Aiming at demand and transportation time uncertainty in path optimization of low-carbon multi⁃modal transport，a hybrid robust stochastic optimization model is established considering transportation cost，transshipment cost，time cost，and carbon emission cost comprehensively. A genetic algorithm based on random sampling is designed and tested for validity. The low-carbon multimodal transportation

schemes and costs under different modes are compared and the impact of uncertain parameters are analyzed based on the case study. The results show the following findings：first，the uncertain mode will affect the decision-making of low-carbon multimodal transportation；second，robust optimization with demand un⁃certainty will increase the total cost of low carbon multimodal transportation；third，the impact of time un⁃certainty on the total cost fluctuates with no obvious rules. Therefore，by comprehensively weighing the impact of uncertainty，selecting the appropriate maximum regret value，paying close attention to and strengthening time constraints，etc. ，multimodal transportation carriers can improve their adaptability to complex market situations，reduce costs to improve operational efficiency and promote high-quality devel⁃opment of transportation services.