This paper presents an effective approach to address the challenge of rapidly restoring train operation order and automatically generating scheduling optimization schemes during abnormal events. The study focuses on high-speed railway, and establishes a high-speed railway train operation adjustment model, with the primary objective of minimizing the weighted total arrival delay time while satisfying various time and capacity constraints. To overcome the NP-hard nature of the problem, we propose a genetic algorithm approach with an appropriate coding mode, fitness function, crossover, and mutation rules. To validate the proposed model and algorithm, we use the operational data from the Beijing-Shanghai high-speed railway. The results of comparing the advantages and disadvantages of the genetic algorithm with the interval-only accelerated operation method demonstrate the feasibility and effectiveness of genetic algorithm, which can provide decision support for dispatching high-speed railway train operation scheduling.


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    Titel :

    Research on High-Speed Railway Timetable Rescheduling Based on Genetic Algorithm


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Qin, Yong (Herausgeber:in) / Jia, Limin (Herausgeber:in) / Yang, Jianwei (Herausgeber:in) / Diao, Lijun (Herausgeber:in) / Yao, Dechen (Herausgeber:in) / An, Min (Herausgeber:in) / Du, Xinyi (Autor:in) / Wang, Li (Autor:in) / Wang, Xianghao (Autor:in)

    Kongress:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2023 ; Beijing, China October 19, 2023 - October 21, 2023



    Erscheinungsdatum :

    03.02.2024


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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