Operation Planning for Heavy‐Haul Railway Trains Under a Group Control Mechanism

ABSTRACT

Heavy‐haul railways face increasing pressure to improve transport capacity and operational efficiency, while conventional measures, such as increasing train weight and operating speed, are increasingly constrained by station layout, arrival‐departure track conditions, and infrastructure capacity. To improve the utilisation of existing railway resources without large‐scale infrastructure expansion, this study develops a group‐control‐based operation‐planning framework for heavy‐haul unit trains. A bi‐objective optimisation model is formulated to minimise the aggregate in‐transit time and demand mismatch penalty cost while coordinating destination‐specific freight demand, latest allowable arrival times, departure intervals, maintenance windows, train‐group limits and arrival‐departure track capacity. An improved NSGA‐II integrating hierarchical elitist preservation and adaptive crossover is developed to solve the model. Numerical experiments on the Daqin Heavy‐Haul Railway show that the proposed algorithm achieves a favourable overall balance between convergence efficiency and Pareto‐solution quality compared with conventional NSGA‐II and its single‐strategy variants. Operational comparisons further demonstrate that the proposed grouping method reduces the number of origin groups and shortens both aggregate and average in‐transit times relative to ungrouped operation and strict fixed four‐unit grouping, while satisfying freight‐demand and delivery‐time requirements. These results provide practical support for heavy‐haul railway operation planning under constrained infrastructure.