OPTIMIZATION OF DECENTRALIZED LAST-MILE DELIVERY USING ARTIFICIAL INTELLIGENCE

In today's e-commerce environment and the ever-growing demand for fast and efficient delivery services, optimizing the last mile is becoming critical to improving the competitiveness of logistics companies. One of the most effective solutions is to implement a decentralized delivery model that uses local centers or micro hubs to optimize routes. This solution reduces the time of delivery to the end consumer, reducing the load on central warehouses, and increases the flexibility and reliability of the logistics system. Artificial intelligence (AI) plays a key role in improving the efficiency of decentralized delivery. By analyzing large amounts of data in real time, AI helps to optimize delivery routes, reducing fuel costs and reducing the number of vehicles, which at the same time has a positive impact on the environment. Machine learning algorithms allow routes to be automatically adapted to changes in traffic, weather conditions, and traffic levels, which is especially important in large cities with heavy traffic. In addition, AI ensures efficient inventory management in local centers, which allows for better planning of replenishment of goods and reduces storage costs. Lastmile management with AI also contributes to the improvement of customer service. The system can take into account individual consumer preferences, for example, determine the optimal delivery time for customer convenience, and provide accurate information about the time of arrival of the courier. This not only increases customer satisfaction, but also reduces the likelihood of repeated deliveries in case the recipient is not at the location. Thus, the decentralized delivery model optimized by AI not only reduces operational costs and improves the efficiency of logistics processes, but also contributes to a more environmentally friendly and customer-oriented service.