Prepositioning network design for humanitarian relief purposes under correlated demand uncertainty.

ABSTRACT: Prepositioning relief network is an effective strategy to mitigate the impact of natural disasters and public health emergencies, such as the COVID-19 pandemic. However, designing a proper network is challenging due to limited information and, more importantly, the correlated demand uncertainty that exists among affected areas. We consider a network design problem for humanitarian relief purposes, where demand correlations exist and demand information is limited, i.e., only the mean demand and covariance matrix are known. Note that the covariance matrix can explicitly capture the correlated demand among areas. We formulate this problem as a mixed-integer two-stage distributionally robust location-inventory model, which is generally NP-hard and computationally intractable. The model is furt

SUBMITTER: Zhang X 

PROVIDER: S-EPMC10265446 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature