Optimization And Adjustment Of High-speed Railway Line Planning Based On Variable Grouping EMU

The travel demand of Chinese citizens has been growing significantly and continually with life qualities improved.The amount of train services has also been increasing with the refinement of China High-speed Railway Network(CHSRN).However,the differences of economic situations and population imbalance among areas can affect the passenger-flow structure.And the passenger-flow structure itself owns a feature of spatiotemporal difference,which leads to a low boarding rate during the off-peak period or in off-busy line sections as the rolling stock grouping method of CHSRN is fixed.For China Railway Departments,this low boarding rate will be regarded as a Transport Capacity Waste(TCW).Considering marketing disciplines,a suitable match between Planned Transport Capacity(PTC)and Actual Transport Amount(PTA)should be scheduled seriously under the condition that basic railway service requirements shall be met if railway departments were determined to optimize their high-speed railway transport products.To avoid TCW in off-busy line sections or in off-peak hours and to achieve a highly efficient rolling stock utilization,it has become another vital research direction that studying High-speed Train Line Plan(HTLP)Optimizations based on Flexible Rolling Stock Grouping Mode(FRSGM).In general,this thesis takes references from domestic and international research on FRSGM and Train Line Plan.To begin with,the thesis has studied the dynamic relationship between HTLP and passenger-flow demand.Then,the service periods of high-speed railway services are divided based on those dynamic features extracted from the previous part.Next,the match situation between HTLP and passenger-flow is adjusted.Finally,the optimization model and relevant algorisms based on FRSGM are introduced.The detailed contents are as follows.1.This thesis has stated a development history and current situations on FRSGM.And it gives clean definitions and analyzes features of HTLP and passenger-flow demand.The correlation between HTLP and passenger-flow demand is studied based on their dynamic relation.Ordered cluster analysis is adopted to divide the passenger-flow periods and a sample of a station in-and-out data is used as a sample.2.This thesis has established a match evaluation framework,which includes passenger-flow satisfying rate,average on-broad rate,the passenger structure match rate and other factors.A match evaluation method is designed based on weight coefficients of each index of information entropy.3.This thesis has introduced a HTLP optimization model,which belongs to a mix-integer programming model,based on FRSGM.The model takes a minimum total amount of comprehensive generalized cost of train operation as objective function.The constraints contain service level of passenger flow,train capacity in variable grouping,train attendance in variable grouping and etc.The model is delivered via Python and Cplex.4.The thesis has taken a case study as verification and validation(V&V).The HTLPs,whose evaluation results are marked as “general” or lower than “general”,are the inputs of the model.A comparation with the original one is also given as V&V。...