To improve the efficiency of lightweight optimization for stiffened panels， an efficient dynamic sequential lightweight optimization method based on Voronoi is proposed. Above all， the influences of the mesh size of the stiffened panel skin and strings on load-carrying capacity and the buckling modes of the structure are analyzed based on the parametric model. Furthermore， the dynamic mesh partition is realized according to the height-thickness of the web to balance the accuracy and efficiency of post-buckling analysis.Then， a dynamic sequential approximate optimization incorporating an exploration strategy and an exploitation strategy is proposed. Sampling by Voronoi focuses on global space exploration， while sampling by approximate optimal solution focuses on local exploitation. The parallel sampling with both explorative and exploitative performance is realized by dynamic sampling iteration to convergence， which improved the convergence precision and computational efficiency of the algorithm.Ultimately， the proposed algorithm is applied to the lightweight design of stiffened panels， and compared with the traditional sequential approximation optimization method. The results reveal that the proposed method needs fewer initial sample points and less iteration times to achieve higher optimization accuracy， and obtains an optimized structure with a weight reduction of 32.6% compared with the initial design，which indicates that the proposed method is validated for the prospect of engineering applications.