多式联运的路径生成是区域产业经济活动联系主导下，受多重因素影响的结果。鉴于此，基于基础设施网络、产业活动、区域生产联系以及货物运输活动等多源综合交通运输大数据，考虑运输方式和中转衔接等影响因素，构建了包括路径最优、时间最优、可靠性最优在内的多目标多式联运路径生成模型。在此基础上，比较不同运输方式和节点差异，借助BPR模型修正得到多方式多式联运阻抗模型，并选取长三角区域作为案例，研究了其中基于时效性差异的货物多式联运模拟路径。研究结果表明，起止点相同的情况下，以成本为偏好的路径结果费用最低，但耗时最长；以时间为偏好的路径结果耗时最少，但费用最高；以可靠性为偏好的路径结果耗时与费用居中，但抗风险和抗运输网络扰动的能力最强。研究揭示了不同需求偏好下的多式联运路径生成差异。

The path generation of multimodal transportation is the result of multiple factors influenced by regional industrial and economic activities. In view of this, based on multi-source comprehensive transportation big data such as infrastructure network, industrial activities, regional production connections and cargo transportation activities, considering the influencing factors such as transportation mode and transit connection, a multi-objective multimodal transportation path generation model, including path optimization, time optimization and reliability optimization, was constructed. Then, the impedance model of multimodal transportation was modified by BPR model after comparing the differences between different transportation modes and nodes. Finally, Yangtze River Delta region was selected as a case to study the simulation path of multimodal transportation of goods based on timeliness differences. The results show that when the starting and ending points are the same, the cost-preferred path results in the lowest cost with the longest time; the time-preferred path takes the least time but costs the most; the reliability-preferred path results in the middle time and cost, but the ability to resist risks and transportation network disturbances is the strongest. The research reveals the difference in multimodal transportation path generation under different demand preferences.