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Reactive tabu adaptive memory programming search for the vehicle routing problem with backhauls

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  • N Wassan

    (University of Kent)

Abstract

A heuristic approach based on a hybrid operation of reactive tabu search (RTS) and adaptive memory programming (AMP) is proposed to solve the vehicle routing problem with backhauls (VRPB). The RTS is used with an escape mechanism which manipulates different neighbourhood schemes in a sophisticated way in order to get a continuously balanced intensification and diversification during the search process. The adaptive memory strategy takes the search back to the unexplored regions of the search space by maintaining a set of elite solutions and using them strategically with the RTS. The AMP feature brings an extra robustness to the search process that resulted in early convergence when tested on most of the VRPB instances. We compare our algorithm against the best methods in the literature and report new best solutions for several benchmark problems.

Suggested Citation

  • N Wassan, 2007. "Reactive tabu adaptive memory programming search for the vehicle routing problem with backhauls," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1630-1641, December.
    • Handle: RePEc:pal:jorsoc:v:58:y:2007:i:12:d:10.1057_palgrave.jors.2602313
    DOI: 10.1057/palgrave.jors.2602313
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    References listed on IDEAS

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    Cited by:

    1. Palhazi Cuervo, Daniel & Goos, Peter & Sörensen, Kenneth & Arráiz, Emely, 2014. "An iterated local search algorithm for the vehicle routing problem with backhauls," European Journal of Operational Research, Elsevier, vol. 237(2), pages 454-464.
    2. 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.
    3. Phuong Khanh Nguyen & Teodor Gabriel Crainic & Michel Toulouse, 2017. "Multi-trip pickup and delivery problem with time windows and synchronization," Annals of Operations Research, Springer, vol. 253(2), pages 899-934, June.
    4. 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.
    5. Queiroga, Eduardo & Frota, Yuri & Sadykov, Ruslan & Subramanian, Anand & Uchoa, Eduardo & Vidal, Thibaut, 2020. "On the exact solution of vehicle routing problems with backhauls," European Journal of Operational Research, Elsevier, vol. 287(1), pages 76-89.
    6. 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.
    7. 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.
    8. Merve Cengiz Toklu, 2023. "A fuzzy multi-criteria approach based on Clarke and Wright savings algorithm for vehicle routing problem in humanitarian aid distribution," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2241-2261, June.
    9. José Brandão, 2016. "A deterministic iterated local search algorithm for the vehicle routing problem with backhauls," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(2), pages 445-465, July.
    10. Salhi, Said & Wassan, Niaz & Hajarat, Mutaz, 2013. "The Fleet Size and Mix Vehicle Routing Problem with Backhauls: Formulation and Set Partitioning-based Heuristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 22-35.
    11. Bortfeldt, Andreas & Hahn, Thomas & Männel, Dirk & Mönch, Lars, 2015. "Hybrid algorithms for the vehicle routing problem with clustered backhauls and 3D loading constraints," European Journal of Operational Research, Elsevier, vol. 243(1), pages 82-96.

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