Capacity-Oriented Train Scheduling Problem Of High-Speed Railway

With the rapid growth of high-speed rail passenger demand in recent years,the actual passenger flow demand of some busy high-speed rail lines far exceed the transportation capacity.Only by making full use of the existing technical level and conditions to add more trains can railway companies serve more passengers and improve operational efficiency of high-speed railway organization.In order to make the high-speed rail line schedule more trains that meet the characteristics of passenger flow within the operating time of the whole day,this thesis studies oriented-capacity train scheduling problem of high-speed railway to maximize service capability.Different from the existing research,we not only make the distribution of train stops during different time periods match the distribution of passenger flow of each OD,and also consider the operation of rolling stock turnaround and daily maintenance,aiming to improve the service capacity of the rail line and better ensure the actual operability of the obtained train timetable.The main research contents of this thesis are as follows:(1)This thesis analyzes the oriented-capacity train scheduling problem of high-speed railway to the maximization of service capacity.The basic theory of train scheduling,transportation capacity and rolling stock operation used in this paper is analyzed.Then,we define the problem,analyze its optimization goals and influencing factors,and determine the maximum service capacity optimization idea.(2)This thesis establishes an oriented-capacity train scheduling optimization model.A time-space network that can describe the running path of the rolling stock is constructed,and the Lagrangian relaxation decomposition method is used to relax the complex constraints associated with multiple rolling stock units into the objective function to form a Lagrangian relaxation model,and then decompose the problem into multiple easy-to-solve models.A subproblem of route search based on a single motor car.(3)This thesis designs an algorithm based on Lagrangian relaxation decomposition.It includes two sub-algorithms for generating a relaxed solution and a feasible solution,which are used to optimize the upper and lower bounds corresponding to the target values of the relaxed solution and the feasible solution.Using the standard sub-gradient method,the lower bound is continuously approached to the optimal feasible solution through an iterative method,so as to obtain a better upper bound.(4)Based on the Wuhan-Guangzhou high-speed railway in China,the feasibility and effectiveness of the model solution method based on Lagrangian relaxation proposed in this thesis are verified.