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Technical Note—Worst-Case Benefit of Restocking for the Vehicle Routing Problem with Stochastic Demands

Author

Listed:
  • Luca Bertazzi

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

  • Nicola Secomandi

    (Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

Abstract

The extant literature on the vehicle routing problem with stochastic demands indicates that the restocking strategy yields moderate percentage expected cost reductions relative to the a priori approach but lacks theoretical support for this improvement. We conduct a worst-case analysis that corroborates the observed restocking benefits and enhances our understanding of a foundational model in logistics under uncertainty.

Suggested Citation

  • Luca Bertazzi & Nicola Secomandi, 2020. "Technical Note—Worst-Case Benefit of Restocking for the Vehicle Routing Problem with Stochastic Demands," Operations Research, INFORMS, vol. 68(3), pages 671-675, May.
    • Handle: RePEc:inm:oropre:v:68:y:2020:i:3:p:671-675
    DOI: 10.1287/opre.2019.1901
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    References listed on IDEAS

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    Cited by:

    1. De La Vega, Jonathan & Gendreau, Michel & Morabito, Reinaldo & Munari, Pedro & Ordóñez, Fernando, 2023. "An integer L-shaped algorithm for the vehicle routing problem with time windows and stochastic demands," European Journal of Operational Research, Elsevier, vol. 308(2), pages 676-695.

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