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Optimization of Subway Departure Timetable by Genetic Algorithm

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International Symposium for Intelligent Transportation and Smart City (ITASC) 2019 Proceedings (ITASC 2019)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 127))

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Abstract

This paper the objective constraints such as the number of train groups available for use and the basic interests of the operating company, and optimizes the departure time of urban rail transit according to the existing passenger flow characteristics change. Based on the characteristics of passengers’travel behavior and the habits of taking urban rail transit, a mathematical model with the objective function as the average waiting time of passengers is constructed. Using genetic algorithm to solve the model reasonably, it is found that the optimized scheme can effectively shorten the average waiting time of passengers under the conditions of satisfying various constraints.

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Authors and Affiliations

  1. The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, No. 4800 Cao’an Road, Shanghai, 201804, China

    Junxiang He, Xiaoqing Zeng, Peiran Ying, Xinchen Xu & Yizeng Wang

Authors
  1. Junxiang He
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  2. Xiaoqing Zeng
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  3. Peiran Ying
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  4. Xinchen Xu
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  5. Yizeng Wang
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Corresponding author

Correspondence to Yizeng Wang .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, Shanghai, China

    Xiaoqing Zeng

  2. Department of Geotechnical Engineering, Tongji University , Shanghai, Shanghai, China

    Xiongyao Xie

  3. Shanghai Jiao Tong University , Shanghai, Shanghai, China

    Jian Sun

  4. School of Environmental Science and Engineering, Tongji University , Shanghai, Shanghai, China

    Limin Ma

  5. School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA

    Yinong Chen

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© 2019 Springer Nature Singapore Pte Ltd.

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He, J., Zeng, X., Ying, P., Xu, X., Wang, Y. (2019). Optimization of Subway Departure Timetable by Genetic Algorithm. In: Zeng, X., Xie, X., Sun, J., Ma, L., Chen, Y. (eds) International Symposium for Intelligent Transportation and Smart City (ITASC) 2019 Proceedings. ITASC 2019. Smart Innovation, Systems and Technologies, vol 127. Springer, Singapore. https://doi.org/10.1007/978-981-13-7542-2_17

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  • DOI: https://doi.org/10.1007/978-981-13-7542-2_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-7541-5

  • Online ISBN: 978-981-13-7542-2

  • eBook Packages: EngineeringEngineering (R0)

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