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A metaheuristic based on a pool of routes for the vehicle routing problem with multiple trips and time windows

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  • Z Wang

    (Dalian University of Technology, Liaoning, China)

  • W Liang

    (Dalian University of Technology, Liaoning, China)

  • X Hu

    (Dalian University of Technology, Liaoning, China)

Abstract

This paper studies the vehicle routing problem with multiple trips and time windows, in which vehicles are allowed to perform multiple trips during a scheduling period and each customer must be served within a given time interval. The problem is of particular importance for planning fleets of hired vehicles in common practices, such as e-grocery distributions, but this problem has received little attention in the literature. As a result of the multi-layered structure characteristic of the problem solution, we propose a pool-based metaheuristic in which various routes are first constructed to fill a pool, following which some of the routes are selected and combined to form vehicle working schedules. Finally, we conduct a series of experiments over a set of benchmark instances to evaluate and demonstrate the effectiveness of the proposed metaheuristic.

Suggested Citation

  • Z Wang & W Liang & X Hu, 2014. "A metaheuristic based on a pool of routes for the vehicle routing problem with multiple trips and time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(1), pages 37-48, January.
    • Handle: RePEc:pal:jorsoc:v:65:y:2014:i:1:p:37-48
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    Citations

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    Cited by:

    1. Diego Cattaruzza & Nabil Absi & Dominique Feillet, 2018. "Vehicle routing problems with multiple trips," Annals of Operations Research, Springer, vol. 271(1), pages 127-159, December.
    2. Véronique François & Yasemin Arda & Yves Crama, 2019. "Adaptive Large Neighborhood Search for Multitrip Vehicle Routing with Time Windows," Transportation Science, INFORMS, vol. 53(6), pages 1706-1730, November.
    3. Sandra Huber & Jean-François Cordeau & Martin Josef Geiger, 2020. "A matheuristic for the swap body vehicle routing problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(1), pages 111-160, March.
    4. Wang, Zheng, 2018. "Delivering meals for multiple suppliers: Exclusive or sharing logistics service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 496-512.
    5. Subrat Sarangi & Sudipta Sarangi & Nasim S. Sabounchi, 2023. "How managerial perspectives affect the optimal fleet size and mix model: a multi-objective approach," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 1-23, March.
    6. Diego Cattaruzza & Nabil Absi & Dominique Feillet, 2016. "Vehicle routing problems with multiple trips," 4OR, Springer, vol. 14(3), pages 223-259, September.
    7. Cheng, Chun & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2020. "Drone routing with energy function: Formulation and exact algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 364-387.
    8. Mar Vazquez-Noguerol & Jose Comesaña-Benavides & Raul Poler & J. Carlos Prado-Prado, 2022. "An optimisation approach for the e-grocery order picking and delivery problem," 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. 30(3), pages 961-990, September.

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