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Train Operational Plan Optimization of Rail Transit Connecting to Airport Ground Transport Center

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Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019 (EITRT 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 640))

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Abstract

With the increasing demand for air transport, the problem of traffic connection between airport and city is becoming more and more severe. Rail transit with the characteristics of speed, punctuality, and larger capacity plays an increasingly significant role in connecting traffic between airport and urban center. From the perspectives of both the passengers and train operators, this paper establishes a multi-objective optimization model of rail transit train operation plan for airport ground transport center (GTC), constructs three objective functions, including passenger waiting time, passenger comfort, and operator income, and develops a genetic algorithm to solve the fuzzy optimal solution of the model. Taking Beijing Rail Transit Airport Line as the research object, this paper validates the proposed model and evaluates the scheme by using typical workday passenger flow data. The results show that our model can provide decision-making basis for the optimization of train dispatch.

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Acknowledgements

This work is supported by National Key R&D Program of China (Grant No. 2018YFB1601200).

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Correspondence to Ailing Huang .

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Li, Y., Xu, X., Xu, R., Huang, A. (2020). Train Operational Plan Optimization of Rail Transit Connecting to Airport Ground Transport Center. In: Liu, B., Jia, L., Qin, Y., Liu, Z., Diao, L., An, M. (eds) Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019. EITRT 2019. Lecture Notes in Electrical Engineering, vol 640. Springer, Singapore. https://doi.org/10.1007/978-981-15-2914-6_63

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  • DOI: https://doi.org/10.1007/978-981-15-2914-6_63

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2913-9

  • Online ISBN: 978-981-15-2914-6

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