Abstract: With the advantages of high performance, strong robustness, and large service range, unmanned aerial vehicle (UAV) swarm systems have been widely used in military and civil scenarios. UAV swarms need to form specific topology shapes autonomously through topology shaping to achieve efficient swarm collaboration mechanisms for specific mission scenarios. Topology shaping typically involves two aspects: the optimal mapping from the initial topology to the target topology and the optimal topology shaping location. These two aspects affect each other and are directly related to the global energy consumption of the UAV swarm. Based on the joint optimization model of UAV swarm topology shaping with global energy consumption minimization as the goal, a generalized solution framework based on the swarm intelligence algorithm is firstly established, and specific solution methods based on the gray wolf optimizer algorithm (GWO), the equilibrium optimizer algorithm (EO) and the poor and rich optimization algorithm (PRO) are proposed. Then the convergence acceleration strategy for solving the optimization model based on the swarm intelligence algorithm is proposed. Simulation results show the effectiveness of the proposed UAV swarm topology shaping method and indicate that the proposed optimization method can achieve convergence within 8 iterations in a typical topology shaping scenario.