Home Delivery

Home delivery research focuses on optimizing the efficiency and cost-effectiveness of last-mile logistics, driven by the surge in e-commerce. Current studies employ advanced machine learning techniques, including graph-based neural networks and convolutional neural networks, to predict delivery demand, dynamically allocate resources (like out-of-home delivery options), and optimize pricing strategies. These models leverage large datasets incorporating socioeconomic factors and spatial-temporal information to improve accuracy and efficiency. Findings inform both the development of more robust predictive models and the implementation of practical strategies to reduce costs and improve delivery service.