Revealing the causes of delays at transit points along an intermodal grain supply chain

This study’s object is the transport and technological system of grain supply along international routes. The issue considered is the emergence of excess cargo weight at the junctions of various types of transport. The study was conducted on the basis of a constructed simulation model built according to the agent and discrete-event principles. It covers both the maximum transportation volumes in one of the Ukraine’s oblasts in 2021 (880 thousand tons) and the forecasted indicators (1–1.5 million tons per year). The application of the model has made it possible to determine the optimal parameters for the fleet of vehicles in a supply chain, guided by the system criterion – minimization of the average delivery time of one ton of grain. It was established that for transporting 1 million tons of grain per year, the optimal composition of the transport fleet should include 92 trucks and four railroad routes. Patterns in the formation of excess cargo weight depending on the estimated composition of vehicles were also determined. With a planned transportation intensity of 1 million tons per year, reducing the number of trucks by 12 units could lead to the accumulation of 237 thousand tons of cargo mass at transit points. Reducing the number of railroad routes by one unit would lead to the accumulation of 544 thousand tons of cargo mass, which corresponds to USD 106 million. The proposed model makes it possible to assess the consequences of delays in delivery, as well as the formation of excess cargo mass at transit logistics terminals and grain elevators

Authors

Institutions

Publication Details

Journal
Eastern-European Journal of Enterprise Technologies
Published
2025-08-30
DOI
https://doi.org/10.15587/1729-4061.2025.338166
Primary Topic
Logistics and Infrastructure Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Revealing the causes of delays at transit points along an intermodal grain supply chain

Viacheslav Matsiuk, Olena Pavlenko, А. М. Окороков, Ірина Леонідівна Журавель et al.
Eastern-European Journal of Enterprise Technologies
Logistics and Infrastructure Analysis
article

Revealing the causes of delays at transit points along an intermodal grain supply chain

Viacheslav Matsiuk, Olena Pavlenko, А. М. Окороков, Ірина Леонідівна Журавель, Yurii Khomenko
article en

Abstract

This study’s object is the transport and technological system of grain supply along international routes. The issue considered is the emergence of excess cargo weight at the junctions of various types of transport. The study was conducted on the basis of a constructed simulation model built according to the agent and discrete-event principles. It covers both the maximum transportation volumes in one of the Ukraine’s oblasts in 2021 (880 thousand tons) and the forecasted indicators (1–1.5 million tons per year). The application of the model has made it possible to determine the optimal parameters for the fleet of vehicles in a supply chain, guided by the system criterion – minimization of the average delivery time of one ton of grain. It was established that for transporting 1 million tons of grain per year, the optimal composition of the transport fleet should include 92 trucks and four railroad routes. Patterns in the formation of excess cargo weight depending on the estimated composition of vehicles were also determined. With a planned transportation intensity of 1 million tons per year, reducing the number of trucks by 12 units could lead to the accumulation of 237 thousand tons of cargo mass at transit points. Reducing the number of railroad routes by one unit would lead to the accumulation of 544 thousand tons of cargo mass, which corresponds to USD 106 million. The proposed model makes it possible to assess the consequences of delays in delivery, as well as the formation of excess cargo mass at transit logistics terminals and grain elevators

Eastern-European Journal of Enterprise TechnologiesVol. 4(3 (136))
National University of Life and Environmental Sciences of Ukraine (UA), Voronezh State University of Engineering Technologies (RU), Ukrainian State University of Science and Technologies (UA)
Openalex Percentile: Top 72%
Logistics and Infrastructure Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.