The unique capability of additive manufacturing (AM) to deal with complex geometries drives the traditional topological optimization and lightweight design to a new paradigm. However, AM constraints are still hard to integrate into the optimization procedure, and the multiple conflict design objectives are difficult to handle when making decisions. In addition, the computation cost is usually high. To solve these problems, this paper proposes a new generative design method with a manufacturing validation so that the designer’s decision-making is more efficient. This method first uses a CSG (constructive solid geometry)-based technique to generate and represent topology geometries with smooth boundaries and parametric control. Then, a genetic algorithm is used to operate the CSG geometries in order to search for optimal solutions. Finally, a set of finite optimal non-dominated design solutions on the Pareto front are located and presented for the designer’s further decision making. The proposed method can generate a large quantity of qualified optimal alternative solutions with smooth geometric boundaries but the computation cost is less. It is promising to design qualified solutions, especially for lightweight structure design, in AM. Several demonstration examples and comparison case studies with existing methods in literature are presented at the end of this paper to show the advantages.

增材制造（AM）应对复杂几何形状的独特能力将传统的拓扑优化和轻量级设计推向了新的范式。但是，AM约束仍然很难集成到优化过程中，并且在制定决策时很难处理多个冲突设计目标。另外，计算成本通常很高。为了解决这些问题，本文提出了一种新的生成设计方法，并通过了制造验证，从而使设计师的决策更加有效。该方法首先使用基于CSG（构造实体几何）的技术来生成和表示具有平滑边界和参数控制的拓扑几何。然后，使用遗传算法来操作CSG几何形状，以寻找最佳解决方案。最后，在Pareto前端找到一组有限的最优非支配设计解决方案，并提供给设计者进一步的决策。所提方法可以生成大量具有光滑几何边界的合格最优替代解，但计算量较小。在AM中设计合格的解决方案（尤其是轻型结构设计）很有希望。最后，给出了一些演示示例和与现有文献中方法进行的比较案例研究，以显示其优势。在AM中设计合格的解决方案（尤其是轻型结构设计）很有希望。最后，给出了一些演示示例和与现有文献中方法进行的比较案例研究，以显示其优势。在AM中设计合格的解决方案（尤其是轻型结构设计）很有希望。最后，给出了一些演示示例和与现有文献中方法进行的比较案例研究，以显示其优势。