eVTOL Dispatch Cost Optimization Under Time-Varying Low-Altitude Delivery Demand

In the emerging paradigm of embodied intelligence, eVTOL technology holds significant potential to transform the low-altitude economy, particularly in short-distance emergency logistics and urban distribution. Companies like Meituan and Shunfeng (SF) are pioneering fixed low-altitude routes to reduce reliance on human delivery. We first investigate the performance and routing of Meituan’s eVTOL system, focusing on the dynamic optimization of eVTOL reserves and total costs at distribution stations under fluctuating order surges and charging constraints. An iterative algorithm is constructed, supported by numerical examples and Monte Carlo simulations. Our results reveal that cost parameters and demand characteristics jointly shape eVTOL incremental decision-making and its economic performance. To optimize costs, strategies like multi-period decentralized scheduling or low-frequency centralized decision-making are proposed. Future research will address limitations such as 2C charging effects and joint battery-eVTOL replenishment to further advance urban logistics and low-altitude economy development.