Abstract: In response to the increasing demand for structural optimization and 3D printing, proposed is an optimization method that considered structural performance and 3D printability in layout and geometry optimization, which generated self-supporting optimized structures. The methodology proposed was implemented through a modular Python framework. Rapid layout optimization for multiple load cases was carried out by combining the "member adding method". The members that violated the self-supporting constraint were removed in the ground structures. A non-linear geometry optimization was carried out with member filtering and node merging operations to simplify the structures. Multiple examples were selected for structural optimization, solid generation, printing path generation, and 3D printing. The results show that the optimized structure obtained by the method has no more than a 5% increase in material relative to the theoretical optimal solution without considering manufacturing constraints, verifying its effectiveness.