Low-Carbon Multimodal Transportation Route Optimization Based on Uncertain Demand and Schedule Limitation

Low-carbon multimodal transportation can not only effectively reduce logistics transportation costs, but also reduce environmental pollution. A multimodal transportation path optimization model with the minimum transportation cost, carbon emission cost, waiting time penalty fee and transportation time among OD transportation routes is established by considering the uncertain demand and the transportation mode’s schedule limitation. In order to solve the problem easily, the expected value is used to deal with the fuzzy variables in the constraints. An improved artificial bee colony algorithm is designed to solve the optimized model. Through sensitivity analysis of delivery deadline and weight factor, it is found that by changing the values of these parameters, multimodal operators can be guided to pick different transportation schemes based on their needs.