Cargo Carrying Model of High-Speed Railway Express Considering Transportation Capacity Sharing and Carbon Trading

In order to maximise the utilisation of high-speed railway (HSR) transportation capacity and facilitate the low-carbon development in transportation infrastructure, this paper examines the cargo carrying method in the context of transportation capacity sharing of HSR. With carbon trading incorporated into the profit of HSR express, a cargo carrying decision-making model is formulated with consideration of carbon trading. The model incorporates key constraints, including loading capacity of HSR and work ability of stations. A multi-loading rules genetic algorithm is developed within a genetic algorithm framework to solve the model, addressing the influences of cargo service types, origin-destination (OD) pairs and loading priority of HSR trains. The numerical case of Xi’an-Chengdu HSR line is implemented to validate the proposed model by the Gurobi solver, and the performance of different algorithms is compared. Results demonstrate the rationality of the three proposed loading rules and the superior performance of the multi-loading rules genetic algorithm. Sensitivity analysis indicates that improving station work ability and incorporating train transfer can improve overall profitability. However, when station work ability reaches 400 kg/min, further increases yield negligible benefits to total profit. Moreover, considering train transfer does not significantly enhance overall profitability but substantially increases computation time.