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Stochastic Inventory Routing for Perishable Products

Author

Listed:
  • Yves Crama

    (HEC Management School, University of Liège, 4000 Liège, Belgium)

  • Mahmood Rezaei

    (HEC Management School, University of Liège, 4000 Liège, Belgium)

  • Martin Savelsbergh

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

  • Tom Van Woensel

    (School of Industrial Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, Netherlands)

Abstract

Different solution methods are developed to solve an inventory routing problem for a perishable product with stochastic demands. The solution methods are empirically compared in terms of average profit, service level, and actual freshness. The benefits of explicitly considering demand uncertainty are quantified. The computational study highlights that in certain situations although a simple ordering policy can achieve very good performance, statistically and economically significant improvements are achieved when using more advanced solution methods. Managerial insights concerning the impact of shelf life and store capacity on profit are also obtained.

Suggested Citation

  • Yves Crama & Mahmood Rezaei & Martin Savelsbergh & Tom Van Woensel, 2018. "Stochastic Inventory Routing for Perishable Products," Transportation Science, INFORMS, vol. 52(3), pages 526-546, June.
    • Handle: RePEc:inm:ortrsc:v:52:y:2018:i:3:p:526-546
    DOI: 10.1287/trsc.2017.0799
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    References listed on IDEAS

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    3. Liu, Wenqian & Ke, Ginger Y. & Chen, Jian & Zhang, Lianmin, 2020. "Scheduling the distribution of blood products: A vendor-managed inventory routing approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    4. 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.
    5. 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.
    6. Song, Yang & Fan, Tijun & Tang, Yuewu & Xu, Chang, 2021. "Omni-channel strategies for fresh produce with extra losses in-store," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    7. 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).
    8. 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.
    9. A. Mor & M. G. Speranza, 2020. "Vehicle routing problems over time: a survey," 4OR, Springer, vol. 18(2), pages 129-149, June.
    10. Sonntag, Danja R. & Schrotenboer, Albert H. & Kiesmüller, Gudrun P., 2023. "Stochastic inventory routing with time-based shipment consolidation," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1186-1201.
    11. A. Mor & M. G. Speranza, 2022. "Vehicle routing problems over time: a survey," Annals of Operations Research, Springer, vol. 314(1), pages 255-275, July.

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