Low-Carbon Railway Traffic Flow Organization: Integrated and Two-Stage Optimization of Traffic Routing and Train Formation

Railway freight transportation plays an important role in sustainable and low-carbon logistics systems. This study investigates a low-carbon railway traffic flow routing and train formation plan problem. An integrated optimization model is developed to jointly determine traffic flow routing, train service configuration, and reclassification decisions, with section running emissions and yard reclassification emissions included in the objective function as a carbon emission penalty cost. A two-stage optimization model under predetermined traffic flow routing is also constructed to evaluate the solution quality loss and computational efficiency of sequential decision-making. The nonlinear terms are linearized, and the resulting models are solved by Gurobi. A benchmark and eight extended medium-scale instances from 12-node to 19-node are used for numerical analysis. The results show that the integrated model obtains objective values no greater than those of the two-stage model, while the two-stage model provides near-optimal solutions with much shorter computational times. In the extended instances, the relative objective gap remains small, whereas the computational advantage of the two-stage model is evident. Sensitivity analysis further indicates that the carbon emission penalty coefficient mainly affects the objective value through the carbon penalty term, while total emissions remain relatively stable under the tested settings.