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Single-Period Cutting Planes for Inventory Routing Problems

Author

Listed:
  • Pasquale Avella

    (Dipartimento di Ingegneria, Università del Sannio, 82100 Benevento, Italy)

  • Maurizio Boccia

    (Dipartimento di Ingegneria, Università del Sannio, 82100 Benevento, Italy)

  • Laurence A. Wolsey

    (Center for Operations Research and Econometrics, Université catholique de Louvain, 1348 Louvain-la-Neuve, Belgium)

Abstract

The Inventory Routing Problem (IRP) involves the distribution of one or more products from a supplier to a set of clients over a discrete planning horizon. Each client has a known demand to be met in each period and can only hold a limited amount of stock. The product is shipped through a distribution network by one or more vehicles of limited capacity. The objective is to find replenishment decisions minimizing the sum of the storage and distribution costs. In this paper, we present IRP reformulations under the Maximum Level replenishment policy, derived from a single-period substructure. We define a generic family of valid inequalities, and then introduce two specific subclasses for which the separation problem of generating violated inequalities can be effectively solved. A basic Branch-and-Cut algorithm has been implemented to demonstrate the strength of the single-period reformulations. We present computational results for the benchmark instances with 50 clients and 3 periods and 30 clients and 6 periods.

Suggested Citation

  • Pasquale Avella & Maurizio Boccia & Laurence A. Wolsey, 2018. "Single-Period Cutting Planes for Inventory Routing Problems," Transportation Science, INFORMS, vol. 52(3), pages 497-508, June.
    • Handle: RePEc:inm:ortrsc:v:52:y:2018:i:3:p:497-508
    DOI: 10.1287/trsc.2016.0729
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    References listed on IDEAS

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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.
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    5. Oğuz Solyalı & Haldun Süral, 2011. "A Branch-and-Cut Algorithm Using a Strong Formulation and an A Priori Tour-Based Heuristic for an Inventory-Routing Problem," Transportation Science, INFORMS, vol. 45(3), pages 335-345, August.
    6. 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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    Cited by:

    1. Zhenzhen Zhang & Zhixing Luo & Roberto Baldacci & Andrew Lim, 2021. "A Benders Decomposition Approach for the Multivehicle Production Routing Problem with Order-up-to-Level Policy," Transportation Science, INFORMS, vol. 55(1), pages 160-178, 1-2.
    2. Archetti, Claudia & Speranza, M. Grazia & Boccia, Maurizio & Sforza, Antonio & Sterle, Claudio, 2020. "A branch-and-cut algorithm for the inventory routing problem with pickups and deliveries," European Journal of Operational Research, Elsevier, vol. 282(3), pages 886-895.
    3. 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.
    4. 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.
    5. Zhouxing Su & Zhipeng Lü & Zhuo Wang & Yanmin Qi & Una Benlic, 2020. "A Matheuristic Algorithm for the Inventory Routing Problem," Transportation Science, INFORMS, vol. 54(2), pages 330-354, March.
    6. Annelieke C. Baller & Said Dabia & Guy Desaulniers & Wout E. H. Dullaert, 2021. "The Inventory Routing Problem with Demand Moves," SN Operations Research Forum, Springer, vol. 2(1), pages 1-61, March.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Jia, Menglei & Chen, Feng, 2023. "Upward scalable vehicle routing problem of automobile inbound logistics with pickup flexibility," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    13. Bertazzi, Luca & Laganà, Demetrio & Ohlmann, Jeffrey W. & Paradiso, Rosario, 2020. "An exact approach for cyclic inbound inventory routing in a level production system," European Journal of Operational Research, Elsevier, vol. 283(3), pages 915-928.
    14. 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.
    15. 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.
    16. Hu, Weihong & Toriello, Alejandro & Dessouky, Maged, 2018. "Integrated inventory routing and freight consolidation for perishable goods," European Journal of Operational Research, Elsevier, vol. 271(2), pages 548-560.

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