At present, China’s urban railway is faced with a large number of insufficient maintenance of failed components and surplus maintenance of normal components. It is urgent to carry out research on the generation of maintenance strategy of urban railway. As to satisfy the demand of transportation capacity in different periods, improve the safety of urban railway operation, and reduce the cost of urban railway maintenance. Particle swarm optimization is a stochastic global optimization method. It can be applied to find the optimal region in the complex search space by the interaction between particles. Particle swarm optimization algorithm is improved through position and particle variation similarity, which is presented in this paper. Based on this improved algorithm, a maintenance strategy generation for urban railway is proposed. The results from a case study show that the operation cost can be reduced by using the improved particle swarm optimization algorithm.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Maintenance Strategy Generation for Urban Railway Based on Improved Particle Swarm Optimization Algorithm


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Qin, Yong (Herausgeber:in) / Jia, Limin (Herausgeber:in) / Liu, Baoming (Herausgeber:in) / Liu, Zhigang (Herausgeber:in) / Diao, Lijun (Herausgeber:in) / An, Min (Herausgeber:in) / He, Zhichao (Autor:in) / Xia, Zhicheng (Autor:in) / Wang, Yanhui (Autor:in) / Li, Lijie (Autor:in)

    Kongress:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2019 ; Qingdao, China October 25, 2019 - October 27, 2019



    Erscheinungsdatum :

    04.04.2020


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Maintenance Strategy Generation for Urban Railway Based on Improved Particle Swarm Optimization Algorithm

    He, Zhichao / Xia, Zhicheng / Wang, Yanhui et al. | British Library Conference Proceedings | 2020



    Improved particle filter algorithm based on chaos particle swarm optimization

    Wang, Ershen / Pang, Tao / Qu, Pingping et al. | British Library Online Contents | 2016


    Improved multi-objective particle swarm optimization algorithm

    Baoning, L. / Weiguo, Z. / Guangwen, L. et al. | British Library Online Contents | 2013


    Expressway and urban local road connection section control strategy optimization method based on particle swarm optimization algorithm

    ZHANG JIAN / WU BINGHAN / YANG XUDONG et al. | Europäisches Patentamt | 2024

    Freier Zugriff