[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v230y2013i2p231-244.html
   My bibliography  Save this article

A matheuristic for the truck and trailer routing problem

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037722171300324X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2013.04.026?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2013. "Heuristics for multi-attribute vehicle routing problems: A survey and synthesis," European Journal of Operational Research, Elsevier, vol. 231(1), pages 1-21.
    2. Brandstätter, Christian & Reimann, Marc, 2018. "The Line-haul Feeder Vehicle Routing Problem: Mathematical model formulation and heuristic approaches," European Journal of Operational Research, Elsevier, vol. 270(1), pages 157-170.
    3. Lahyani, Rahma & Khemakhem, Mahdi & Semet, Frédéric, 2015. "Rich vehicle routing problems: From a taxonomy to a definition," European Journal of Operational Research, Elsevier, vol. 241(1), pages 1-14.
    4. John E. Fontecha & Oscar O. Guaje & Daniel Duque & Raha Akhavan-Tabatabaei & Juan P. Rodríguez & Andrés L. Medaglia, 2020. "Combined maintenance and routing optimization for large-scale sewage cleaning," Annals of Operations Research, Springer, vol. 286(1), pages 441-474, March.
    5. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    6. Ehmke, Jan Fabian & Campbell, Ann Melissa, 2014. "Customer acceptance mechanisms for home deliveries in metropolitan areas," European Journal of Operational Research, Elsevier, vol. 233(1), pages 193-207.
    7. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    8. Zhang, Zizhen & Qin, Hu & Wang, Kai & He, Huang & Liu, Tian, 2017. "Manpower allocation and vehicle routing problem in non-emergency ambulance transfer service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 45-59.
    9. Yan Cheng Hsu & Jose L. Walteros & Rajan Batta, 2020. "Solving the petroleum replenishment and routing problem with variable demands and time windows," Annals of Operations Research, Springer, vol. 294(1), pages 9-46, November.
    10. Huber, Sandra & Geiger, Martin Josef, 2017. "Order matters – A Variable Neighborhood Search for the Swap-Body Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 263(2), pages 419-445.
    11. Michael Schneider & Andreas Stenger & Dominik Goeke, 2014. "The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations," Transportation Science, INFORMS, vol. 48(4), pages 500-520, November.
    12. Juan José Miranda-Bront & Brian Curcio & Isabel Méndez-Díaz & Agustín Montero & Federico Pousa & Paula Zabala, 2017. "A cluster-first route-second approach for the swap body vehicle routing problem," Annals of Operations Research, Springer, vol. 253(2), pages 935-956, June.
    13. Chen, Qingfeng & Li, Kunpeng & Liu, Zhixue, 2014. "Model and algorithm for an unpaired pickup and delivery vehicle routing problem with split loads," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 218-235.
    14. Shijin Wang & Xiaodong Wang & Xin Liu & Jianbo Yu, 2018. "A Bi-Objective Vehicle-Routing Problem with Soft Time Windows and Multiple Depots to Minimize the Total Energy Consumption and Customer Dissatisfaction," Sustainability, MDPI, vol. 10(11), pages 1-21, November.
    15. Ehsan Khodabandeh & Lihui Bai & Sunderesh S. Heragu & Gerald W. Evans & Thomas Elrod & Mark Shirkness, 2017. "Modelling and solution of a large-scale vehicle routing problem at GE appliances & lighting," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1100-1116, February.
    16. Md. Anisul Islam & Yuvraj Gajpal, 2021. "Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    17. Ciancio, Claudio & Laganá, Demetrio & Vocaturo, Francesca, 2018. "Branch-price-and-cut for the Mixed Capacitated General Routing Problem with Time Windows," European Journal of Operational Research, Elsevier, vol. 267(1), pages 187-199.
    18. Alcaraz, Juan J. & Caballero-Arnaldos, Luis & Vales-Alonso, Javier, 2019. "Rich vehicle routing problem with last-mile outsourcing decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 263-286.
    19. Simona Mancini, 2013. "Multi-echelon distribution systems in city logistics," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 54, pages 1-2.
    20. Lai, David S.W. & Caliskan Demirag, Ozgun & Leung, Janny M.Y., 2016. "A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 32-52.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:230:y:2013:i:2:p:231-244. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.