Freight parking and charging optimization toward sustainable urban logistics

Purpose The rapid urbanization and exponential growth of e-commerce have intensified the demand for more efficient but sustainable urban logistics. This research explores the solutions to optimizing urban delivery activities with time windows using electric vehicles while considering the parking availability. Design/methodology/approach A mixed integer linear programming model is formulated to extend electric vehicle routing problem with time windows (EVRPTW) by incorporating parking issues during urban deliveries. Numerical experiments are conducted to assess the model based on random delivery requests. Findings The integration of parking and charging constraints into the EVRPTW model results in severe computational complexity. Parking-related expenses emerge as the dominant cost in urban logistics, which reshapes traditional cost structures. The results present the importance of strategic parking management in urban logistics and necessitate algorithmic design. Originality/value Our research contributes to urban logistics by integrating parking and charging optimization into the classic EVRPTW model. The proposed model provides a more realistic and comprehensive framework for planning electric vehicle-based urban deliveries. Our findings also offer valuable managerial implications for practitioners to achieve a transition toward more efficient and sustainable urban logistics systems.