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A Matheuristic for the Multivehicle Inventory Routing Problem

Author

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  • Claudia Archetti

    (Department of Economics and Management, University of Brescia, 25122 Brescia, Italy)

  • Natashia Boland

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Grazia Speranza

    (Department of Economics and Management, University of Brescia, 25122 Brescia, Italy)

Abstract

We consider the inventory routing problem, in which a supplier has to replenish a set of customers by means of a limited fleet of capacitated vehicles over a discrete time horizon. The goal is to minimize the total cost of the distribution that comprises the inventory cost at the supplier and at the customers and the routing cost. We present a matheuristic that combines a tabu search and mathematical programming formulations. When compared with two exact methods on 640 small instances, the matheuristic finds 192 (48%) optima over the 402 instances with known optima and improves 125 upper bounds. Tested on 240 large instances (with up to 200 customers) for which no optimal solutions are known, it improves the best solution for 220 (92%) of the 240 instances.

Suggested Citation

  • Claudia Archetti & Natashia Boland & Grazia Speranza, 2017. "A Matheuristic for the Multivehicle Inventory Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 29(3), pages 377-387, August.
    • Handle: RePEc:inm:orijoc:v:29:y:2017:i:3:p:377-387
    DOI: 10.1287/ijoc.2016.0737
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    References listed on IDEAS

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    8. Yossiri Adulyasak & Jean-François Cordeau & Raf Jans, 2014. "Optimization-Based Adaptive Large Neighborhood Search for the Production Routing Problem," Transportation Science, INFORMS, vol. 48(1), pages 20-45, February.
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    Cited by:

    1. Qiu, Yuzhuo & Zhou, Dan & Du, Yanan & Liu, Jie & Pardalos, Panos M. & Qiao, Jun, 2021. "The two-echelon production routing problem with cross-docking satellites," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    2. Skålnes, Jørgen & Ben Ahmed, Mohamed & Hvattum, Lars Magnus & Stålhane, Magnus, 2024. "New benchmark instances for the inventory routing problem," European Journal of Operational Research, Elsevier, vol. 313(3), pages 992-1014.
    3. Alvarez, Aldair & Cordeau, Jean-François & Jans, Raf & Munari, Pedro & Morabito, Reinaldo, 2020. "Formulations, branch-and-cut and a hybrid heuristic algorithm for an inventory routing problem with perishable products," European Journal of Operational Research, Elsevier, vol. 283(2), pages 511-529.
    4. Song, Ruidian & Zhao, Lei & Van Woensel, Tom & Fransoo, Jan C., 2019. "Coordinated delivery in urban retail," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 122-148.
    5. Manousakis, Eleftherios & Repoussis, Panagiotis & Zachariadis, Emmanouil & Tarantilis, Christos, 2021. "Improved branch-and-cut for the Inventory Routing Problem based on a two-commodity flow formulation," European Journal of Operational Research, Elsevier, vol. 290(3), pages 870-885.
    6. Malladi, Krishna Teja & Sowlati, Taraneh, 2018. "Biomass logistics: A review of important features, optimization modeling and the new trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 587-599.
    7. Bertazzi, Luca & Coelho, Leandro C. & De Maio, Annarita & Laganà, Demetrio, 2019. "A matheuristic algorithm for the multi-depot inventory routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 524-544.
    8. Li, Yantong & Chu, Feng & Côté, Jean-François & Coelho, Leandro C. & Chu, Chengbin, 2020. "The multi-plant perishable food production routing with packaging consideration," International Journal of Production Economics, Elsevier, vol. 221(C).
    9. 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).
    10. Nikzad, Erfaneh & Bashiri, Mahdi & Abbasi, Babak, 2021. "A matheuristic algorithm for stochastic home health care planning," European Journal of Operational Research, Elsevier, vol. 288(3), pages 753-774.
    11. Diabat, Ali & Bianchessi, Nicola & Archetti, Claudia, 2024. "On the zero-inventory-ordering policy in the inventory routing problem," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1024-1038.
    12. Ziye Tang & Yang Jiao & R. Ravi, 2022. "Combinatorial Heuristics for Inventory Routing Problems," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 370-384, January.
    13. Absi, Nabil & Archetti, Claudia & Dauzère-Pérès, Stéphane & Feillet, Dominique & Speranza, M. Grazia, 2018. "Comparing sequential and integrated approaches for the production routing problem," European Journal of Operational Research, Elsevier, vol. 269(2), pages 633-646.
    14. Archetti, Claudia & Christiansen, Marielle & Grazia Speranza, M., 2018. "Inventory routing with pickups and deliveries," European Journal of Operational Research, Elsevier, vol. 268(1), pages 314-324.
    15. Çelik, Melih & Archetti, Claudia & Süral, Haldun, 2022. "Inventory routing in a warehouse: The storage replenishment routing problem," European Journal of Operational Research, Elsevier, vol. 301(3), pages 1117-1132.
    16. Vidal, Thibaut & Laporte, Gilbert & Matl, Piotr, 2020. "A concise guide to existing and emerging vehicle routing problem variants," European Journal of Operational Research, Elsevier, vol. 286(2), pages 401-416.
    17. Archetti, Claudia & Coelho, Leandro C. & Grazia Speranza, M., 2019. "An exact algorithm for the inventory routing problem with logistic ratio," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 96-107.
    18. Angel A. Juan & Peter Keenan & Rafael Martí & Seán McGarraghy & Javier Panadero & Paula Carroll & Diego Oliva, 2023. "A review of the role of heuristics in stochastic optimisation: from metaheuristics to learnheuristics," Annals of Operations Research, Springer, vol. 320(2), pages 831-861, January.
    19. Archetti, Claudia & Ljubić, Ivana, 2022. "Comparison of formulations for the Inventory Routing Problem," European Journal of Operational Research, Elsevier, vol. 303(3), pages 997-1008.
    20. Bertazzi, Luca & Chua, Geoffrey A. & Laganà, Demetrio & Paradiso, Rosario, 2022. "Analysis of effective sets of routes for the split-delivery periodic inventory routing problem," European Journal of Operational Research, Elsevier, vol. 298(2), pages 463-477.
    21. Skålnes, Jørgen & Andersson, Henrik & Desaulniers, Guy & Stålhane, Magnus, 2022. "An improved formulation for the inventory routing problem with time-varying demands," European Journal of Operational Research, Elsevier, vol. 302(3), pages 1189-1201.
    22. Chiu, Agustín & Angulo, Gustavo & Larrain, Homero, 2024. "Optimizing the long-term costs of an Inventory Routing Problem using linear relaxation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    23. Masoud Chitsaz & Jean-François Cordeau & Raf Jans, 2019. "A Unified Decomposition Matheuristic for Assembly, Production, and Inventory Routing," INFORMS Journal on Computing, INFORMS, vol. 31(1), pages 134-152, February.

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    18. Archetti, Claudia & Christiansen, Marielle & Grazia Speranza, M., 2018. "Inventory routing with pickups and deliveries," European Journal of Operational Research, Elsevier, vol. 268(1), pages 314-324.
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    20. Masoud Chitsaz & Jean-François Cordeau & Raf Jans, 2019. "A Unified Decomposition Matheuristic for Assembly, Production, and Inventory Routing," INFORMS Journal on Computing, INFORMS, vol. 31(1), pages 134-152, February.

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