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An Optimization Model for Rescheduling Trains to Serve Unpredicted Large Passenger Flow

Junduo Zhao
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China / School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China

Haiying Li
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China /

Lingyun Meng
School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China

Francesco Corman
Institute for Transport Planning and Systems (IVT), ETH Zurich, Zurich, Switzerland

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Ingår i: RailNorrköping 2019. 8th International Conference on Railway Operations Modelling and Analysis (ICROMA), Norrköping, Sweden, June 17th – 20th, 2019

Linköping Electronic Conference Proceedings 69:81, s. 1229-1243

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Publicerad: 2019-09-13

ISBN: 978-91-7929-992-7

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

As the separation of vertically-integrated organizations in railway transportation, not only the competitive but also the collaboration between different operating companies and different modes should be considered emphatically in the rapidly changing multimodal transportation market. This paper tries to solve the Train Timetable Problem for serving Unpredicted Large Passenger Flow causing by the stop of air traffic in collaborating with air transportation companies. We address the Unpredicted Large Passenger Flow as a perturbation in normal train dispatching and solve this problem through an optimization approach. Two strategies of reassigning remaining seats and inserting new trains are adopted to establish integer programming model in dispatching to evacuate unpredicted passengers. The proposed model is solved by a standard CPLEX solver and test through a study case. The effectiveness of the proposed model is demonstrated in the study case and both two strategies take part in serving ULPF.

Nyckelord

Train rescheduling, Collaboration, Unpredicted large passenger flow, Inserting new trains

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