Abstract: The maintenance and scheduling of distribution networks is an important part of ensuring the safe and stable operation of power systems. However, traditional maintenance and scheduling methods have low solving efficiency and are prone to getting stuck in local optima when dealing with complex optimization problems with multiple objectives and constraints. Therefore, a distribution network maintenance and scheduling method based on an improved adaptive genetic algorithm is designed. An adaptive crossover rate and mutation rate adjustment mechanism into traditional genetic algorithms is introduced, achieving real-time adjustment of genetic operation probabilities. It also incorporates an elite retention strategy and an adaptive population size adjustment mechanism to enhance the algorithm’s global search capability. The experimental results show that the maintenance scheduling efficiency of the method proposed in this paper is above 95%, laying an important foundation for the safe and stable operation of the distribution network.