针对低碳多式联运路径优化中需求和时间不确定的问题，综合考虑直接运输成本、转运成本、时间成本、碳排放成本，建立混合鲁棒随机优化模型，设计基于随机采样的遗传算法并进行有效性检验。通过算例研究比较不同不确定模式下低碳多式联运运输方案及成本，并分析不确定参数的影响。结果表明：不确定模式会影响低碳多式联运的运输决策，需求不确定的鲁棒优化会使总成本增加，时间的不确定性对总成本的影响呈现无明显规律的波浪形变化趋势。由此，多式联运承运企业可以通过综合权衡不确定性的影响、选择合适的最大遗憾值、关注和加强时间约束等方式提高复杂市场情境的应变能力，降低成本提高运营效率，促进运输服务高质量发展。

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.