Optimizing social costs in post-pandemic humanitarian distribution models

In response to the COVID-19 pandemic, the Red Cross Society of China played a crucial role in distributing medical donations, but the initial efforts were inefficient and neglected medical personnel's welfare. This study proposes a time-sensitive humanitarian distribution model that optimizes the social costs by integrating logistics and deprivation costs that cares about human suffering. We ues the Gini coefficient to evaluate delays in distribution, aiding trade-off analysis between logistics efforts and social welfare. Our findings show that the proposed model improves the Gini coefficient by an average of 33.96% across 500 scenarios. Additionally, investing 23.7% more in logistics costs reduces the Gini coefficient by 0.1, enhancing the social welfare of medical supplies distribution. Sensitivity analysis examines the impact of time delay and cost investment on the Gini coefficient, offering insights into balancing logistics investments and social welfare.