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An Alternative Approach for High Speed Railway Carrying Capacity Calculation Based on Multiagent Simulation

Author

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  • Mo Gao
  • Leishan Zhou
  • Yongjun Chen

Abstract

It is a multiobjective mixed integer programming problem that calculates the carrying capacity of high speed railway based on mathematical programming method. The model is complex and difficult to solve, and it is difficult to comprehensively consider the various influencing factors on the train operation. The multiagent theory is employed to calculate high speed railway carrying capacity. In accordance with real operations of high speed railway, a three-layer agent model is developed to simulate the operating process of high speed railway. In the proposed model, railway network agent, line agent, station agent, and train agent are designed, respectively. To validate the proposed model, a case study is performed for Beijing–Shanghai high speed railway by using NetLogo software. The results are consistent with the actual data, which implies that the proposed multiagent method is feasible to calculate the carrying capacity of high speed railway.

Suggested Citation

  • Mo Gao & Leishan Zhou & Yongjun Chen, 2016. "An Alternative Approach for High Speed Railway Carrying Capacity Calculation Based on Multiagent Simulation," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-10, November.
    • Handle: RePEc:hin:jnddns:4278073
    DOI: 10.1155/2016/4278073
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    Cited by:

    1. Camelia Delcea & Liviu-Adrian Cotfas & Liliana Crăciun & Anca Gabriela Molanescu, 2018. "Are Seat and Aisle Interferences Affecting the Overall Airplane Boarding Time? An Agent-Based Approach," Sustainability, MDPI, vol. 10(11), pages 1-23, November.
    2. Camelia Delcea & Liviu-Adrian Cotfas & Nora Chiriță & Ionuț Nica, 2018. "A Two-Door Airplane Boarding Approach When Using Apron Buses," Sustainability, MDPI, vol. 10(10), pages 1-14, October.
    3. Camelia Delcea & Liviu-Adrian Cotfas & Carmen Lenuța Trică & Liliana Crăciun & Anca Gabriela Molanescu, 2019. "Modeling the Consumers Opinion Influence in Online Social Media in the Case of Eco-friendly Products," Sustainability, MDPI, vol. 11(6), pages 1-32, March.

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