在优化预约配额方案时，现有方法面临诸多挑战，包括动态性、随机性捕捉难，理论假设局限，以及数据获取处理复杂等。本文利用集卡的GPS轨迹数据，全面捕获了集卡从到达港口至完成作业的全过程周转时间，并基于此建立了单位预约时间窗口内集卡到达数量与其在港总周转时间之间的映射关系。利用该映射关系，构建了一个更为精确简洁的配额优化模型，并对集卡预约配额方案进行了优化求解。实验结果表明，优化后的预约配额方案有效减少了高峰期的集卡到达量，同时提高了低谷期的车辆到达数量，显著减少了集卡在港的总周转时间，提升了码头的运营效率，进而增强了港口竞争力。

When optimizing the reservation quota scheme, existing methods faced many challenges, including difficulty in capturing dynamics and randomness, limited theoretical assumptions, and complex data acquisition and processing. GPS trajectory data of container trucks was used to comprehensively capture the entire process of container truck turnover from arrival at the port to completion of operations, and based on this, establishes a mapping relationship between the number of container truck arrivals within the unit appointment time window and their total turnover time at the port. A more precise and concise quota optimization model was constructed by using this mapping relationship, and the quota appointment system for container trucks was optimized and solved. The experimental results show that the optimized reservation quota scheme effectively reduces the arrival volume of container trucks during peak periods, while increasing the number of vehicles arriving during off peak periods, significantly reducing the total turnover time of container trucks at the port, improving the operational efficiency of the terminal, and thereby enhancing the competitiveness of the port.