To deal with train delays in large high-speed railway stations,a multi-objectivemixedintegernonlinear programming(MO-MINLP)optimization model was *** model used the arrival time,departure time,track occupation,and r...
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To deal with train delays in large high-speed railway stations,a multi-objectivemixedintegernonlinear programming(MO-MINLP)optimization model was *** model used the arrival time,departure time,track occupation,and route selection as the decision variables,and fully considered the station infrastructure layout,train operational requirements,and time standards as limiting *** optimization objectives were to minimize train delays and reduce track and to route *** realize the large-scale and rapid solution of the MO-MINLP model,this study proposed a rolling horizon optimization algorithm that used half an hour as a time interval and solved the rescheduling and platforming problem of each time interval *** numerical experiments,227 train movements under delay circumstances in Hangzhoudong station were optimized by using the proposed model and solution *** results show that the proposed MO-MINLP model could resolve route conflicts,compress unnecessary dwell times,and reduce train delays,and the solution algorithm could efficiently increase the computational *** maximum solution time for optimizing the 227 train movements is 15 min 24 s.
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