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An improved formulation for the multi-depot open vehicle routing problem

Author

Listed:
  • Eduardo Lalla-Ruiz

    (University of La Laguna)

  • Christopher Expósito-Izquierdo

    (University of La Laguna)

  • Shervin Taheripour

    (University of Hamburg)

  • Stefan Voß

    (University of Hamburg
    Pontificia Universidad Católica de Valparaíso)

Abstract

The multi-depot open vehicle routing problem (MDOVRP) is a recent hard combinatorial optimization problem that belongs to the vehicle routing problem family. In the MDOVRP, the vehicles depart from several depots and once they have delivered the goods to the last customers in their routes they are not required to return to the depots. In this work, we propose a new mixed integer programming formulation for the MDOVRP by improving some constraints from the literature and proposing new ones. The computational experience carried out over problem instances from the literature indicates that our proposed model outperforms the existing one.

Suggested Citation

  • Eduardo Lalla-Ruiz & Christopher Expósito-Izquierdo & Shervin Taheripour & Stefan Voß, 2016. "An improved formulation for the multi-depot open vehicle routing problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(1), pages 175-187, January.
    • Handle: RePEc:spr:orspec:v:38:y:2016:i:1:d:10.1007_s00291-015-0408-9
    DOI: 10.1007/s00291-015-0408-9
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Alinaghian, Mahdi & Shokouhi, Nadia, 2018. "Multi-depot multi-compartment vehicle routing problem, solved by a hybrid adaptive large neighborhood search," Omega, Elsevier, vol. 76(C), pages 85-99.
    2. Leonard Heilig & Eduardo Lalla-Ruiz & Stefan Voß, 2017. "port-IO: an integrative mobile cloud platform for real-time inter-terminal truck routing optimization," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 504-534, December.
    3. Brandão, José, 2020. "A memory-based iterated local search algorithm for the multi-depot open vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 284(2), pages 559-571.
    4. 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.
    5. Darvish, Maryam & Archetti, Claudia & Coelho, Leandro C. & Speranza, M. Grazia, 2019. "Flexible two-echelon location routing problem," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1124-1136.
    6. Behrend, Moritz & Meisel, Frank & Fagerholt, Kjetil & Andersson, Henrik, 2021. "A multi-period analysis of the integrated item-sharing and crowdshipping problem," European Journal of Operational Research, Elsevier, vol. 292(2), pages 483-499.
    7. Afsaneh Amiri & Majid Salari, 2019. "Time-constrained maximal covering routing problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 415-468, June.
    8. Zhen, Lu & Tan, Zheyi & Wang, Shuaian & Yi, Wen & Lyu, Junyan, 2021. "Shared mobility oriented open vehicle routing with order radius decision," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 19-33.
    9. Efraín Ruiz y Ruiz & Irma García-Calvillo & Samuel Nucamendi-Guillén, 2022. "Open vehicle routing problem with split deliveries: mathematical formulations and a cutting-plane method," Operational Research, Springer, vol. 22(2), pages 1017-1037, April.

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