Logistics delivery efficiency and environmental sustainability have become important research areas in the construction of smart cities. In order to further enhance the effectiveness of sustainable logistics and distribution operations in existing smart cities and reduce energy consumption, a multi-objective problem function is constructed for electric vehicle logistics and distribution. Based on the cuckoo algorithm, this study introduces adaptive step size adjustment, bird egg dynamic discovery strategy, and flight reconstruction strategy to optimize the search accuracy and global convergence ability of distribution paths. Finally, a new logistics distribution operation path mechanism is proposed. The new algorithm had an average delivery energy consumption of 149.67 J–160.72 J and a task processing time of 6.32s–8.42s. Compared with the other three advanced planning algorithms, it significantly reduced delivery costs and resource occupation, and improved delivery efficiency by more than 25%. The lowest delivery cost per kilometer was only 1.1 yuan, and the highest delivery efficiency was 40 kilometers per hour. From this, the method can effectively improve operational efficiency and achieve sustainable development in smart city logistics distribution, providing certain reference value for the subsequent development of this field.