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Assessing Different Two-Stage Stochastic Models for Optimizing Food Bank Networks’ Operations During Natural Disasters

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  • Esteban Ogazón

    (Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Monterrey 64849, Nuevo León, Mexico
    Faculty of Business Administration, Université Laval, Quebec, QC G1V 0A6, Canada
    Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Quebec, QC H3T 2B2, Canada)

  • Neale R. Smith

    (Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Monterrey 64849, Nuevo León, Mexico)

  • Angel Ruiz

    (Faculty of Business Administration, Université Laval, Quebec, QC G1V 0A6, Canada
    Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Quebec, QC H3T 2B2, Canada)

Abstract

Humanitarian logistics face significant challenges during natural disasters due to operational uncertainties. Humanitarian logistics networks such as food banks must manage both regular operations and disaster-induced supply and demand. The study aims to develop and assess two-stage stochastic models that support decision-making under these dual operations. We evaluate various decisional strategies through extensive numerical experiments inspired in the operation of the food bank network Bancos de Alimentos de México (BAMX), highlighting the importance of suitable timeframes for reactive and anticipative decisions. The findings offer valuable insights for managers in balancing routine and emergency responses efficiently.

Suggested Citation

  • Esteban Ogazón & Neale R. Smith & Angel Ruiz, 2024. "Assessing Different Two-Stage Stochastic Models for Optimizing Food Bank Networks’ Operations During Natural Disasters," Mathematics, MDPI, vol. 12(20), pages 1-24, October.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:20:p:3238-:d:1500123
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    References listed on IDEAS

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