Energy-efficient Train Timetable Optimization For Urban Rail Transit With Time-varying Passenger Demand

With the increasing urban traffic problems,urban rail transit is favored by more and more cities,becoming the backbone of public transport.The development of urban rail transit alleviates the pressure of ground traffic with passenger traffic keeping on growing,but the huge energy consumption problems that it brings can not be ignored.The train ranning energy consumption is the most prominent of the urban rail transit system energy consumption.In this context,researching how to meet the passenger demand while reducing the train energy consumption from the transport organization level,is an important issue.Based on the level of transport organization and taking an urban rail transit line as the research object,taking into account the time-varying characteristics of passenger flow and traction energy consumption saving,this paper establishes the energy-saving train timetabling optimization model of urban rail transit with time-varying passenger flow,and designs adaptive genetic algorithm.The specific research contents are as follows:(1)Analysis on urban rail train timetabling optimization problem.On the basis of fully understanding the concept and characteristics of train timetable,the influencing factors of urban rail transit train timetable are analyzed from three aspects:passenger demand,operating condition and capacity resource,then,this paper summarizes energy-saving methods in the train timetabling optimization problem based on extensive researching on domestic and foreign related papers,put forwards the train timetable preparation framework.(2)Construction of optimization model for urban rail transit energy-saving train timetabling with time-varying passenger flow.Taking the passenger travel time and the total train running energy consumption as the goal,considering the passenger demand constraint and the train running related constraints,this paper puts forward a train timetabling optimization model.And the multi-objective function is transformed by the two-stage method based on AHP-fuzzy optimization theory to obtain the fuzzy optimal solution.(3)Research and design of Adaptive Genetic Algorithm for solving the train timetabling optimization model.According to the characteristics of the solution,different coding methods are designed for the two-part coding section of the departure time and the maximum train running speed.The adaptive crossover operator and the mutation operator are designed to improve the global search ability of the algorithm.We design program using MATLAB software to solve the problem.(4)Case studies and results analysis.Based on the data of Beijing urban rail transit Changping line,the line and train data,the timetable data and the OD passenger flow data are input into the algorithm of the optimization model.Different optimization schemes are obtained though changing the objective function and compared with the results of the initial scheme,and the result proves the superiority of our scheme,then the sensitivity of the train running number is analyzed.The experimental results verify the validity of the model and algorithm.