A scenario-based stochastic programming model for multi-commodity distribution considering disruption in distribution network

As one of the core operations in disaster management, the relief distribution has been challenged by factors such as occurrence time, nature, the intensity of disasters impact, and the existence of secondary disasters (e.g., aftershock, landslides). The distribution of multi -commodity relief after disaster strikes becomes more significant when secondary disasters occur in the same or close areas. Secondary disasters may take place right after the primary disaster attack. Because of the diverse natures and the destruction of secondary disasters, the temporary relief distribution centers in operation for distributing commodities after the primary disaster can be disrupted. New temporary distribution centers should be constructed to cover the capacity of disrupted distribution centers. In addition, roads may be unavailable to transport the commodity, and the demand can vary significantly because of secondary disasters. To hedge against the disruption of temporary distribution canters and road unavailability, this paper proposes a mixed -integer stochastic programming model under demand and capacity uncertainty. The objective of this model is to minimize the unmet demand at relief collection centers. A computational study is performed to highlight the significance of this study, and the results show that the proposed approach is effective in secondary disasters perspective.