логістичні системи

This paper presents a method for predicting delivery delays and optimizing routes in logistics systems using Graph Neural Networks (GNNs). Modern logistics networks face numerous challenges due to unpredictable delays caused by dynamic traffic conditions, weather events, vehicle malfunctions, and other external factors. Traditional machine learning methods, such as regression models or decision trees, often prove inadequate in modeling such complex spatiotemporal dependencies inherent in logistical environments.

The integration of artificial intelligence into the logistics industry is a rapidly evolving field with the potential to revolutionize the way goods are transported and managed. Artificial intelligence can be used to optimize a wide range of logistics processes, from demand forecasting and route planning to warehouse management and customer service. However, the integration of artificial intelligence also raises a number of technical and ethical issues that need to be addressed to ensure its successful implementation.