The design of resilient food supply chain networks prone to epidemic disruptions

Food supply chains are nowadays perturbed by an increased and demand uncertainty, more suffering from unexpected disruptions. In the specific context of food (FSC) for perishable products, these could be linked to natural hazards, industrial accidents or epidemics their impact lead huge economic losses. The case epidemic events has been little studied in existing literature, although there numerous cases reported practice. At strategic level, this requires a novel risk modeling approach tackle correlation propagation features advanced stochastic multi-period models design FSC network. Our interest research is propose comprehensive two-stage scenario-based mathematical model resilient chain under uncertainty order adequately characterize disruptions, they modeled as compound process Monte Carlo procedure developed generate plausible scenarios. covers special characteristics FSC, such products perishability time discount prices based on product's age. addition, number resiliency strategies incorporated into core enhance resilience level network design. solved through efficient solution relying scenario reduction technique Benders decomposition. Numerous problem instances used validate derive managerial insights.