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The Continuous-Time Inventory-Routing Problem

Author

Listed:
  • Felipe Lagos

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Natashia Boland

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Martin Savelsbergh

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

We consider a continuous-time variant of the inventory-routing problem in which the maximum quantity that can delivered to a customer depends on the customer’s storage capacity and product inventory at the time of the delivery. We investigate critical components of a dynamic discretization discovery algorithm and demonstrate in an extensive computational study that these components are sufficient to produce provably high-quality, often optimal solutions.

Suggested Citation

  • Felipe Lagos & Natashia Boland & Martin Savelsbergh, 2020. "The Continuous-Time Inventory-Routing Problem," Transportation Science, INFORMS, vol. 54(2), pages 375-399, March.
    • Handle: RePEc:inm:ortrsc:v:54:y:2020:i:2:p:375-399
    DOI: 10.1287/trsc.2019.0902
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    References listed on IDEAS

    as
    1. Natashia Boland & Mike Hewitt & Luke Marshall & Martin Savelsbergh, 2017. "The Continuous-Time Service Network Design Problem," Operations Research, INFORMS, vol. 65(5), pages 1303-1321, October.
    2. 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.
    3. 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.
    4. Jin-Hwa Song & Martin Savelsbergh, 2007. "Performance Measurement for Inventory Routing," Transportation Science, INFORMS, vol. 41(1), pages 44-54, February.
    5. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Wang, Qingyi & Nie, Xiaofeng, 2023. "A location-inventory-routing model for distributing emergency supplies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    2. Belieres, Simon & Hewitt, Mike & Jozefowiez, Nicolas & Semet, Frédéric, 2021. "A time-expanded network reduction matheuristic for the logistics service network design problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    3. 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).
    4. Agra, Agostinho & Christiansen, Marielle & Wolsey, Laurence, 2022. "Improved models for a single vehicle continuous-time inventory routing problem with pickups and deliveries," European Journal of Operational Research, Elsevier, vol. 297(1), pages 164-179.
    5. Lara, Cristiana L. & Koenemann, Jochen & Nie, Yisu & de Souza, Cid C., 2023. "Scalable timing-aware network design via lagrangian decomposition," European Journal of Operational Research, Elsevier, vol. 309(1), pages 152-169.

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