Optimization method of urban rail train operational plan based on O-D time-varying demand

Purpose–Under the constraints of given passenger service level and coupling travel demand with train departure time,this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of train trips and rolling stocks considering the time-varying demand of urban rail passenger flow.Design/methodology/approach–The authors optimize the train operational plan in a special network layout,i.e.an urban rail corridor with dead-end terminal yard,by decomposing it into two sub-problems:train timetable optimization and rolling stock circulation optimization.As for train timetable optimization,the authors propose a schedule-based passenger flow assignment method,construct the corresponding timetabling optimization model and design the bi-directional coordinated sequential optimization algorithm.For the optimization of rolling stock circulation,the authors construct the corresponding optimization assignment model and adopt the Hungary algorithm for solving the model.Findings–The case study shows that the train operational plan developed by the study’s approach meets requirements on the passenger service quality and reduces the operational cost to the maximum by minimizing the numbers of train trips and rolling stocks.Originality/value–The example verifies the efficiency of the model and algorithm.

A two-layer optimization model for high-speed railway line planning

Line planning is the first important strategic element in the railway operation planning process,which will directly affect the successive planning to determine the efficiency of the whole railway system.A two-layer optimization model is proposed within a simulation framework to deal with the high-speed railway (HSR) line planning problem.In the model,the top layer aims at achieving an optimal stop-schedule set with the service frequencies,and is formulated as a nonlinear program,solved by genetic algorithm.The objective of top layer is tominimize the total operation cost and unserved passenger volume.Given a specific stop-schedule,the bottom layer focuses on weighted passenger flow assignment,formulated as a mixed integer program with the objective of maximizing the served passenger volume andminimizing the total travel time for all passengers.The case study on Taiwan HSR shows that the proposed two-layer model is better than the existing techniques.In addition,this model is also illustrated with the Beijing-Shanghai HSR in China.The result shows that the two-layer optimization model can reduce computation complexity and that an optimal set of stop-schedules can always be generated with less calculation time.