Abstract
The paper defines a simplified model of dynamic structures characteristic of the representation of traffic flows during transportation by various modes of transport. It is assumed that in each node of the transport network, the cargo flow can be distributed along branches corresponding to certain possible modes of transportation. The main parameters of branching are the share of the total volume of cargo transported by this method and the time of progress along the selected branch. A linear combination of «split» volumes of cargo flow with coefficients – volume fractions and a parameter – travel time for each transport node of the logistics chain form a basic element. The possibility of serial connection of such structures into a linear network equivalent to the original one is proved. Coefficients and time parameters in simple cases are set by expert means, in more complex cases, taking into account possible ranges of values depending on specific transport infrastructures and qualitative criteria, they are calculated using machine learning.
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