An extended goal programming framework incorporating poverty measures: application to food bank logistics

Abstract Food banks play a key role in reducing food insecurity, yet their operations are often constrained by manual and non‐optimised allocation procedures. This study introduces a methodological advance through an extended goal programming model with poverty incorporation (EGP‐PI). The EGP‐PI extends classical goal programming (GP) by embedding dynamically defined poverty measures directly into the deviation structure and by transforming multidimensional vulnerability attributes into endogenous optimisation weights. This creates a poverty‐sensitive, data‐driven prioritisation mechanism not present in traditional GP. The formulation also integrates dynamic inventory management and First Expired, First Out (FEFO)‐based shelf‐life control, ensuring coherence between perishability, fairness and efficiency across sequential connected planning periods. The model is validated using operational data from the São Paulo municipal food bank, one of the largest metropolitan systems in the world. Results show substantial improvements in allocation fairness, poverty targeting and resource utilisation, providing a quantitative and socially responsive tool for humanitarian food‐distribution systems.