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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. [ABSTRACT FROM AUTHOR]