FLEET Management

Fleet management research focuses on optimizing the operation of diverse fleets, from autonomous delivery robots to urban air mobility vehicles and mining trucks, aiming to improve efficiency, resilience, and profitability. Current research emphasizes the development and application of advanced algorithms, including reinforcement learning, graph neural networks, and hybrid combinatorial optimization methods, often within sophisticated simulation environments to account for real-world uncertainties and operational constraints. These advancements hold significant potential for improving resource allocation, reducing operational costs, and enhancing the sustainability of various transportation and logistics systems.