Integrated Rolling Stock And Crew Rescheduling Optimization Model And Algorithm For High Speed Railway

The completion of high-speed railway transportation channels and inter-city rapid transportation systems such as Beijing-Shanghai and Beijing-Guangzhou marked the era of China's high-speed railways entering the networked operation.However,compared with the innovative achievements in the "hardware" facilities such as high-speed EMUs,the "software" of high-speed rail operation management has not yet formed a relatively mature theory and method.Therefore,the improvement of the efficiency of high-speed railway operation management has become a hot issue that needs urgent researches.When the railway operation encounters disturbances,the train operation deviates from the initial status.In order to resume the normal operation of the train as soon as possible,multi-type dispatchers are usually set up.Each group of dispatchers relies on the established dispatching rules and their own experience to reschedule the timetable,the rolling stock plan and the crew plan.However,due to the independent and sequential rescheduling of various sub-plans,the rescheduled operation plan will often be uncoordinated.For example,the trains in the rescheduled timetable will be canceled due to the lack of rolling stocks,or lack of crews.At the same time,due to the lack of support from intelligent decision-making systems,it is difficult to guarantee the quality of the rescheduling plans,and it is even unable to fully utilize the driving resources to achieve effective response to sudden disturbances.Therefore,in order to ensure the overall feasibility of the rescheduling plans and improve its optimization performance,it is necessary to explore the integrated model and solution algorithm for each sub-plan.This essay will first investigate the similarity between rolling stock rescheduling and crew rescheduling,followed by building up formalized description models for integrated rolling stock and crew rescheduling based on multi-commodity flow model.The objective of the integrated model is to minimize the difference between the adjusted and original schedule and reduce the cancellations of trips caused by the shortage of rolling stocks or crews.In order to speed up solution process and improve solution quality.This essay will propose a customized ant colony algorithm.Furthermore,the data for case studies will be prepared by collecting historical train monitoring data from Beijing-Shanghai high-speed railway line.A series of practical experiments will be conducted to test the proposed models and algorithms and the calculation results show that comparing with sequential approach a better objective function value was optimized by 62.5%and RAM consumption was reduced by 44.4%with short computation time.Finally,the influential factors in the objective function would be calibrated to show the impacts caused by different parameters such as additional cancellations,difference between the original plan and rescheduled plan.The implementation of this project will be beneficial for improving the quality of high speed rail rescheduling operations and providing theoretical guidelines and scientific basis for generating relatively optimal rescheduling plan during a time limitation and meeting passengers' expectations on safe,efficient and punctual train services.