In charging station services, user charging requirements limit the layout optimization of charging stations to realize total cost minimization. By combining the k-center algorithm and cloud model particle swarm algorithm, this study puts forward a method to improve the global search ability of the adaptive parameter adjustment strategy. A simulation is performed accordingly. Results show that when solving the layout optimization problem for charging stations, the improved adaptive hybrid algorithm that combines the k-center and cloud model particle swarm algorithm outperforms the original cloud model particle swarm algorithm and the basic particle swarm optimization algorithm. The improved algorithm is thus effective.


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    Titel :

    Improved Particle Swarm Optimization Algorithm to Solve the Problem of Layout Optimization of Electric Vehicle Charging Stations


    Beteiligte:
    Qi, Lin (Autor:in) / Yao, Jian (Autor:in) / Wang, Xin-yue (Autor:in)


    Erscheinungsdatum :

    2018-06-01


    Format / Umfang :

    82018-01-01 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt



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