вантажні перевезення

The results of the analysis of algorithmic models of machine learning application to the freight transportation process are given in this paper. Analysis of existing research allowed discovering a range of advantages in the application of computational intelligence in logistic systems, including increasing the accuracy of forecasting, reduction of transport costs, increasing the efficiency of cargo delivery, risks reduction, and search for key performance factors. In the research process, the main directions of application of algorithmic models of machine learning were determined.

In recent years decrease in volumes for all types, except imports by types of freight transporta- tion by the railways of Ukraine. The article is devoted to the problem of ensuring mutually beneficial cooperation between cargo owners and freight carriers in the  field of railway transportation in Ukraine. The purpose of the article is to determine the priorities in the area of servicing freight owners by Ukrainian railways to ensure the validity of relevant management decisions by the railway rolling stock operators.