Optimization of Ato Operation Process of Urban Rail Train Based on Sa-Abc Algorithm

For the improved performance of urban rail trains, Some measures, such as reduced train energy consumption, improved the comfort of urban rail trains, and shorten the parking distance error and time error, were proposed. As a promising bionic algorithm, the artificial bee colony algorithm has the advantages of less control parameters, strong robustness and easy implementation. However, it still has the disadvantages of poor local development ability, slow convergence speed and low precision of optimization. In order to overcome the these disadvantages. In this paper, An improved artificial bee colony algorithm (the simulated annealing model - artificial bee colony algorithm), combined the simulation experiments on the actual circuit, was proposed. The result demostrated the effectiveness of the algorithm combined with multi-objective optimization of urban rail trains.