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A Biased-Randomised Large Neighbourhood Search for the two-dimensional Vehicle Routing Problem with Backhauls

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  • Dominguez, Oscar
  • Guimarans, Daniel
  • Juan, Angel A.
  • de la Nuez, Ignacio

Abstract

The two-dimensional loading vehicle routing problem with clustered backhauls (2L-VRPB) is a realistic extension of the classical vehicle routing problem where both delivery and pickup demands are composed of non-stackable items. Despite the fact that the 2L-VRPB can be frequently found in real-life transportation activities, it has not been analysed so far in the literature. This paper presents a hybrid algorithm that integrates biased-randomised versions of vehicle routing and packing heuristics within a Large Neighbourhood Search metaheuristic framework. The use of biased randomisation techniques allows to better guide the local search process. The proposed approach for solving the 2L-VRPB is tested on an extensive set of instances, which have been adapted from existing benchmarks for the two-dimensional loading vehicle routing problem (2L-VRP). Additionally, when no backhauls are considered our algorithm is able to find new best solutions for several 2L-VRP benchmark instances with sequential oriented loading, both with and without items rotation.

Suggested Citation

  • Dominguez, Oscar & Guimarans, Daniel & Juan, Angel A. & de la Nuez, Ignacio, 2016. "A Biased-Randomised Large Neighbourhood Search for the two-dimensional Vehicle Routing Problem with Backhauls," European Journal of Operational Research, Elsevier, vol. 255(2), pages 442-462.
    • Handle: RePEc:eee:ejores:v:255:y:2016:i:2:p:442-462
    DOI: 10.1016/j.ejor.2016.05.002
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    Cited by:

    1. 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.
    2. Zheng Zhang & Bin Ji & Samson S. Yu, 2023. "An Adaptive Tabu Search Algorithm for Solving the Two-Dimensional Loading Constrained Vehicle Routing Problem with Stochastic Customers," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    3. Zhang, Xiangyi & Chen, Lu & Gendreau, Michel & Langevin, André, 2022. "A branch-and-cut algorithm for the vehicle routing problem with two-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 302(1), pages 259-269.
    4. Marques, Alexandra & Soares, Ricardo & Santos, Maria João & Amorim, Pedro, 2020. "Integrated planning of inbound and outbound logistics with a Rich Vehicle Routing Problem with backhauls," Omega, Elsevier, vol. 92(C).
    5. Julio C. Londoño & Rafael D. Tordecilla & Leandro do C. Martins & Angel A. Juan, 2021. "A biased-randomized iterated local search for the vehicle routing problem with optional backhauls," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 387-416, July.
    6. Carlos A. Vega-Mejía & Jairo R. Montoya-Torres & Sardar M. N. Islam, 2019. "Consideration of triple bottom line objectives for sustainability in the optimization of vehicle routing and loading operations: a systematic literature review," Annals of Operations Research, Springer, vol. 273(1), pages 311-375, February.
    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).

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