Principles of modeling the logistics complex system using machine learning.

Abstract

The article describes the principles of modeling the logistics complex system using machine learning. It is emphasized that with the help of machine learning, a computer can be taught to detect certain patterns, meeting which, it will perform certain actions, which can be: calculation of the shortest delivery route, instant calculation of the cost of transportation, optimization of schedules, as well as optimization of equipment operation. It is emphasized that the application of artificial intelligence and machine learning for inventory and warehouse management allows to optimize the costs of storage and inventory management, as well as to reduce the probability of errors. Using artificial intelligence to analyze data about orders and consumer behavior can improve demand forecasting and reduce inventory costs. The use of artificial intelligence algorithms allows you to optimize delivery routes and improve the efficiency of the delivery process. A logistics complex system using machine learning can automate routine tasks in warehouses and order processing centers, which will reduce personnel costs and increase productivity. The use of artificial intelligence allows you to create logistics management software systems that can effectively coordinate logistics and delivery processes. The structure of the business process of the logistics complex management system is presented, the application of which allows you to increase efficiency and reduce processing time, due to the use of such technologies as: data collection from sensors installed on vehicles, warehouses and other objects of the logistics infrastructure; the use of RFID tags and other technologies that allow tracking the location of goods and controlling their movement; using data obtained from communication networks, such as the Internet of Things (IoT), to monitor equipment and processes remotely; analysis of external information; using software and programs to manage logistics processes that integrate all collected data and automate a number of processes