The current risk assessment methods for dangerous goods roads have the problem of being unable to cope with complex road conditions and the influence of multiple factors. This study extends 9 tertiary indicators from three secondary indicators: personnel factors, vehicle factors, and road factors, to evaluate the transportation risk of dangerous goods. After calculating the weights of each indicator, this study improves the parameters of the particle swarm algorithm using the aggregation and foraging behavior of artificial fish, and uses the improved algorithm to solve the optimal solution for the cost of dangerous goods road transportation. After experimental verification, the improved hybrid algorithm has optimized the path transportation time by 13.9 % compared to a single algorithm model. The total risk of simultaneously improving the algorithm was 0.8863, and the total transportation distance was 861 km, both lower than other algorithms. The comprehensive analysis shows that the established model is reasonable, and the designed improved hybrid algorithm can improve the efficiency of the transportation industry, while also contributing to the improvement of the current cost status of dangerous goods road transportation.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Risk assessment and hybrid algorithm transportation path optimization model for road transport of dangerous goods


    Beteiligte:
    Qiankun Jiang (Autor:in) / Haiyan Wang (Autor:in)


    Erscheinungsdatum :

    2025




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt







    Dangerous goods transportation path planning method under uncertain time-varying road network

    ZHENG SONG / LIU ZHIGUO / GE MING et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    Dangerous goods transportation carriage and dangerous goods transportation vehicle

    WANG GUOFENG | Europäisches Patentamt | 2021

    Freier Zugriff