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optimization on the Driving Curve of Heavy Haul Trains Based on Artificial Bee Colony Algorithm

For the driving curve optimization of heavy haul trains with pneumatic braking, one of the biggest challenges is how to generate a driving curve on the long steep downward slope. Since the train velocity will increase rapidly due to a long releasing time and unsuitable position of applying the air braking will influence the operational efficiency or may cause accidents. In this paper, the optimization method for the driving curve of heavy haul trains is investigated. Based on the train dynamic model, an optimization model is firstly formulated, taking the energy consumption, running time and distance of pneumatic braking as the objectives. Practical constraints are considered, including the releasing time, velocity, minimum hold-on time and conversion rules of regimes. To solve this problem, the complex constraints are combined into the objective function by using penalty functions. Then, the artificial bee colony (ABC) algorithm is introduced to find the proper switching points of different regimes. Simulations are conducted based on the practical data of Shuohuang railway line and the results confirmed the effectiveness of the proposed algorithm.