Effective Distribution of Primary Relief Supplies in Post-Disaster Scenarios

The frequency, severity, and impact of natural disasters are increasing globally, posing significant risks to both human lives and economic systems. Rising population density and the expansion of high-risk areas have further exacerbated the destructive consequences of these events. Earthquakes, in particular, represent a critical threat to densely populated regions, requiring the development of effective disaster response strategies. In this study, an optimization model was developed to ensure the fastest and most efficient delivery of aid materials stored in AFAD warehouses to the affected regions of Bingöl. In order to better represent local aid demands, Bingöl province was divided into 52 regions based on neighborhood proximity and population density. To avoid logistical complexity, the model ensures that each region receives aid from a single warehouse. It optimizes the timely and accurate distribution of five aid types (tents, beds, bed sets, heaters, and kitchen sets) by considering warehouse capacities, locations, available resources, geographical accessibility, and road conditions. The model was tested under two different scenarios to determine optimal warehouse-to-region assignments and was solved using IBM ILOG CPLEX software. According to the results, a total of 470,271 aid items were delivered using 525 vehicles, with each vehicle serving an average of 377 people. In this context, the model aims to accelerate post-disaster response, prevent potential complexity in aid distribution, and minimize human losses.