IDEAS home Printed from https://ideas.repec.org/a/spr/joheur/v28y2022i5d10.1007_s10732-022-09503-6.html
   My bibliography  Save this article

Modeling and evolutionary algorithm for solving a multi-depot mixed vehicle routing problem with uncertain travel times

Author

Listed:
  • Liang Sun

    (Shandong University of Technology)

Abstract

This paper deals with a multi-depot mixed vehicle routing problem under uncertain travel times (MDMVRP-UT), where there are several different depots and a number of identical vehicles. A vehicle can come back to any of the depots after its service is completed. A light-robust-optimization model is set up to control the total travel time within a preset value and to minimize the total travel time as much as possible. Then an effective evolutionary algorithm (EA) is proposed to solve the light-robust-optimization model. In the proposed EA, two constructive heuristics, namely a random customer sequence-based heuristic and a minimum spanning tree-based heuristic, are presented according to the problem-specific knowledge to generate a high-quality initial population with a certain level of diversity. A destruction and construction-based reproduction operator is provided to give birth to high-quality feasible offspring. A pairwise interchange based local search method is proposed to enhance the local exploitation capability. A hybrid selection operator and a population updating method are employed to remain the diversity of the population. The effectiveness of the proposed EA is verified by comprehensive experiments based on the well-known benchmark instances in the literature.

