficiently found. In order to solve the backhauling problem associated with mixed and simultaneous delivery and pick-ups, this paper presents a hybrid algorithm which is comprised of the two metaheuristics of tabu search and variable neighbourhood descent. The primary challenge associated with backhauling consists of creating routes in which vehicles are not only required to deliver goods, but also to perform pick-ups at customer locations. The problems associated with these two categories of problems, however, have received little attention in the literature to date. A set of examples taken from the literature with Euclidean cost matrices are presented. Finally, some numerical results are illustrated to show the effectiveness of the proposed approach.

Suggested Citation

  • J Crispim & J Brandão, 2005. "Metaheuristics applied to mixed and simultaneous extensions of vehicle routing problems with backhauls," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(11), pages 1296-1302, November.
    • Handle: RePEc:pal:jorsoc:v:56:y:2005:i:11:d:10.1057_palgrave.jors.2601935
    DOI: 10.1057/palgrave.jors.2601935
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Niaz A. Wassan & A. Hameed Wassan & Gábor Nagy, 2008. "A reactive tabu search algorithm for the vehicle routing problem with simultaneous pickups and deliveries," Journal of Combinatorial Optimization, Springer, vol. 15(4), pages 368-386, May.
    2. Henriette Koch & Andreas Bortfeldt & Gerhard Wäscher, 2018. "A hybrid algorithm for the vehicle routing problem with backhauls, time windows and three-dimensional loading constraints," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 1029-1075, October.
    3. Yang, Senyan & Ning, Lianju & Shang, Pan & (Carol) Tong, Lu, 2020. "Augmented Lagrangian relaxation approach for logistics vehicle routing problem with mixed backhauls and time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    4. Maria João Santos & Pedro Amorim & Alexandra Marques & Ana Carvalho & Ana Póvoa, 2020. "The vehicle routing problem with backhauls towards a sustainability perspective: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 358-401, July.
    5. Fagui Liu & Lvshengbiao Wang & Mengke Gui & Yang Zhang & Yulin Lan & Chengqi Lai & Boyuan Zhu, 2023. "A hybrid heuristic algorithm for urban distribution with simultaneous pickup-delivery and time window," Journal of Heuristics, Springer, vol. 29(2), pages 269-311, June.
    6. Mehmet Fatih Yuce & Erhan Musaoglu & Ali Gunes, 2016. "Enhancing heuristic bubble algorithm with simulated annealing," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1220662-122, December.
    7. Y Gajpal & P Abad, 2010. "Saving-based algorithms for vehicle routing problem with simultaneous pickup and delivery," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(10), pages 1498-1509, October.
    8. Henriette Koch & Maximilian Schlögell & Andreas Bortfeldt, 2020. "A hybrid algorithm for the vehicle routing problem with three-dimensional loading constraints and mixed backhauls," Journal of Scheduling, Springer, vol. 23(1), pages 71-93, February.

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