Para mejorar la eficiencia de gestión de los huertos de duraznos, este documento considera el esquema de operación cooperativa de múltiples tractores no tripulados. Según la situación actual, este documento construye el modelo de planificación de rutas de múltiples tractores no tripulados en un huerto de duraznos estándar, diseña la función objetivo para optimizar el tiempo total de giro y el tiempo total de operación de acuerdo con los parámetros de conducción del tractor, y lo resuelve mediante la mejora del algoritmo de evolución diferencial. Aiming at the premature convergence problem, the permutation matrix is introduced to represent the driving paths of multiple unmanned tractors. Then, the dynamic parameters are adopted to make the parameters change with the number of iterations, and the elite selection strategy is used to eliminate the redundant feasible solutions. An Adaptive Elite Differential Evolution (AEDE) algorithm suitable for multi-tractor path optimization is proposed. The results show that, compared with the traditional Differential Evolution algorithm (Differential Evolution, DE), the total turning time and total operating time in the rectangular peach orchard optimized by AEDE are reduced by 3.34% and 0.87%, respectively. Compared with the block operation, the total turning time and total operating time of the AEDE-optimized rectangular peach orchard operation path were reduced by 37.37% and 9.47%, respectively. Experiments show that AEDE, which optimizes the operating path of multi-tractors in standard peach orchards, is able to improve the efficiency and reduce the operating time.