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Research On The Dynamic Operation Of The EMU Considering The Fluctuation Of Line Planning Within A Week

Posted on:2021-05-23Degree:MasterType:Thesis
Country:ChinaCandidate:Y T GongFull Text:PDF
GTID:2392330614471660Subject:Transportation planning and management
Abstract/Summary:PDF Full Text Request
With the development of socio-economy,the continuous improvement of the living standard and the change of consumption philosophy for our residents,people's requirements for the quantity and quality of travel are also constantly changing.In order to adapt to the dynamic changes in passenger demand,within a week,the railway enterprises always implement different train schedules according to the different conditions of the daily passenger flow,which is what we call the Dynamic Train Schedule.As an important transportation resource in the high-speed railway system,it is highly important and necessary to realize the rational planning for the using of the EMU and study the mechanisms to ensure the dynamic supply of capacity resources for the normal operation of trains and improving the level of transportation organization and service quality of the high-speed railway.Therefore,it is necessary to optimize the operation schedule of the EMU in accordance with the actual characteristics of the Dynamic Train Schedule,which is of great significance to further improve the using efficiency of EMU and reduce the operating costs.In this paper,the following aspects are studied in the context of the actual operation of the Dynamic Train Schedule at the railway site,with the objective of optimizing the EMU operation schedule,when the train schedules change dynamically during the week.(1)Systematic analysis of the EMU dynamic operation in the context of the Dynamic Train Schedule.Firstly,in the light of the application of Dynamic Train Schedule in the railway field,the research object of this paper is to study the EMU dynamic operation considering the fluctuations of line planning within a week;then,the application analysis of the EMU dynamic operation from three aspects: characteristics,influencing factors and application advantages;finally,the solution process of the EMU dynamic operation is proposed.(2)Research on modelling methods for the dynamic operation of the EMU.Firstly,according to the actual characteristics of the problem,optimization modeling ideas and model hypothesis conditions are proposed;then,the EMU operation network is established,and the EMU operation problem is transformed into a traveler problem(TSP problem);finally,according to the phased research method,the daily EMU circulation schedule optimization model with the minimum number of EMU used,and the weekly EMU operation schedule optimization model with the minimum number of EMU used and the minimum number of first-class maintenance operations are established.(3)Study of the algorithm for the optimization of the EMU operation schedule.Based on the characteristics of the model and the scale of the problem,the ACO algorithm is selected to solve the problem.the parts and the overall solution flow of the ACO are designed,and the special case of complex constraints and variable grouping train in the model is designed.(4)A case study of the Shanghai Railway Bureau's train schedule and a separately designed variable grouping train schedule.The feasibility and validity of the model and algorithm studied in this paper are verified by applying the research method of this paper to optimize the preparation of the weekly EMU operation schedule,and compare with practical operation schedule.Through the study of the relevant model and algorithm in this paper,a method for optimizing the preparation of the EMU operation schedule,which takes into account the fluctuation of the line planning within a week,has been developed,which can provide methodological and technical support for optimizing the preparation of the EMU operation schedule when the Dynamic Train Schedule is applied in the railway field.
Keywords/Search Tags:Dynamic Train Schedule, EMU Operation Schedule, TSP Problem, Train of Variable Grouping, ACO Algorithm
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