On-time and energy-saving train operation strategy based on improved AGA multi-objective optimization

Abstract

On-time and energy-saving train operation is important for the sustainable development of rail transit. As for the problems of traction energy consumption and on-time arrival at stations faced by trains in rail transit, an optimization strategy of energy-saving speed curves of trains based on an improved adaptive genetic algorithm (AGA) was proposed in this paper. First, weight coefficients of operation time and energy consumption were designed through an analytic hierarchy process, and an optimization model that targets train operation time and energy consumption was established according to a basic train operation model with constraints such as speed limits and precise train stopping. Then, on-time and energy-saving speed curves of trains were generated based on the improved AGA. Finally, a simulation was carried out with actual rail transit lines. The results show that the proposed method has strong efficiency for energy conservation and better optimization performance than the simple genetic algorithm in solving train trajectory optimization problem.