Electric Vehicle Routing Problem

The Electric Vehicle Routing Problem (EVRP) focuses on optimizing delivery routes for electric vehicles, considering factors like limited range, charging infrastructure, and time constraints to minimize travel time and energy consumption. Current research emphasizes the use of advanced algorithms, including deep reinforcement learning (e.g., transformer networks) and hyper-heuristics combining simulated annealing and reinforcement learning, to efficiently solve complex EVRP variants, such as those incorporating time windows and vehicle-to-grid energy supply. These improvements are crucial for optimizing logistics, reducing operational costs, and promoting the wider adoption of electric vehicles in various sectors, from last-mile delivery to emergency power supply. The development of more efficient and robust algorithms is driving significant progress in both theoretical understanding and practical applications of EVRP.