Collaborative Optimization For Train Stopping Pattern And Train Timetable On High-speed Railway Line

With the continuous expansion of high-speed railway network,the high-speed rail has basically achieved coverage in major cities across the country and has entered a period of large-scale network operation.However,the huge transportation resources and superstrong transportation demand put forward new requirements for the operation and management of high-speed railway,especially making it more difficult to formulate a reasonable train operation organization plan based on system optimization.Train stopping pattern and train timetable are the basic planning of transportation plan,which has an important influence on transportation time,cost and efficiency,while train stopping pattern is an important component of train operation plan and train timetable.Therefore,developing research of integrated optimization methods for train timetabling and train stopping pattern problems is of great instructive significance for the rational allocation of transportation resources and the improvement of the level of transportation service.The specific work and conclusions of the paper are as follows:(1)Developing research on the relevant theories of train stopping pattern and train timetable for high-speed railway.Firstly,this paper introduces the decision variables,and the main optimization goals and constraints of the train stopping pattern and train timetable,and conducts the correlation analysis between the decision variables and the objective function.On this basis,analyzing the necessity of integrated optimization,which contribute new ideas for subsequent modeling work.(2)Conducting an integrated optimization model of train timetable and train stopping pattern problems.Based on the train time-space network,it is transformed into a network optimization problem,and a collaborative optimization model is constructed with the goal of minimizing the weighted sum of the total train travel time,the delay time at the departure station and the number of train stops.The model needs to meet the expected departure time,train stop time,station capacity,train safety interval time and inter-station service accessibility constraints.Finally,this paper designs a small calculation case and uses the GAMS software to solve it.The accuracy of the model is verified by the calculation example.(3)Design and implementation of the solving algorithm.By analyzing the complexity of the model,considering the efficiency of multiple algorithms,this paper chooses the basic idea based on the Lagrangian relaxation algorithm,designs a solution algorithm with a pricing feedback mechanism,and decomposes the original problem into two sub-problems,a train stopping pattern and train timetable optimization.Finally,the specific process of the entire algorithm is designed,and the algorithm is programmed in C# language,and the same small case as GAMS is solved to verify the feasibility of the algorithm.(4)Analysis and optimization of the actual case.Based on the basic data of the Beijing-Shanghai high-speed railway network,a detailed analysis of its train operation and station service requirements was carried out.Then uses the above methods to verify the effectiveness,and a better train stopping pattern and train timetable are calculated.The optimization results are analyzed from the three aspects of feasibility,it shows that the model and algorithm proposed in this paper is of good applicability and has a certain guiding effect on actual production.