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The Vehicle Routing Problem with Divisible Deliveries and Pickups

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  • Gábor Nagy

    (Centre for Logistics and Heuristic Optimisation, Kent Business School, University of Kent, Canterbury CT2 7PE, United Kingdom)

  • Niaz A. Wassan

    (Centre for Logistics and Heuristic Optimisation, Kent Business School, University of Kent, Canterbury CT2 7PE, United Kingdom)

  • M. Grazia Speranza

    (Dipartimento Metodi Quantitativi, Università degli Studi di Brescia, 25122 Brescia, Italy)

  • Claudia Archetti

    (Dipartimento Metodi Quantitativi, Università degli Studi di Brescia, 25122 Brescia, Italy)

Abstract

The vehicle routing problem with divisible deliveries and pickups is a new and interesting model within reverse logistics. Each customer may have a pickup and delivery demand that have to be served with capacitated vehicles. The pickup and the delivery quantities may be served, if beneficial, in two separate visits. The model is placed in the context of other delivery and pickup problems and formulated as a mixed-integer linear programming problem. In this paper, we study the savings that can be achieved by allowing the pickup and delivery quantities to be served separately with respect to the case where the quantities have to be served simultaneously. Both exact and heuristic results are analysed in depth for a better understanding of the problem structure and an average estimation of the savings due to the possibility of serving pickup and delivery quantities separately.

Suggested Citation

  • Gábor Nagy & Niaz A. Wassan & M. Grazia Speranza & Claudia Archetti, 2015. "The Vehicle Routing Problem with Divisible Deliveries and Pickups," Transportation Science, INFORMS, vol. 49(2), pages 271-294, May.
    • Handle: RePEc:inm:ortrsc:v:49:y:2015:i:2:p:271-294
    DOI: 10.1287/trsc.2013.0501
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    References listed on IDEAS

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    10. Kidd, Martin P. & Darvish, Maryam & Coelho, Leandro C. & Gendron, Bernard, 2024. "A relax-and-restrict matheuristic for supply chain network design with facility location and customer due date flexibility," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    11. Heimfarth, Andreas & Ostermeier, Manuel & Hübner, Alexander, 2022. "A mixed truck and robot delivery approach for the daily supply of customers," European Journal of Operational Research, Elsevier, vol. 303(1), pages 401-421.
    12. Weikang Fang & Zailin Guan & Peiyue Su & Dan Luo & Linshan Ding & Lei Yue, 2022. "Multi-Objective Material Logistics Planning with Discrete Split Deliveries Using a Hybrid NSGA-II Algorithm," Mathematics, MDPI, vol. 10(16), pages 1-30, August.
    13. Allahviranloo, Mahdieh & Baghestani, Amirhossein, 2019. "A dynamic crowdshipping model and daily travel behavior," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 175-190.
    14. Oyama, Yuki & Fukuda, Daisuke & Imura, Naoto & Nishinari, Katsuhiro, 2024. "Do people really want fast and precisely scheduled delivery? E-commerce customers' valuations of home delivery timing," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    15. 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).
    16. Zhu, Lin & Sheu, Jiuh-Biing, 2018. "Failure-specific cooperative recourse strategy for simultaneous pickup and delivery problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 271(3), pages 896-912.
    17. Zhen, Lu & Baldacci, Roberto & Tan, Zheyi & Wang, Shuaian & Lyu, Junyan, 2022. "Scheduling heterogeneous delivery tasks on a mixed logistics platform," European Journal of Operational Research, Elsevier, vol. 298(2), pages 680-698.

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