3 papers
math.OC2025
Wasserstein crossover for evolutionary algorithm-based topology optimization
Taisei Kii, Kentaro Yaji, Hiroshi Teramoto +1
Evolutionary algorithms (EAs) are promising approaches for non-differentiable or strongly multimodal topology optimization problems, but they often suffer from the curse of dimensi…
math.OC2025
Maximum stress minimization via data-driven multifidelity topology design
Misato Kato, Taisei Kii, Kentaro Yaji +1
The maximum stress minimization problem is among the most important topics for structural design. The conventional gradient-based topology optimization methods require transforming…
math.OC2024
Data-driven topology design with persistent homology for enhancing population diversity
Taisei Kii, Kentaro Yaji, Hiroshi Teramoto +1
This paper proposes a selection strategy for enhancing population diversity in data-driven topology design (DDTD), a topology optimization framework based on evolutionary algorithm…