Topology optimization, a method for automatically generating structural shapes with high design freedom, is gaining significant attention across various fields, including aerospace, automotive, and architecture. While conventional topology optimization primarily focuses on continuously varying material distribution, explicitly controlling topological changes, such as structural connectivity and the number of holes, remains a challenge for gradient-based methods. This study proposes a heuristic optimization method that explicitly performs topological changes, such as structural connections and disconnections, as well as hole insertion and removal. By locally exploring the design space at each optimization step and selectively introducing changes that yield favorable evaluation values, we anticipate a more efficient improvement of evaluation values compared to conventional approaches. Furthermore, by incorporating processes to correct concave regions smoothly and imposing minimum thickness constraints, the method addresses not only analytical stability but also practical manufacturability. A key feature of this method is its ability to explore diverse structural shapes while improving the evaluation value with a smaller number of simulations. This approach significantly expands the design space for employability in topology optimization and is expected to serve as a practical design support tool in the future.
TAKAHASHI et al. (Wed,) studied this question.