Collaborative Optimization Of Train Stop Pattern And Train Timetable For High-Speed Railway Based On Passenger Demand

The proposal of "eight vertical and eight horizontal" high-speed railway network construction plan promotes the rapid development of high-speed railway.The development of high-speed railway services and the improvement of passenger travel service quality need not only complete facilities and equipment,but also efficient and scientific high-speed railway operation management.The train stop pattern and train timetable are the core contents of high-speed railway transportation organization.Studying the theory and method of collaborative optimization of high-speed railway train stop pattern and train timetable has important practical significance to improve the level of passenger service and railway transportation efficiency.Based on this practical problem,this paper completes the following work:(1)Analysis on basic content and relationship between the train stop pattern and train timetable for high-speed railway.This paper describes the basic concepts,basic elements,common optimization objectives and constraints of train stop pattern and train timetable for high-speed railway,analyzes the problems arising from the hierarchical optimization,and puts forward the necessity,importance and complexity of the collaborative optimization.It provides a theoretical basis for the subsequent research on the collaborative optimization of train stop pattern and train timetable for high-speed railway.(2)Establishment of collaborative optimization model of train stop pattern and train timetable for high-speed railway.This paper analyses the relationship between passenger flow and traffic flow with the help of spatio-temporal network graph.Then the collaborative optimization model is constructed to save the total travel time of passengers under the constraints of passenger flow conservation,safety interval time,train departure time,train stop time,train capacity,time window,etc.Finally,a small example is designed and solved by GAMS software.(3)The design and of algorithm for model.Considering the characteristics of the constructed model and the applicable conditions of various algorithms,a combined optimization algorithm is designed.It solves the train timetable problem by using improved particle swarm optimization algorithm and realizes the optimal allocation of passenger flow by using the capacity constraint incremental loading method.Finally,the algorithm is used to solve the above small-scale calculation examples,and the betterresults are obtained quickly.(4)Optimization and analysis of actual cases.This paper combs the relevant data of the real road network of Beijing Shanghai high-speed railway,and makes a detailed analysis of its passenger flow characteristics,train operation and station service content.By using the above model and algorithm to solve the case,the paper obtains the better train stop pattern and train timetable,which realizes the idea of collaborative optimization and proves the good application value of the model and algorithm.With 54 figures,37 tables and 63 reference literatures.