Optimization of Green Multimodal Transport Schemes Considering Order Consolidation under Uncertainty Conditions

As society becomes increasingly concerned with sustainable development, the demand for high-efficiency, low-cost, and green technology makes air-land multimodal transportation one of the effective means of fast freight transportation. In the actual transportation business, some orders will have overlapping transportation routes, and transporting each order separately will result in resource waste, high costs, and carbon emissions. This paper proposes a multimodal transportation scheme optimization model considering order consolidation to improve transport efficiency and reduce costs and carbon emissions. An improved genetic algorithm incorporating the ride-sharing scheduling method is designed to solve the model. The results show that order consolidation will reduce multimodal transport costs and carbon emissions but increase transportation time slightly, and the advantages in cost and carbon emission reduction will vary with origin-destination scenarios, which are ranked in order of single-origin single-destination, single-origin multi-destinations, multi-origin single-destination, and multi-origin multi-destination. For the fourth scenario, the cost and carbon emissions decrease by 16.6% and 26.69%, respectively, and the time increases by 5.56% compared with no consolidation. For the sensibility of customer demands, it is found that order consolidation has the advantage for price-sensitive, time- and price-sensitive, and time- and carbon emission-sensitive customers; however, it is specifically beneficial for time-sensitive customers only in single-origin single-destination scenarios.