Suggested Citation

  • Liang Sun, 2022. "Modeling and evolutionary algorithm for solving a multi-depot mixed vehicle routing problem with uncertain travel times," Journal of Heuristics, Springer, vol. 28(5), pages 619-651, December.
    • Handle: RePEc:spr:joheur:v:28:y:2022:i:5:d:10.1007_s10732-022-09503-6
    DOI: 10.1007/s10732-022-09503-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10732-022-09503-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10732-022-09503-6?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. Gilbert Laporte & François Louveaux & Hélène Mercure, 1992. "The Vehicle Routing Problem with Stochastic Travel Times," Transportation Science, INFORMS, vol. 26(3), pages 161-170, August.
    2. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    3. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    4. D Sariklis & S Powell, 2000. "A heuristic method for the open vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(5), pages 564-573, May.
    5. Lu, Da & Gzara, Fatma, 2019. "The robust vehicle routing problem with time windows: Solution by branch and price and cut," European Journal of Operational Research, Elsevier, vol. 275(3), pages 925-938.
    6. Éric Taillard & Philippe Badeau & Michel Gendreau & François Guertin & Jean-Yves Potvin, 1997. "A Tabu Search Heuristic for the Vehicle Routing Problem with Soft Time Windows," Transportation Science, INFORMS, vol. 31(2), pages 170-186, May.
    7. Calvete, Herminia I. & Gale, Carmen & Oliveros, Maria-Jose & Sanchez-Valverde, Belen, 2007. "A goal programming approach to vehicle routing problems with soft time windows," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1720-1733, March.
    8. Dimitris J. Bertsimas, 1992. "A Vehicle Routing Problem with Stochastic Demand," Operations Research, INFORMS, vol. 40(3), pages 574-585, June.
    9. Chrysanthos E. Gounaris & Panagiotis P. Repoussis & Christos D. Tarantilis & Wolfram Wiesemann & Christodoulos A. Floudas, 2016. "An Adaptive Memory Programming Framework for the Robust Capacitated Vehicle Routing Problem," Transportation Science, INFORMS, vol. 50(4), pages 1239-1260, November.
    10. Christophe Duhamel & Jean-Yves Potvin & Jean-Marc Rousseau, 1997. "A Tabu Search Heuristic for the Vehicle Routing Problem with Backhauls and Time Windows," Transportation Science, INFORMS, vol. 31(1), pages 49-59, February.
    11. Lu Zhen & Ziheng Xu & Chengle Ma & Liyang Xiao, 2020. "Hybrid electric vehicle routing problem with mode selection," International Journal of Production Research, Taylor & Francis Journals, vol. 58(2), pages 562-576, January.
    12. Cosmin Sabo & Petrică C. Pop & Andrei Horvat-Marc, 2020. "On the Selective Vehicle Routing Problem," Mathematics, MDPI, vol. 8(5), pages 1-11, May.
    13. Jorge Oyola & Halvard Arntzen & David L. Woodruff, 2018. "The stochastic vehicle routing problem, a literature review, part I: models," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 193-221, September.
    14. A N Letchford & J Lysgaard & R W Eglese, 2007. "A branch-and-cut algorithm for the capacitated open vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1642-1651, December.
    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. Jinil Han & Chungmok Lee & Sungsoo Park, 2014. "A Robust Scenario Approach for the Vehicle Routing Problem with Uncertain Travel Times," Transportation Science, INFORMS, vol. 48(3), pages 373-390, August.
    2. Yu, Vincent F. & Anh, Pham Tuan & Baldacci, Roberto, 2023. "A robust optimization approach for the vehicle routing problem with cross-docking under demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    3. Briseida Sarasola & Karl Doerner & Verena Schmid & Enrique Alba, 2016. "Variable neighborhood search for the stochastic and dynamic vehicle routing problem," Annals of Operations Research, Springer, vol. 236(2), pages 425-461, January.
    4. Yu Zhang & Zhenzhen Zhang & Andrew Lim & Melvyn Sim, 2021. "Robust Data-Driven Vehicle Routing with Time Windows," Operations Research, INFORMS, vol. 69(2), pages 469-485, March.
    5. Briseida Sarasola & Karl F. Doerner & Verena Schmid & Enrique Alba, 2016. "Variable neighborhood search for the stochastic and dynamic vehicle routing problem," Annals of Operations Research, Springer, vol. 236(2), pages 425-461, January.
    6. Jbili, S. & Chelbi, A. & Radhoui, M. & Kessentini, M., 2018. "Integrated strategy of Vehicle Routing and Maintenance," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 202-214.
    7. Sébastien Mouthuy & Florence Massen & Yves Deville & Pascal Van Hentenryck, 2015. "A Multistage Very Large-Scale Neighborhood Search for the Vehicle Routing Problem with Soft Time Windows," Transportation Science, INFORMS, vol. 49(2), pages 223-238, May.
    8. Chiang, Wen-Chyuan & Russell, Robert & Xu, Xiaojing & Zepeda, David, 2009. "A simulation/metaheuristic approach to newspaper production and distribution supply chain problems," International Journal of Production Economics, Elsevier, vol. 121(2), pages 752-767, October.
    9. Baals, Julian & Emde, Simon & Turkensteen, Marcel, 2023. "Minimizing earliness-tardiness costs in supplier networks—A just-in-time truck routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 707-741.
    10. Sana Jawarneh & Salwani Abdullah, 2015. "Sequential Insertion Heuristic with Adaptive Bee Colony Optimisation Algorithm for Vehicle Routing Problem with Time Windows," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-23, July.
    11. Shubhechyya Ghosal & Wolfram Wiesemann, 2020. "The Distributionally Robust Chance-Constrained Vehicle Routing Problem," Operations Research, INFORMS, vol. 68(3), pages 716-732, May.
    12. 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.
    13. Chen, Lijian & Chiang, Wen-Chyuan & Russell, Robert & Chen, Jun & Sun, Dengfeng, 2018. "The probabilistic vehicle routing problem with service guarantees," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 149-164.
    14. Karels, Vincent C.G. & Rei, Walter & Veelenturf, Lucas P. & Van Woensel, Tom, 2024. "A vehicle routing problem with multiple service agreements," European Journal of Operational Research, Elsevier, vol. 313(1), pages 129-145.
    15. Soumia Ichoua & Michel Gendreau & Jean-Yves Potvin, 2006. "Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching," Transportation Science, INFORMS, vol. 40(2), pages 211-225, May.
    16. Sungwon Lee & Taesung Hwang, 2018. "Estimating Emissions from Regional Freight Delivery under Different Urban Development Scenarios," Sustainability, MDPI, vol. 10(4), pages 1-14, April.
    17. Xiaoxu Wei & Zhouru Xiao & Yongsheng Wang, 2024. "Solving the Vehicle Routing Problem with Time Windows Using Modified Rat Swarm Optimization Algorithm Based on Large Neighborhood Search," Mathematics, MDPI, vol. 12(11), pages 1-33, May.
    18. 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.
    19. Campelo, Pedro & Neves-Moreira, Fábio & Amorim, Pedro & Almada-Lobo, Bernardo, 2019. "Consistent vehicle routing problem with service level agreements: A case study in the pharmaceutical distribution sector," European Journal of Operational Research, Elsevier, vol. 273(1), pages 131-145.
    20. Baozhen Yao & Qianqian Yan & Mengjie Zhang & Yunong Yang, 2017. "Improved artificial bee colony algorithm for vehicle routing problem with time windows," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-18, September.

    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:spr:joheur:v:28:y:2022:i:5:d:10.1007_s10732-022-09503-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.