Energy-Efficient Train Operation Strategy with Speed Profiles Selection for an Urban Metro Line

Abstract

In the daily operations of a metro system, physical trains track the speed profiles which are embedded in the automatic train operation (ATO) system, and the speed profile plays a key role in determining both energy consumption and travel time. With consideration of the real-world operational environment and uncertain levels of passenger demand, this study specifically proposes an integer programming model with respect to energy consumption to generate a robust operational strategy which determines the speed profile choice on each segment. Because of the computational complexity of the proposed model, a heuristic algorithm is designed, which combines a genetic algorithm (GA) and a nomadic algorithm (NA), to find a good solution in acceptable computational time. Finally, numerical experiments based on the Beijing Yizhuang metro line are implemented to verify the effectiveness and efficiency of this approach.