DG access in a distribution network leads to an intelligent optimization algorithm which can easily fall into local convergence and low optimization rate in the reconstruction. Considering the relationship between the distribution network topological characteristics and the algorithm, an active distribution network reconstruction method based on single loop optimization strategy is proposed by deeply combining the two. First, Levy flight is introduced into the quantum particle swarm optimization algorithm to establish the Levy coefficient quantum particle swarm optimization (LCQPSO) algorithm. Secondly, the adaptive ordered ring matrix based on node voltage in a ring network is proposed as the solution space of the algorithm. Finally, from the corresponding relationship between the distribution network topology and the global optimal solution of the algorithm, a single loop optimization strategy is established. This is dynamically combined with the algorithm. By improving the algorithm, optimizing the solution space, and combining the distribution network topology with the algorithm depth, the global search ability and optimization efficiency of the algorithm is improved. The effectiveness and applicability of the proposed algorithm and strategy are verified by simulation analysis of several power systems. This work is supported by the National Natural Science Foundation of China (No. 51907116).