Research On Multi-objective Optimization Of Train Operation Strategy In Urban Rail Transit

With the in-depth development of urbanization in our country,the concept of convenient transportation has become an important connotation of urban sustainable development.While the urban rail transit system facilitates people’s travel,it also causes huge energy consumption.The energy-saving optimization problem of the urban rail transit system’s train operation strategy has been urgent.An efficient operation strategy should not only consider the cost optimization of the operating company,but also take into account the benefits of passenger travel services.Therefore,more and more researches focus on the establishment of a train operation strategy optimization model based on single-vehicle control strategies and train operation schedules,to weigh the operating costs and passenger benefits.Aiming at the optimization problem of urban rail transit train operation strategy,this thesis establishes a multi-objective optimization model of single-train section operation strategy and a multi-objective timetable optimization model that aims to reduce the total net energy consumption of trains on the whole line and the total waiting time of passengers.Design two multi-objective optimization model solving algorithms to carry out the optimization research of train operation strategy.Establish a multi-objective optimization model of single-train section control strategy.Based on the characteristics of complex line changes,the inter-station section is spatially nonequally separated into several sections,and the train real-time "running speed-spatial displacement-running time" constitutes the state variable to establish and describe the train movement process in a three-dimensional space Discrete state space.Taking the ramp and speed limit of the section line as well as the on-time train arrival,precise parking,safety and comfort,etc.as constraints,the multi-objective optimization of the single-train section operation strategy is established with the goal of minimizing the traction energy consumption and running time of the train section operation model.Based on the non-dominated sorting genetic algorithm(NSGA-II),the solution strategy of the multi-objective optimization model of the maneuvering strategy is designed.the Pareto frontier of the traction energy consumption and the running time of the inter-station operation is obtained.Establish a multi-objective timetable energy-saving optimization model considering passenger waiting time.Based on the utilization of the regenerative energy of the trains in the urban rail transit system and the utilization of the regenerative energy when the trains have multiple traction and braking in the interval operation,a calculation model of the total net energy consumption of the trains on the whole line is constructed.Aiming at the shortcomings of the traditional passenger waiting time model such as changing the passenger to a constant value,an improved passenger waiting time model considering dynamic passenger flow changes is proposed to accurately reflect the passenger’s travel service benefits.By optimizing the stop time and inter-station running time of each station in the train schedule,the operating costs and passenger service benefits are the starting points,and a multi-target time is established with the goal of minimizing the total net train traction energy and total passenger waiting time on the entire line Table optimization model.Based on the non-dominated sorting genetic algorithm(NSGA-II),the multi-objective timetable optimization model solving algorithm design is carried out.Get the Pareto frontier of the total net energy consumption of train traction and total passenger waiting time.Finally,taking the Beijing Metro Yizhuang Line as an example,the performance of the Pareto optimal operation scheme of the model in this thesis is evaluated by using relevant standards and indicators in the existing literature.The experimental results verify the effectiveness of the multi-objective optimization model and algorithm proposed in this thesis.It provides the optimal operation strategy scheme for train operation decision-makers under the condition of weighing the operation cost and the interests of passengers.