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A matheuristic for the truck and trailer routing problem

Author

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  • Villegas, Juan G.
  • Prins, Christian
  • Prodhon, Caroline
  • Medaglia, Andrés L.
  • Velasco, Nubia

Abstract

In the truck and trailer routing problems (TTRPs) a fleet of trucks and trailers serves a set of customers. Some customers with accessibility constraints must be served just by truck, while others can be served either by truck or by a complete vehicle (a truck pulling a trailer). We propose a simple, yet effective, two-phase matheuristic that uses the routes of the local optima of a hybrid GRASP×ILS as columns in a set-partitioning formulation of the TTRP. Using this matheuristic we solved both the classical TTRP with fixed fleet and the new variant with unlimited fleet. This matheuristic outperforms state-of-the-art methods both in terms of solution quality and computing time. While the best variant of the matheuristic found new best-known solutions for several test instances from the literature, the fastest variant of the matheuristic achieved results of comparable quality to those of all previous method from the literature with an average speed-up of at least 2.5.

Suggested Citation

  • Villegas, Juan G. & Prins, Christian & Prodhon, Caroline & Medaglia, Andrés L. & Velasco, Nubia, 2013. "A matheuristic for the truck and trailer routing problem," European Journal of Operational Research, Elsevier, vol. 230(2), pages 231-244.
  • Handle: RePEc:eee:ejores:v:230:y:2013:i:2:p:231-244
    DOI: 10.1016/j.ejor.2013.04.026
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    References listed on IDEAS

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    1. Mauricio G.C. Resende & Celso C. Ribeiro & Fred Glover & Rafael Martí, 2010. "Scatter Search and Path-Relinking: Fundamentals, Advances, and Applications," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 87-107, Springer.
    2. James P. Kelly & Jiefeng Xu, 1999. "A Set-Partitioning-Based Heuristic for the Vehicle Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 11(2), pages 161-172, May.
    3. Gerdessen, Johanna C., 1996. "Vehicle routing problem with trailers," European Journal of Operational Research, Elsevier, vol. 93(1), pages 135-147, August.
    4. Beasley, JE, 1983. "Route first--Cluster second methods for vehicle routing," Omega, Elsevier, vol. 11(4), pages 403-408.
    5. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms," Transportation Science, INFORMS, vol. 39(1), pages 104-118, February.
    6. M Caramia & F Guerriero, 2010. "A heuristic approach for the truck and trailer routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(7), pages 1168-1180, July.
    7. Pureza, Vitória & Morabito, Reinaldo & Reimann, Marc, 2012. "Vehicle routing with multiple deliverymen: Modeling and heuristic approaches for the VRPTW," European Journal of Operational Research, Elsevier, vol. 218(3), pages 636-647.
    8. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    9. Subramanian, Anand & Penna, Puca Huachi Vaz & Uchoa, Eduardo & Ochi, Luiz Satoru, 2012. "A hybrid algorithm for the Heterogeneous Fleet Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 221(2), pages 285-295.
    10. Massimiliano Caramia & Francesca Guerriero, 2010. "A Milk Collection Problem with Incompatibility Constraints," Interfaces, INFORMS, vol. 40(2), pages 130-143, April.
    11. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    12. Tan, K.C. & Chew, Y.H. & Lee, L.H., 2006. "A hybrid multi-objective evolutionary algorithm for solving truck and trailer vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 172(3), pages 855-885, August.
    13. Mauricio G.C. Resende & Celso C. Ribeiro, 2010. "Greedy Randomized Adaptive Search Procedures: Advances, Hybridizations, and Applications," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 283-319, Springer.
    14. Jesus Gonzalez-Feliu, 2011. "Two-echelon freight transport optimisation: unifying concepts via a systematic review," Post-Print halshs-00569980, HAL.
    15. Jourdan, L. & Basseur, M. & Talbi, E.-G., 2009. "Hybridizing exact methods and metaheuristics: A taxonomy," European Journal of Operational Research, Elsevier, vol. 199(3), pages 620-629, December.
    16. Baldacci, Roberto & Mingozzi, Aristide & Roberti, Roberto, 2012. "Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints," European Journal of Operational Research, Elsevier, vol. 218(1), pages 1-6.
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