Managing Dynamically Changing Traffic Flows

  • Authors

    • M Karaeva
    • N Napkhonenko
    • V Perevozniuk
    2018-09-15
    https://doi.org/10.14419/ijet.v7i4.3.19791
  • differential equations, development of logistic models, chromosome, gene, genetic algorithm, linear and nonlinear architectures, logistics meta-heuristic methods, organization of transport, optimization methods, passenger traffic, population, system of ur
  • The brief analysis of publications in the field of transport development, the organization and management of urban passenger traffic in the conditions of constantly changing passenger traffics is carried out. The efficiency of using logistic methods is proved by optimization of public passenger transport of the megalopolis. The factors influencing regularity of passenger traffics formation and their dynamic spatial distribution taking into account the main communications between passenger formed points and service providers are revealed. For improvement of traffic flows management the relevance of development of new mathematical models and methods considering relationship of cause and effect between the input and output parameters is established. Methods of solving large-size problems in the conditions of difficult criterion function are considered. Advantages and the prospects of meta-heuristic methods application – genetic algorithms – are shown at the solution of the transport tasks characteristic of unstable streams.

    For solving the objective using a set of genes is proposed which elements represent a chromosome with a certain set of decisions. Restrictions are formulated and operators of casual changes for a work of genetic algorithm are defined. The algorithm allowing to define and range the key input parameters influencing process of providing transport services and to receive parameters for the output correlation analysis is obtained.

     

     

  • References

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  • How to Cite

    Karaeva, M., Napkhonenko, N., & Perevozniuk, V. (2018). Managing Dynamically Changing Traffic Flows. International Journal of Engineering & Technology, 7(4.3), 222-227. https://doi.org/10.14419/ijet.v7i4.3.19791