Research On Simulation Of Train Operation Based On Adaptive Genetic And Tabu Search Algorithm

In recent years,with great economic change in China,the rail transportation industry obtained the swirl and violent development.As the important component,the railway transport system,which takes up high operating costs,consumes a lot of energy.The proportion of energy consumed by train operation is relatively large.Therefore,under the premise of satisfying the operational requirements of railway transportation system,how to effectively reduce the energy consumption of train operation has great research significance.In this paper,based on the analysis of train characteristics and related traction knowledge,a train optimization model with time constraints is established.Combined with adaptive genetic and tabu search algorithm,Adaptive genetic and tabu search algorithm is designed,which is applied to the train energy-saving optimization problem.It utilizes the computer simulation technology to simulate the actual operation of the train,then analyzes the experimental results and data,which proves that the proposed algorithm can achieve the purpose of train energy saving.The main contents of this paper are as follows.(1)In order to solve problems,such as random roaming and premature convergence,with the improvement of tabu search algorithm and genetic algorithm,an adaptive genetic tabu search algorithm is designed.Firstly,aiming at the random roaming phenomenon of roulette selection strategy in genetic algorithm,the adaptive roulette selection strategy is designed,increasing the probability that the individual is inherited,and ensuring a certain degree of randomness to maintain the diversity of population;Secondly,for the shortcoming of fixed crossover probability and mutation probability,a dynamic adjustment crossover mutation probability formula based on population fitness value is designed,in order to avoid premature convergence;Thirdly,because of the weak climbing ability of genetic algorithm,the paper combines tabu search algorithm with genetic algorithm,as a tabu mutation operator involved in the algorithm operation,in order to enhance the overall performance of the algorithm.(2)In this paper,under the background of the energy saving operation of freight train,the minimum operating energy consumption of the train as the objective function,the train punctuality,speed limit and its working conditions conversion as a constraint,the corresponding train optimization model is established,and the adaptive genetic and tabu search algorithm is applied in the train energy-saving optimization problem.Finally,it uses MATLAB2015 as the programming platform,takes the control condition and running line of freight trains as data set,to verify the improved algorithm and model.Experiments show that the adaptive genetic and tabu search algorithm used to optimize the train energy consumption problem can reduce energy by about 9.6%.Nowadays,the practical application is being promoted.