Energy optimisation of single train operation based on tabu search. (2016) - Cao, Fang; Liu, Shuqi
Amid concerns about rising energy prices and environmental issues, the optimisation of automatic train operation (ATO) is significant for energy-efficient operation of trains. Different from the previous researches, this paper presents a more accurate model of the train energy consumption by considering the control strategy of ATO. It then proposes two modifications of tabu search (TS) algorithm, which are named as up-down modification (UDM) and left-right modification (LRM), to optimise train recommended speed curve based on the presented model. The simulation results based on the Beijing Subway illustrate that the proposed approaches can achieve a good performance on energy reduction. Sensitivities of the parameters are analysed to illustrate that the proposed approach is practical and meaningful. In addition, the computation time is within 2 s, which is short enough to be applied in the real-time control of trains.