Machinery & Energetics (Feb 2023)
Agent-based simulation model of multimodal iron ore concentrate transportation
Abstract
Most global supply chains are implemented through the use of some different types of transport. This especially applies to general cargo: iron ore, oil, grain. As the participants in the transport process increase, the risks of delays, interoperational downtime, and delays in deliveries increase. Therefore, the improvement of multimodal cargo transportation remains an urgent scientific and applied problem. The aim of studying was to research technical and operational parameters of the multimodal supply chain of cargo delivery (on the example of iron ore concentrate). The research's aim of the study was realized by the development of an agent-based simulation model. The simulation model is implemented in the Any Logic Research Edition environment with Java SE, as this toolkit allows combining discrete-event and agent-based approaches in the simulation simultaneously. As a result of the experiment with the developed simulation model, it was found that: 1) approximately 40% of the delivery time is spent waiting for the transport unit to load (8%) and freight being under collecting up to the loading rate into the transport unit (33%); 2) the sensitivity experiment of the model has determined that of all the variable technological parameters of the basic model, the difference in the ratio between the rate of loading of the railway train and the sea vessel has the greatest influence on the average time of freight delivery; 3) the relationship between the capacity of the vessel (with a constant rate of mass shipment into the railway train) and the average time of shipment collecting to the rate of loading into the vessel in case of accidental arrival of freight by rail in the transshipment terminal is highly approximate linear dependence. The results of the research can be used to improve the logistics chains for the delivery of iron ore concentrate from Ukraine to other countries
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