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Research On Optimization Of Urban Rail Transit Operation Scheme

Posted on:2021-01-06Degree:MasterType:Thesis
Country:ChinaCandidate:C JiangFull Text:PDF
GTID:2392330605960911Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of rail transit in China,urban rail transit has become an increasingly important mode of travel for urban residents in China due to its advantages of speed,punctuality,large capacity,safety and cross-regional travel services.Due to the long distance of rail transit lines and the different development of the areas along the line,the distribution of passenger flow on the line is uneven.When the traditional single-pass train is used,the passenger flow in some sections is large,and the train capacity is insufficient;in some areas Segment passenger flow is low,and transportation capacity is wasted.However,the train departure plan for large and small interchanges shortens the departure time of trains in small intersections with large passenger flows,increases the departure density,reduces the overall waiting time cost of passengers,reduces the running cost of trains and the cost of vehicle purchase,and improves the service level.,Saving costs.Therefore,scientifically and rationally formulating train operation plans is particularly important,the specific research is as follows:(1)Detailed introduction and analysis of different train interchange forms,advantages and disadvantages and corresponding passenger flow characteristics;in terms of passenger flow characteristics,the spatial and temporal distribution of passenger flow and the imbalance of passenger flow cross section are analyzed;in terms of driving conditions,the passing capacity of the line is analyzed 1.The return capacity of the return station,the number of car bodies used,etc.In the aspect of operation management,the form of the return station of the line,the train formation plan and the stop plan of the train are analyzed.(2)The optimization model of trains running on large and small crossroads,with the total target minimum composed of the total waiting time cost of passengers on the whole line and the operating cost of the enterprise(train operating cost and vehicle purchase cost)as the objective function,with the minimum allowable departure The interval time,the maximum number of trains,the full load rate of trains,the minimum departure frequency,the return position of the return station,and the number of vehicles are used as constraints.(3)Taking an urban rail transit line in City B as an example,based on the passenger flow distribution characteristics of the line,using the passenger flow data between 23 stations on the entire line,using the established optimal model of the train operation plan and the genetic simulated annealing algorithm After solving,the optimal train running plan is: the number of trains on the big crossroads is 4 and the departure frequency is 13 pairs / hour;the number of trains on the small crossroads is 5 and the departure frequency is 13 pairs / hour;Between station 5 and station 19.The cost of passenger travel per unit hour is 2553.53 yuan,the operating cost of train per unit hour is 19881.37 yuan,and the cost of vehicle purchase per unit hour is 8915.78 yuan.Compare the optimal train operation plan with the original single-route train operation plan parameters,and the factors affecting the operation plan are the proportion of small cross-road passenger flow,the maximum full load rate,the position of the small cross-road return station,and the number of small cross-train trains,? weights and train departure frequency for sensitivity analysis,it can be seen that the size of the train crossing scheme can reduce the total waiting time cost of passengers,the operating cost of the train and the cost of vehicle purchase,and the full load rate of the train in each section is reduced and improved.The enterprise's service level to passengers is reduced,and the operation cost of the enterprise is reduced.
Keywords/Search Tags:Urban Rail Transit, Crossroads, Genetic Simulated Annealing Algorithm, Sensitivity Analysis
PDF Full Text Request
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