Resilience in humanitarian logistics : adjusting capacity in the points of distribution in natural disaster areas

Background: The administration and management of humanitarian logistical operations are considered critical factors. The extreme and unexpected nature of events such as natural disasters poses logistical challenges to humanitarian support agencies providing aid to the affected area. These logistical challenges are characterized by fluctuations in demand that generate uncertainty in the required capacity for aid, all of which are emphasized at the last link in the humanitarian supply chain: the point of distribution for humanitarian aid (the so-called last-mile problem). The objective of this research work is to support the decision-making process regarding capacity adjustments and the closure of the distribution points established in the disaster area. Methods: In response, a Markovian Decision Model for Capacity Adjustment was developed, focused not only on reducing traditional logistics costs but also on minimizing human suffering by incorporating so-called deprivation costs. Results: The model establishes adjustment policies for capacity for each aid period, and the existence of a monotonous policy that establishes an optimal threshold for closure decisions was demonstrated. Conclusions: It is possible to efficiently adjust the capacity at the distribution points and minimize the costs (both logistical and deprivation) associated with each decision period.