Development of a simulation model of transport enterprise operation when carrying various types of cargo along international routes
DOI:
https://doi.org/10.15587/1729-4061.2025.337913Keywords:
transport enterprise, international transportation, simulation model, motor vehicleAbstract
This study’s object is the process that organizes and plans the work of a transport enterprise when transporting general, dangerous, and oversized cargo along international roads.
The task addressed is the need to compile recommendations for determining the required number of personnel and the duration of rendering transport services depending on the type of cargo received for service.
A simulation model of the work of a transport enterprise when organizing international road transportation has been built and implemented in the GPSS World simulation modeling automation package. The model involves determining the duration of transport service and planning the personnel support for a transport enterprise according to the functional division of labor.
When building the model, the duration of the types of work provided by specialists of the transport enterprise when transporting general, dangerous, and oversized cargo was taken into account.
In addition, the model takes into account the probability of errors and delays at each stage of service. The average duration of the delay in the event of errors is also determined, which could make it possible to set additional time for engaging a separate specialist to eliminate them.
The application of the devised model in practice would allow owners of transport enterprises to organize business processes depending on the available type of rolling stock. It could also make it possible to determine the optimal number of specialists of various profiles required for organizing transport services for the customer.
At the same time, the duration of transport services for the delivery of various types of cargo will be reduced by 8–14% while the number of specialists of the transport enterprise – by 10–15%; in turn, the throughput will increase by 7–16%
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Copyright (c) 2025 Ievgenii Lebid, Nataliia Luzhanska, Iryna Lebid, Alexander Mazurenko, Inesa Halona, Oleksii Tihov
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