Fleet management is the process of overseeing, managing, and coordinating a group of vehicles used for deliveries or services, with the goal of improving logistics, efficiency, and cost-effectiveness.
In the context of optimization and AI, fleet management involves using data-driven insights to enhance vehicle utilization, reduce fuel consumption, and maintain timely deliveries. This process often integrates route optimization, vehicle tracking, maintenance scheduling, and performance analytics. AI-driven fleet management systems can predict maintenance needs to prevent unexpected vehicle breakdowns and use real-time data to adjust routes and schedules dynamically, ensuring the fleet is operating at maximum efficiency.
It also involves optimizing driver assignments based on skills, availability, and familiarity with specific routes.
Advanced fleet management through AI can also make decisions on which vehicle in a mixed fleet with e.g. bicycles, cars, vans, and trucks is best fit for which orders.
Overall, fleet management aims to minimize operational costs, improve customer service levels, and ensure compliance with regulations, making it a critical component in logistics and supply chain management.