Adaptive Matching Algorithm and Scheduling Strategy in Cross Border Order Intelligent Allocation Platform

The intelligent allocation platform for cross-border orders must meet diverse requirements and high load processing requirements, and the adaptive matching algorithm highlights its unique advantages in this situation. This algorithm adopts dynamic learning and real-time improvement techniques, which can accurately capture the key attributes of orders and meet the diverse and complex allocation tasks through flexible weight configuration. This paper proposes a scheduling strategy of distributed architecture, which integrates deep learning model prediction, hybrid cloud and edge computing, and significantly enhances the operating efficiency and reliability of the platform. According to the performance evaluation results, the platform has excellent performance in order matching accuracy, response speed, and resource utilization, providing a more efficient order allocation solution for cross-border e-commerce.