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Nowadays, the study of disasters such as earthquakes and their consequences, specifically in metropolises such as Tehran, has attracted significant attention. Allocating relief goods to distribution centres before the earthquake and providing relief services to the injured can reduce the fatality rate. Therefore, it seems quite necessary to present a certain routing and allocation scheduling model of relief vehicles to serve the injured. In this research, a mathematical model was proposed to minimise the unmet demands and transportation costs of relief vehicles and in the affected areas. Regarding the inherent uncertainties of disasters, we developed a robust scenario-based optimisation model for relief logistics networks to reduce the risk of fatality and provide near-optimal solutions for different possible disaster scenarios. We showed that the proposed cooperation plan produces a situation with additive supper property, which means that this type of cooperation will finally lead to a greater incentive for aid agencies to form larger coalitions. Furthermore, we proposed a set of cooperative game theory methods to distribute the cost-saving of the cooperation fairly.

Robust cooperative planning of relief logistics operations under demand uncertainty: a case study on a possible earthquake in Tehran