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A stochastic mixed-integer model to support foodbank resources prepositioning during the prelude to a natural disaster

Author

Listed:
  • Adrian F. Rivera
  • Neale R. Smith
  • Esteban Ogazon
  • Angel Ruiz

Abstract

A key strategic issue in pre-disaster planning for humanitarian logistics is the pre-establishment of adequate capacity and resources that enable efficient relief operations. Foodbanks must review their decisions and replan their activities upon the arrival of catastrophic events, such as earthquakes or floods. With the aim to support managers in the adaptation of their network and preparedness decisions during the prelude to the event, this paper presents a scenario-based stochastic mixed-integer optimisation formulation that aims to minimise the maximum amount of unfulfilled relief needs considering uncertainty both on the demand as well as on the availability of the infrastructure. The formulation was applied to the case of hurricane Odile that struck the Baja California Peninsula, Mexico, in 2014. Numerical experiments demonstrate that the solution reached by the proposed mathematical formulation improved the actual decisions that were made during the event. Further comparisons and analyses are presented. [Submitted: 19 October 2021; Accepted: 24 February 2022]

Suggested Citation

  • Adrian F. Rivera & Neale R. Smith & Esteban Ogazon & Angel Ruiz, 2023. "A stochastic mixed-integer model to support foodbank resources prepositioning during the prelude to a natural disaster," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 17(3), pages 460-477.
    • Handle: RePEc:ids:eujine:v:17:y:2023:i:3:p:460-477
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