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An assign-and-route matheuristic for the time-dependent inventory routing problem

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  • Touzout, Faycal A.
  • Ladier, Anne-Laure
  • Hadj-Hamou, Khaled

Abstract

In this paper, we consider a variant of the Inventory Routing Problem (IRP), the Time-Dependent IRP (TD-IRP). The TD-IRP extends the routing component of the IRP by making the travelling time between two locations no longer constant but depending on the departure time. In order to investigate the relevance of considering time-dependent travelling time functions, a set of new benchmark instances based on real-data is assumed. Numerical experiments show that optimising with time-dependent travelling times is cost-efficient, but computationally challenging. Thus, we propose a matheuristic that decomposes the problem, based on the observation of the structure of optimal TD-IRP solutions. The proposed matheuristic defines the set of clients to visit and the quantity to deliver for each period first and solves the routing problem second. Numerical experiments prove it to be very efficient and yield solutions with small gaps to the best lower bounds found. Because it separates the routing problem, the proposed matheuristic opens the possibility to solve the TD-IRP very efficiently by taking advantage of the rich literature on time-dependent routing problems.

Suggested Citation

  • Touzout, Faycal A. & Ladier, Anne-Laure & Hadj-Hamou, Khaled, 2022. "An assign-and-route matheuristic for the time-dependent inventory routing problem," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1081-1097.
  • Handle: RePEc:eee:ejores:v:300:y:2022:i:3:p:1081-1097
    DOI: 10.1016/j.ejor.2021.09.025
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    1. Guy Desaulniers & Jørgen G. Rakke & Leandro C. Coelho, 2016. "A Branch-Price-and-Cut Algorithm for the Inventory-Routing Problem," Transportation Science, INFORMS, vol. 50(3), pages 1060-1076, August.
    2. Wouter Lefever & Faycal A. Touzout & Khaled Hadj-Hamou & El-Houssaine Aghezzaf, 2021. "Benders' decomposition for robust travel time-constrained inventory routing problem," International Journal of Production Research, Taylor & Francis Journals, vol. 59(2), pages 342-366, January.
    3. Bernhard Fleischmann & Martin Gietz & Stefan Gnutzmann, 2004. "Time-Varying Travel Times in Vehicle Routing," Transportation Science, INFORMS, vol. 38(2), pages 160-173, May.
    4. N H Moin & S Salhi, 2007. "Inventory routing problems: a logistical overview," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(9), pages 1185-1194, September.
    5. Coelho, Leandro C. & Laporte, Gilbert, 2014. "Improved solutions for inventory-routing problems through valid inequalities and input ordering," International Journal of Production Economics, Elsevier, vol. 155(C), pages 391-397.
    6. Li, Kunpeng & Chen, Bin & Sivakumar, Appa Iyer & Wu, Yong, 2014. "An inventory–routing problem with the objective of travel time minimization," European Journal of Operational Research, Elsevier, vol. 236(3), pages 936-945.
    7. Ichoua, Soumia & Gendreau, Michel & Potvin, Jean-Yves, 2003. "Vehicle dispatching with time-dependent travel times," European Journal of Operational Research, Elsevier, vol. 144(2), pages 379-396, January.
    8. Rodrigues, Filipe & Agra, Agostinho & Christiansen, Marielle & Hvattum, Lars Magnus & Requejo, Cristina, 2019. "Comparing techniques for modelling uncertainty in a maritime inventory routing problem," European Journal of Operational Research, Elsevier, vol. 277(3), pages 831-845.
    9. Claudia Archetti & Luca Bertazzi & Gilbert Laporte & Maria Grazia Speranza, 2007. "A Branch-and-Cut Algorithm for a Vendor-Managed Inventory-Routing Problem," Transportation Science, INFORMS, vol. 41(3), pages 382-391, August.
    10. Sun, Peng & Veelenturf, Lucas P. & Dabia, Said & Van Woensel, Tom, 2018. "The time-dependent capacitated profitable tour problem with time windows and precedence constraints," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1058-1073.
    11. Rahimi, Mohammad & Baboli, Armand & Rekik, Yacine, 2017. "Multi-objective inventory routing problem: A stochastic model to consider profit, service level and green criteria," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 59-83.
    12. Alarcon Ortega, Emilio J. & Schilde, Michael & Doerner, Karl F., 2020. "Matheuristic search techniques for the consistent inventory routing problem with time windows and split deliveries," Operations Research Perspectives, Elsevier, vol. 7(C).
    13. Coelho, Leandro Callegari & De Maio, Annarita & Laganà, Demetrio, 2020. "A variable MIP neighborhood descent for the multi-attribute inventory routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    14. Yan Sun & Martin Hrušovský & Chen Zhang & Maoxiang Lang, 2018. "A Time-Dependent Fuzzy Programming Approach for the Green Multimodal Routing Problem with Rail Service Capacity Uncertainty and Road Traffic Congestion," Complexity, Hindawi, vol. 2018, pages 1-22, June.
    15. Rincon-Garcia, Nicolas & Waterson, Ben & Cherrett, Tom J. & Salazar-Arrieta, Fernando, 2020. "A metaheuristic for the time-dependent vehicle routing problem considering driving hours regulations – An application in city logistics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 429-446.
    16. Rifki, Omar & Chiabaut, Nicolas & Solnon, Christine, 2020. "On the impact of spatio-temporal granularity of traffic conditions on the quality of pickup and delivery optimal tours," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    17. Mohammad Rahimi & Armand Baboli & Yacine Rekik, 2017. "Multi-objective inventory routing problem : A stochastic model to consider profit, service level and green criteria," Post-Print hal-02311993, HAL.
    18. Franceschetti, Anna & Demir, Emrah & Honhon, Dorothée & Van Woensel, Tom & Laporte, Gilbert & Stobbe, Mark, 2017. "A metaheuristic for the time-dependent pollution-routing problem," European Journal of Operational Research, Elsevier, vol. 259(3), pages 972-991.
    19. Walter J. Bell & Louis M. Dalberto & Marshall L. Fisher & Arnold J. Greenfield & R. Jaikumar & Pradeep Kedia & Robert G. Mack & Paul J. Prutzman, 1983. "Improving the Distribution of Industrial Gases with an On-Line Computerized Routing and Scheduling Optimizer," Interfaces, INFORMS, vol. 13(6), pages 4-23, December.
    20. Leandro C. Coelho & Jean-François Cordeau & Gilbert Laporte, 2014. "Thirty Years of Inventory Routing," Transportation Science, INFORMS, vol. 48(1), pages 1-19, February.
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