Abstract: Based on the demand uncertainty and carbon trading policies, this work aims to enable multi-modal transportation operators to develop low-carbon and efficient transportation plans. Considering the constraints of railway and waterway schedules as well as receiving time windows, a robust optimization model of multi-modal transportation routing with the objective as the minimum of economic cost is established using robust optimization to describe uncertain demand. Genetic algorithm is adopted to verify the rationality and effectiveness of the model. Results show that the schedule constraints of railway and waterway generate waiting time and then waiting cost; robust optimization with uncertain demand not only increases the economic cost by 19%, but also prefer low-carbon transportation in the mode selection; By balancing the relationship between the maximal regret value and the economic cost, multi-modal transportation operators can easily handle demand fluctuations in the freight market while also responding to low-carbon requirements.

Key words: multi-modal transportation, carbon trading policies, demand uncertainty, schedule, robust optimization