| High-speed railways(HSR)have been developing rapidly in China.Compared with air transportation,highway transportation,and waterway transportation,HSRs have the advantages of large capacity,high safety,high comfortability,and high punctuality,which are the core of the Chinese comprehensive transportation system due to the strong competitiveness of the medium-distance transportation.With the rising of HSR lines and the rail network scale,disturbances on HSRs increase,including bad weather,equipment failures and human factors.Therefore,the normal operation of trains is affected,which can bring the delay of train and the deviation from the timetables.In order to mitigate effects of disturbances,the dispatcher must make some decisions and take some action according to experiences,practical field situation and technical specifications,which can adjust the timetables to rearrange the departure sequence and the departure time of delayed trains to recover the normal operation of HSR lines as soon as possible.Due to the high speed and the high running density of HSRs,effects caused by system disturbances can spread widely and fast,and the manual adjustments of dispatchers are required to be fast and efficient though the workload is heavy and difficult.As a matter of facts,capabilities and experiences of dispatchers are various,and there is always big difference between effects of disturbance mitigation measures implemented by different dispatchers even facing the same disturbance.Hence,it is necessary to build an efficient evaluation system and theoretical basis to quantitatively analyze effects of dispatching decisions,which is significant to improve the levels of dispatchers.This thesis starts with the HSR timetables,and build a mathematical model of timetable rescheduling based on the constraints including safety protection mechanisms of train control systems and the traction power supply.With genetic algorithm,the optimal solution is obtained and used as the basis for analysis and evaluation.Secondly,the resilience theory is selected to analyze the effects of rescheduling decisions made by dispatchers at the pre-disturbance stage,the during-disturbance stage and the postdisturbance stage.Finally,a simulation and verification platform is built,which can present the evaluation results,the practical and the optimal rescheduling strategies for different scenarios.The main innovations of the thesis are as follows:1.The optimal rescheduling strategies generation approach for multiple scenarios based on the genetic algorithm is proposed.The genetic algorithm has comprehensive search capabilities and is easy to find the global optimal solution.Compared with the traditional constraints,the thesis comprehensively considers the capacity of the power supply system and the maximum speed limit of train control systems during the operation of the train.The shortest delay time and the lowest energy consumption of trains are taken as the optimization objective functions,which is helpful to find the optimal solutions.2.A resilience-based evolution of rescheduling strategies is provided,which can make a direct analysis and evaluation of the system performance levels at the predisturbance stage,the during-disturbance stage and the post-disturbance stage.Based on the practical timetables,mathematical descriptions of various indicators are provided before and after adjustments are implemented,which can establish an evaluation index system.Therefore,the theoretical basis and evaluation basis are built for simulations and verifications.3.The simulation and verification approach to rescheduling timetables of practical scenarios is developed.C# language is used to design and implement the simulation platform,which can issue train operation plans and generate timetables.By setting interference scenarios,the genetic algorithm is used to solve the optimal adjustment plan,and rescheduling timetables are generated.Effectiveness of the proposed evaluation method in the thesis is present. |
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