| High speed railway technology is the most beautiful business card in China.In just a few years,the rapid development of high-speed railway in China has greatly changed our daily life and way of travel.The high-speed railway network is crisscross and accessible in all directions.How to make greater use of highspeed railway,better meet the demand of passenger flow,more convenient for passenger travel,and at the same time,protect the revenue of railway enterprises,It is very important to make a reasonable train plan.The train stop plan is an important part of the operation plan.In this paper,the optimization of the stop plan is studied by using the knowledge of modern intelligent optimization algorithm.Firstly,it introduces the content of train stop plan,and divides the stop mode.Then,the optimization model of high-speed railway stop plan is constructed,which takes the balance of high-speed train stops in each stop mode and the accessibility of each station in the train operation section as the optimization goal,and takes the upper and lower limits of the number of stops in each stop mode and the stop rate of each station in the train operation section as the constraint conditions.In this paper,three intelligent optimization algorithms are used to solve the optimization model of high-speed railway stop scheme,which are genetic algorithm,genetic simulated annealing fusion algorithm and particle swarm optimization algorithm based on discrete binary.The basic principle and process of each algorithm are described in detail,and the corresponding model solving algorithm is designed.Finally,combined with the relevant data of Hangzhou-Changsha high-speed railway in 2019,using the optimization model solution algorithm of the highspeed railway stop scheme,the optimization of the balance of each type of stop mode and the accessibility of each station have been improved,and good results have been achieved,which verifies the effectiveness of the model and algorithm. |
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