Devising an automated technology to organize the railroad transportation of containers for intermodal deliveries based on the theory of point processes

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.195071

Keywords:

intermodal container transportation, random point processes, stochastic optimization, railroad container transportation

Abstract

A significant number of problems and associated additional expenses emerge for operators due to imperfections in the existing technology of operational planning of the functioning of railroad transport as a part of the intermodal transportation system. The source of problems is not only the process of transportation of containers by rail but also the processes that occur immediately before and after it. These processes are uncertain because of their probabilistic nature. Their random nature provokes additional idle time of rolling stock, causes additional operator expenses, and reduces the quality of customer service. However, the direct influence on them is very difficult or economically inexpedient.

The study shows that taking into account the probabilistic nature of these processes to reduce their negative impact is most effective precisely at the stage of operational planning of the functioning of railroad enterprises involved in the intermodal transportation process. One should note that it is necessary to take into account random factors of processes of formation and processing of container trains at stations, their movement along sections and transfer to a port simultaneously in order to improve the quality of such planning. However, the arrival of containers at terminal railroad stations requires special attention.

It has been proven that the key to the solution to the problem of synchronization of the processes is the formation of automated technology for the organization of the transportation of containers by railroad.

We have formalized the technological process of formation and movement of container trains to seaports in the form of a model of stochastic optimization using a mathematical apparatus from the theory of point processes for this purpose. The optimization criterion for this model represents the operating expenses of an operator for the organization of the railroad part of intermodal transportation. The stochastic nature of the model gives a possibility to find the optimal parameters of the operational plan for the organization of container transportation while controlling a level of certainty in the possibility of implementation of the plan taking into account the probabilistic nature of the constituent processes.

Based on the developed model, software was created in the MATLAB programming environment and an automated technology for moving container trains was formed. The application of the proposed model in the formation of railroad container transportation technology could reduce operating expenses of a railroad part of intermodal container transportation by at least 10 %

Author Biographies

Tetiana Butko, Ukrainian State University of Railway Transport Feuerbacha sq., 7, Kharkiv, Ukraine, 61050

Doctor of Technical Sciences, Professor

Department of Operational Work Management

Viktor Prokhorov, Ukrainian State University of Railway Transport Feuerbacha sq., 7, Kharkiv, Ukraine, 61050

PhD, Associate Professor

Department of Operational Work Management

Alina Kolisnyk, Ukrainian State University of Railway Transport Feuerbacha sq., 7, Kharkiv, Ukraine, 61050

Postgraduate Student

Department of Operational Work Management

Larysa Parkhomenko, Ukrainian State University of Railway Transport Feuerbacha sq., 7, Kharkiv, Ukraine, 61050

PhD, Аssociate Рrofessor

Department of Operational Work Management

References

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Published

2020-02-29

How to Cite

Butko, T., Prokhorov, V., Kolisnyk, A., & Parkhomenko, L. (2020). Devising an automated technology to organize the railroad transportation of containers for intermodal deliveries based on the theory of point processes. Eastern-European Journal of Enterprise Technologies, 1(3 (103), 6–12. https://doi.org/10.15587/1729-4061.2020.195071

Issue

Section

Control processes