A study on intelligent computation of methods of optimization operation for train

Energy-saving train operations are significant both in theory and in applications, but computing the optimization of train operations is very difficult and complex. The optimization computation problem of energy-saving train operations on an undulating-slope line is discussed by means of an intelligent computation model in this paper. To generate the optimal train operation diagram, an intelligent computation model combining local optimization with global optimization is proposed. The local optimization's numerical functions are obtained from the simulation computation, and the construction of those data is realized by a neural network. The global optimization computation, using a genetic algorithm, generates the train operation diagram. Theoretical analysis and simulation experiments show that the result is satisfactory. Moreover, compared to other methods, not only is the energy saving greater but the computational efficiency is greatly improved too.